data
dict |
|---|
{
"issue": {
"id": "12OmNyYm2vr",
"title": "Dec.",
"year": "2007",
"issueNum": "12",
"idPrefix": "si",
"pubType": "journal",
"volume": "15",
"label": "Dec.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxAStYw",
"doi": "10.1109/TVLSI.2007.909807",
"abstract": "As the VLSI feature size has already decreased below lithographic wavelength, the printability problem, due to strong diffraction effects, poses a serious threat to the progress of VLSI technology. A circuit layout with poor printability implies that it is difficult to make the printed features on wafers follow designed shapes without distortions. The development of resolution enhancement techniques (RET) can alleviate the printability problem but cannot reverse the trend of deterioration. Moreover, over-usage of RET may dramatically increase photo-mask cost and increase the cycle time for volume production. Thus, there is a strong demand to consider the subwavelength printability problem in circuit layout designs. However, layout printability optimization should not degrade circuit timing performance. In this paper, we introduce a wire sizing and spacing method to improve wire printability with minimal adverse impact on interconnect timing performance. A new printability model is proposed to handle partially coherent illuminations. The complex printability and timing optimization problem is solved in a two-phase approach. The difficulty of the printability optimization due to its multimodal nature is handled with a sensitivity-based heuristic. A coupling aware timing driven continuous wire sizing algorithm is also provided. Lithographic simulation results show that our approach can improve the printability in term of edge placement error (EPE) by 20%-40% without violating timing, wire width, and spacing constraints.",
"abstracts": [
{
"abstractType": "Regular",
"content": "As the VLSI feature size has already decreased below lithographic wavelength, the printability problem, due to strong diffraction effects, poses a serious threat to the progress of VLSI technology. A circuit layout with poor printability implies that it is difficult to make the printed features on wafers follow designed shapes without distortions. The development of resolution enhancement techniques (RET) can alleviate the printability problem but cannot reverse the trend of deterioration. Moreover, over-usage of RET may dramatically increase photo-mask cost and increase the cycle time for volume production. Thus, there is a strong demand to consider the subwavelength printability problem in circuit layout designs. However, layout printability optimization should not degrade circuit timing performance. In this paper, we introduce a wire sizing and spacing method to improve wire printability with minimal adverse impact on interconnect timing performance. A new printability model is proposed to handle partially coherent illuminations. The complex printability and timing optimization problem is solved in a two-phase approach. The difficulty of the printability optimization due to its multimodal nature is handled with a sensitivity-based heuristic. A coupling aware timing driven continuous wire sizing algorithm is also provided. Lithographic simulation results show that our approach can improve the printability in term of edge placement error (EPE) by 20%-40% without violating timing, wire width, and spacing constraints.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "As the VLSI feature size has already decreased below lithographic wavelength, the printability problem, due to strong diffraction effects, poses a serious threat to the progress of VLSI technology. A circuit layout with poor printability implies that it is difficult to make the printed features on wafers follow designed shapes without distortions. The development of resolution enhancement techniques (RET) can alleviate the printability problem but cannot reverse the trend of deterioration. Moreover, over-usage of RET may dramatically increase photo-mask cost and increase the cycle time for volume production. Thus, there is a strong demand to consider the subwavelength printability problem in circuit layout designs. However, layout printability optimization should not degrade circuit timing performance. In this paper, we introduce a wire sizing and spacing method to improve wire printability with minimal adverse impact on interconnect timing performance. A new printability model is proposed to handle partially coherent illuminations. The complex printability and timing optimization problem is solved in a two-phase approach. The difficulty of the printability optimization due to its multimodal nature is handled with a sensitivity-based heuristic. A coupling aware timing driven continuous wire sizing algorithm is also provided. Lithographic simulation results show that our approach can improve the printability in term of edge placement error (EPE) by 20%-40% without violating timing, wire width, and spacing constraints.",
"title": "Wire sizing and spacing for lithographic printability and timing optimization",
"normalizedTitle": "Wire sizing and spacing for lithographic printability and timing optimization",
"fno": "04380267",
"hasPdf": true,
"idPrefix": "si",
"keywords": [
"Circuit Optimisation",
"Design For Manufacture",
"Integrated Circuit Design",
"Integrated Circuit Interconnections",
"Integrated Circuit Layout",
"Integrated Circuit Manufacture",
"Integrated Circuit Modelling",
"Proximity Effect Lithography",
"VLSI",
"Wire Sizing Method",
"Wire Spacing Method",
"Lithographic Printability",
"Interconnect Timing Optimization",
"VLSI Feature Size",
"Resolution Enhancement Techniques",
"Subwavelength Printability Problem",
"Circuit Layout Designs",
"Layout Printability Optimization",
"Circuit Timing Performance",
"Wire Printability",
"Printability Model",
"Two Phase Approach",
"Sensitivity Based Heuristic Mechanism",
"Edge Placement Error",
"Design For Manufacturing",
"Optical Proximity Correction",
"Coupling Aware Time",
"Continuous Wire Sizing Algorithm",
"Wire",
"Timing",
"Very Large Scale Integration",
"Diffraction",
"Shape",
"Costs",
"Production",
"Degradation",
"Integrated Circuit Interconnections",
"Lighting",
"Design For Manufacturing DFM",
"Optical Proximity Correction OPC",
"Physical Design",
"Timing Optimization",
"VLSI"
],
"authors": [
{
"givenName": "Ke",
"surname": "Cao",
"fullName": "Ke Cao",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jiang",
"surname": "Hu",
"fullName": "Jiang Hu",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mosong",
"surname": "Cheng",
"fullName": "Mosong Cheng",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "12",
"pubDate": "2007-12-01 00:00:00",
"pubType": "trans",
"pages": "1332-1340",
"year": "2007",
"issn": "1063-8210",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iccad/1997/8200/0/82000628",
"title": "Global interconnect sizing and spacing with consideration of coupling capacitance",
"doi": null,
"abstractUrl": "/proceedings-article/iccad/1997/82000628/12OmNAZOJXf",
"parentPublication": {
"id": "proceedings/iccad/1997/8200/0",
"title": "Computer-Aided Design, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccad/1996/7597/0/75970044",
"title": "Buffered Steiner Tree Construction with Wire Sizing for Interconnect Layout Optimization",
"doi": null,
"abstractUrl": "/proceedings-article/iccad/1996/75970044/12OmNAoDilr",
"parentPublication": {
"id": "proceedings/iccad/1996/7597/0",
"title": "Computer-Aided Design, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccad/2006/3891/0/04110219",
"title": "Wire Density Driven Global Routing for CMP Variation and Timing",
"doi": null,
"abstractUrl": "/proceedings-article/iccad/2006/04110219/12OmNBqv2ow",
"parentPublication": {
"id": "proceedings/iccad/2006/3891/0",
"title": "Computer-Aided Design, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccad/2003/762/0/01257869",
"title": "Power-optimal simultaneous buffer insertion/sizing and wire sizing",
"doi": null,
"abstractUrl": "/proceedings-article/iccad/2003/01257869/12OmNqGitZb",
"parentPublication": {
"id": "proceedings/iccad/2003/762/0",
"title": "ICCAD-2003. International Conference on Computer Aided Design",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/date/2003/1870/1/01253586",
"title": "Global wire bus configuration with minimum delay uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/date/2003/01253586/12OmNrkjVea",
"parentPublication": {
"id": "proceedings/date/2003/1870/1",
"title": "Design, Automation & Test in Europe Conference & Exhibition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/date/2003/1870/0/01253586",
"title": "Global wire bus configuration with minimum delay uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/date/2003/01253586/12OmNro0Idp",
"parentPublication": {
"id": "proceedings/date/2003/1870/0",
"title": "Design, Automation & Test in Europe Conference & Exhibition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aspdac/1998/4425/0/00669503",
"title": "Simultaneous wire sizing and wire spacing in post-layout performance optimization",
"doi": null,
"abstractUrl": "/proceedings-article/aspdac/1998/00669503/12OmNxcMSer",
"parentPublication": {
"id": "proceedings/aspdac/1998/4425/0",
"title": "Proceedings of 1998 Asia and South Pacific Design Automation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/date/2003/1870/2/01253586",
"title": "Global wire bus configuration with minimum delay uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/date/2003/01253586/12OmNxdm4wp",
"parentPublication": {
"id": "proceedings/date/2003/1870/2",
"title": "Design, Automation & Test in Europe Conference & Exhibition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccad/2002/7607/0/01167547",
"title": "Repeater insertion and wire sizing optimization for throughput-centric VLSI global interconnects",
"doi": null,
"abstractUrl": "/proceedings-article/iccad/2002/01167547/12OmNy5R3GC",
"parentPublication": {
"id": "proceedings/iccad/2002/7607/0",
"title": "2002 IEEE/ACM International Conference on Computer Aided Design (ICCAD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2004/10/01336846",
"title": "Individual wire-length prediction with application to timing-driven placement",
"doi": null,
"abstractUrl": "/journal/si/2004/10/01336846/13rRUxCRFTL",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "04374120",
"articleId": "13rRUy0HYOQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "04378269",
"articleId": "13rRUyuvRuE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwIHoDX",
"title": "Feb.",
"year": "2016",
"issueNum": "02",
"idPrefix": "tg",
"pubType": "journal",
"volume": "22",
"label": "Feb.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxASupC",
"doi": "10.1109/TVCG.2015.2430322",
"abstract": "Scissor structure is used to generate deployable objects for space-saving in a variety of applications, from architecture to aerospace science. While deployment from a small, regular shape to a larger one is easy to design, we focus on a more challenging task: designing a planar scissor structure that deploys from a given source shape into a specific target shape. We propose a two-step constructive method to generate a scissor structure from a high-dimensional parameter space. Topology construction of the scissor structure is first performed to approximate the two given shapes, as well as to guarantee the deployment. Then the geometry of the scissor structure is optimized in order to minimize the connection deflections and maximize the shape approximation. With the optimized parameters, the deployment can be simulated by controlling an anchor scissor unit. Physical deployable objects are fabricated according to the designed scissor structures by using 3D printing or manual assembly. We show a number of results for different shapes to demonstrate that even with fabrication errors, our designed structures can deform fluently between the source and target shapes.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Scissor structure is used to generate deployable objects for space-saving in a variety of applications, from architecture to aerospace science. While deployment from a small, regular shape to a larger one is easy to design, we focus on a more challenging task: designing a planar scissor structure that deploys from a given source shape into a specific target shape. We propose a two-step constructive method to generate a scissor structure from a high-dimensional parameter space. Topology construction of the scissor structure is first performed to approximate the two given shapes, as well as to guarantee the deployment. Then the geometry of the scissor structure is optimized in order to minimize the connection deflections and maximize the shape approximation. With the optimized parameters, the deployment can be simulated by controlling an anchor scissor unit. Physical deployable objects are fabricated according to the designed scissor structures by using 3D printing or manual assembly. We show a number of results for different shapes to demonstrate that even with fabrication errors, our designed structures can deform fluently between the source and target shapes.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Scissor structure is used to generate deployable objects for space-saving in a variety of applications, from architecture to aerospace science. While deployment from a small, regular shape to a larger one is easy to design, we focus on a more challenging task: designing a planar scissor structure that deploys from a given source shape into a specific target shape. We propose a two-step constructive method to generate a scissor structure from a high-dimensional parameter space. Topology construction of the scissor structure is first performed to approximate the two given shapes, as well as to guarantee the deployment. Then the geometry of the scissor structure is optimized in order to minimize the connection deflections and maximize the shape approximation. With the optimized parameters, the deployment can be simulated by controlling an anchor scissor unit. Physical deployable objects are fabricated according to the designed scissor structures by using 3D printing or manual assembly. We show a number of results for different shapes to demonstrate that even with fabrication errors, our designed structures can deform fluently between the source and target shapes.",
"title": "Designing Planar Deployable Objects via Scissor Structures",
"normalizedTitle": "Designing Planar Deployable Objects via Scissor Structures",
"fno": "07102745",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Shape",
"Topology",
"Geometry",
"Joints",
"Three Dimensional Displays",
"Fabrication",
"Approximation Methods",
"Digital Fabrication",
"Computer Graphics",
"Digital Fabrication",
"Computer Graphics"
],
"authors": [
{
"givenName": "Ran",
"surname": "Zhang",
"fullName": "Ran Zhang",
"affiliation": "CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, Anhui, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shiwei",
"surname": "Wang",
"fullName": "Shiwei Wang",
"affiliation": "School of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xuejin",
"surname": "Chen",
"fullName": "Xuejin Chen",
"affiliation": "CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, Anhui, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chao",
"surname": "Ding",
"fullName": "Chao Ding",
"affiliation": "School of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Luo",
"surname": "Jiang",
"fullName": "Luo Jiang",
"affiliation": "School of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jie",
"surname": "Zhou",
"fullName": "Jie Zhou",
"affiliation": "CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System, University of Science and Technology of China, Hefei, Anhui, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ligang",
"surname": "Liu",
"fullName": "Ligang Liu",
"affiliation": "School of Mathematical Sciences, University of Science and Technology of China, Hefei, Anhui, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2016-02-01 00:00:00",
"pubType": "trans",
"pages": "1051-1062",
"year": "2016",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icmtma/2010/3962/3/3962e427",
"title": "Spatial Geometry Modeling of Truss Structure and Analysis of Connection Deviation for Deployable Truss Antenna",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2010/3962e427/12OmNwfsI0m",
"parentPublication": {
"id": "proceedings/icmtma/2010/3962/3",
"title": "2010 International Conference on Measuring Technology and Mechatronics Automation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2015/01/06846311",
"title": "Planar Hexagonal Meshing for Architecture",
"doi": null,
"abstractUrl": "/journal/tg/2015/01/06846311/13rRUEgs2BY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2014/07/06654158",
"title": "Shape Analysis of Planar Multiply-Connected Objects Using Conformal Welding",
"doi": null,
"abstractUrl": "/journal/tp/2014/07/06654158/13rRUxBa5d8",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09721643",
"title": "Geometry-Aware Planar Embedding of Treelike Structures",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09721643/1BhzmWFFD9K",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600u0813",
"title": "Topology-Preserving Shape Reconstruction and Registration via Neural Diffeomorphic Flow",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600u0813/1H1hR5pweWc",
"parentPublication": {
"id": "proceedings/cvpr/2022/6946/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2017/2636/0/263600a067",
"title": "Scissor-Based 3D Deployable Contours",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2017/263600a067/1ap5CQXwZws",
"parentPublication": {
"id": "proceedings/icvrv/2017/2636/0",
"title": "2017 International Conference on Virtual Reality and Visualization (ICVRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300h153",
"title": "Learning Shape Templates With Structured Implicit Functions",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300h153/1hVlFj4REmk",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/09022090",
"title": "Learning to Reconstruct Symmetric Shapes using Planar Parameterization of 3D Surface",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/09022090/1i5mERbIGQg",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiea/2020/8288/0/828800a547",
"title": "Simulation of Re-Entrant Structures Fabricated by Electrochemical Deposition",
"doi": null,
"abstractUrl": "/proceedings-article/aiea/2020/828800a547/1nTum4s64Te",
"parentPublication": {
"id": "proceedings/aiea/2020/8288/0",
"title": "2020 International Conference on Artificial Intelligence and Electromechanical Automation (AIEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/10/09462521",
"title": "View-Aware Geometry-Structure Joint Learning for Single-View 3D Shape Reconstruction",
"doi": null,
"abstractUrl": "/journal/tp/2022/10/09462521/1uDSvbmzJQc",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07117451",
"articleId": "13rRUy2YLT3",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07116602",
"articleId": "13rRUxOdD2G",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNCm7Bxr",
"title": "May",
"year": "2009",
"issueNum": "05",
"idPrefix": "tp",
"pubType": "journal",
"volume": "31",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwghda9",
"doi": "10.1109/TPAMI.2008.120",
"abstract": "The instabilities of the medial axis of a shape under deformations have long been recognized as a major obstacle to its use in recognition and other applications. These instabilities, or transitions, occur when the structure of the medial axis graph changes abruptly under deformations of shape. The recent classification of these transitions in 2D for the medial axis and for the shock graph was a key factor in the development of an object recognition system where the classified instabilities were utilized to represent deformation paths. The classification of generic transitions of the 3D medial axis could likewise potentially lead to a similar representation in 3D. In this paper, these transitions are classified by examining the order of contact of spheres with the surface, leading to an enumeration of possible transitions which are then examined on a case-by-case basis. Some cases are ruled out as never occurring in any family of deformations, while others are shown to be nongeneric in a one-parameter family of deformations. Finally, the remaining cases are shown to be viable by developing a specific example for each. Our work is inspired by that of Bogaevsky, who obtained the transitions as part of an investigation of viscosity solutions of Hamilton-Jacobi equations. Our contribution is to give a more down-to-earth approach, bringing this work to the attention of the computer vision community, and to provide explicit constructions for the various transitions using simple surfaces. We believe that the classification of these transitions is vital to the successful regularization of the medial axis in its use in real applications.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The instabilities of the medial axis of a shape under deformations have long been recognized as a major obstacle to its use in recognition and other applications. These instabilities, or transitions, occur when the structure of the medial axis graph changes abruptly under deformations of shape. The recent classification of these transitions in 2D for the medial axis and for the shock graph was a key factor in the development of an object recognition system where the classified instabilities were utilized to represent deformation paths. The classification of generic transitions of the 3D medial axis could likewise potentially lead to a similar representation in 3D. In this paper, these transitions are classified by examining the order of contact of spheres with the surface, leading to an enumeration of possible transitions which are then examined on a case-by-case basis. Some cases are ruled out as never occurring in any family of deformations, while others are shown to be nongeneric in a one-parameter family of deformations. Finally, the remaining cases are shown to be viable by developing a specific example for each. Our work is inspired by that of Bogaevsky, who obtained the transitions as part of an investigation of viscosity solutions of Hamilton-Jacobi equations. Our contribution is to give a more down-to-earth approach, bringing this work to the attention of the computer vision community, and to provide explicit constructions for the various transitions using simple surfaces. We believe that the classification of these transitions is vital to the successful regularization of the medial axis in its use in real applications.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The instabilities of the medial axis of a shape under deformations have long been recognized as a major obstacle to its use in recognition and other applications. These instabilities, or transitions, occur when the structure of the medial axis graph changes abruptly under deformations of shape. The recent classification of these transitions in 2D for the medial axis and for the shock graph was a key factor in the development of an object recognition system where the classified instabilities were utilized to represent deformation paths. The classification of generic transitions of the 3D medial axis could likewise potentially lead to a similar representation in 3D. In this paper, these transitions are classified by examining the order of contact of spheres with the surface, leading to an enumeration of possible transitions which are then examined on a case-by-case basis. Some cases are ruled out as never occurring in any family of deformations, while others are shown to be nongeneric in a one-parameter family of deformations. Finally, the remaining cases are shown to be viable by developing a specific example for each. Our work is inspired by that of Bogaevsky, who obtained the transitions as part of an investigation of viscosity solutions of Hamilton-Jacobi equations. Our contribution is to give a more down-to-earth approach, bringing this work to the attention of the computer vision community, and to provide explicit constructions for the various transitions using simple surfaces. We believe that the classification of these transitions is vital to the successful regularization of the medial axis in its use in real applications.",
"title": "Transitions of the 3D Medial Axis under a One-Parameter Family of Deformations",
"normalizedTitle": "Transitions of the 3D Medial Axis under a One-Parameter Family of Deformations",
"fno": "ttp2009050900",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Medial Axis",
"Shape",
"Singularity",
"Skeleton",
"Transition"
],
"authors": [
{
"givenName": "Peter J.",
"surname": "Giblin",
"fullName": "Peter J. Giblin",
"affiliation": "University of Liverpool, Liverpool",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Benjamin B.",
"surname": "Kimia",
"fullName": "Benjamin B. Kimia",
"affiliation": "Brown University, Providence",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Anthony J.",
"surname": "Pollitt",
"fullName": "Anthony J. Pollitt",
"affiliation": "University of Liverpool, Liverpool",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2009-05-01 00:00:00",
"pubType": "trans",
"pages": "900-918",
"year": "2009",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/sibgrapi/2008/3358/0/3358a212",
"title": "New Higher-Resolution Discrete Euclidean Medial Axis in nD with Linear Time Parallel Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2008/3358a212/12OmNApu5fr",
"parentPublication": {
"id": "proceedings/sibgrapi/2008/3358/0",
"title": "2008 XXI Brazilian Symposium on Computer Graphics and Image Processing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2009/3813/0/3813a096",
"title": "Fast Medial Axis Transform for Planar Domains With General Boundaries",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2009/3813a096/12OmNBU1jPl",
"parentPublication": {
"id": "proceedings/sibgrapi/2009/3813/0",
"title": "2009 XXII Brazilian Symposium on Computer Graphics and Image Processing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icig/2011/4541/0/4541a182",
"title": "A Medial Axis Extraction Algorithm for the Processing of Combustion Flame Images",
"doi": null,
"abstractUrl": "/proceedings-article/icig/2011/4541a182/12OmNrYlmTY",
"parentPublication": {
"id": "proceedings/icig/2011/4541/0",
"title": "Image and Graphics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icip/1995/7310/2/73102105",
"title": "Parallel complexity of the medial axis computation",
"doi": null,
"abstractUrl": "/proceedings-article/icip/1995/73102105/12OmNs5rkMi",
"parentPublication": {
"id": "proceedings/icip/1995/7310/2",
"title": "Image Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2000/0750/1/07501712",
"title": "Object Representation and Comparison Inferred from Its Medial Axis",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2000/07501712/12OmNvDI45q",
"parentPublication": {
"id": "proceedings/icpr/2000/0750/1",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2004/2128/3/212830123",
"title": "Towards Surface Regularization via Medial Axis Transitions",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2004/212830123/12OmNvSbBDk",
"parentPublication": {
"id": "proceedings/icpr/2004/2128/3",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aici/2009/3816/2/3816b544",
"title": "Medial Axis Extraction Using Growing Neural Gas",
"doi": null,
"abstractUrl": "/proceedings-article/aici/2009/3816b544/12OmNyS6REf",
"parentPublication": {
"id": "proceedings/aici/2009/3816/2",
"title": "2009 International Conference on Artificial Intelligence and Computational Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2009/3781/0/3781a171",
"title": "Medial Axis Approximation with Bounded Error",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2009/3781a171/12OmNyUWR1g",
"parentPublication": {
"id": "proceedings/isvd/2009/3781/0",
"title": "2009 Sixth International Symposium on Voronoi Diagrams",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2009/3781/0/3781a089",
"title": "On the Isomorphism between the Medial Axis and a Dual of the Delaunay Graph",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2009/3781a089/12OmNyYDDKn",
"parentPublication": {
"id": "proceedings/isvd/2009/3781/0",
"title": "2009 Sixth International Symposium on Voronoi Diagrams",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2004/02/i0238",
"title": "A Formal Classification of 3D Medial Axis Points and Their Local Geometry",
"doi": null,
"abstractUrl": "/journal/tp/2004/02/i0238/13rRUxAAT28",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttp2009050884",
"articleId": "13rRUyoPSQe",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttp2009050919",
"articleId": "13rRUzphDyZ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNALlciu",
"title": "April",
"year": "1986",
"issueNum": "04",
"idPrefix": "tp",
"pubType": "journal",
"volume": "8",
"label": "April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwj7cpY",
"doi": "10.1109/TPAMI.1986.4767815",
"abstract": "A shape smoothing algorithm is presented which uses properties of the medial axis to define segments of the shape border and their prominence relative to the local radius of the shape. Prominence values are used to classify axes as either major or minor, and minor axes are then deleted. An augmented medial axis transform is also defined using an approximate Euclidean distance transform, and medial axis interpolation and linking.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A shape smoothing algorithm is presented which uses properties of the medial axis to define segments of the shape border and their prominence relative to the local radius of the shape. Prominence values are used to classify axes as either major or minor, and minor axes are then deleted. An augmented medial axis transform is also defined using an approximate Euclidean distance transform, and medial axis interpolation and linking.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A shape smoothing algorithm is presented which uses properties of the medial axis to define segments of the shape border and their prominence relative to the local radius of the shape. Prominence values are used to classify axes as either major or minor, and minor axes are then deleted. An augmented medial axis transform is also defined using an approximate Euclidean distance transform, and medial axis interpolation and linking.",
"title": "Shape Smoothing Using Medial Axis Properties",
"normalizedTitle": "Shape Smoothing Using Medial Axis Properties",
"fno": "04767815",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [],
"authors": [
{
"givenName": "Seng-Beng",
"surname": "Ho",
"fullName": "Seng-Beng Ho",
"affiliation": "Department of Computer Sciences, University of Wisconsin, Madison, WI 53706.",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Charles R.",
"surname": "Dyer",
"fullName": "Charles R. Dyer",
"affiliation": "Department of Computer Sciences, University of Wisconsin, Madison, WI 53706.",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "1986-07-01 00:00:00",
"pubType": "trans",
"pages": "512-520",
"year": "1986",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icdar/2013/4999/0/06628836",
"title": "Scene Character Reconstruction through Medial Axis",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2013/06628836/12OmNAYGlty",
"parentPublication": {
"id": "proceedings/icdar/2013/4999/0",
"title": "2013 12th International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2017/1032/0/1032c727",
"title": "AMAT: Medial Axis Transform for Natural Images",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/1032c727/12OmNBE7MmQ",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icig/2011/4541/0/4541a182",
"title": "A Medial Axis Extraction Algorithm for the Processing of Combustion Flame Images",
"doi": null,
"abstractUrl": "/proceedings-article/icig/2011/4541a182/12OmNrYlmTY",
"parentPublication": {
"id": "proceedings/icig/2011/4541/0",
"title": "Image and Graphics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2003/2030/0/20300063",
"title": "Shape Simplification Based on the Medial Axis Transform",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2003/20300063/12OmNvRU0rS",
"parentPublication": {
"id": "proceedings/ieee-vis/2003/2030/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2004/2128/3/212830123",
"title": "Towards Surface Regularization via Medial Axis Transitions",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2004/212830123/12OmNvSbBDk",
"parentPublication": {
"id": "proceedings/icpr/2004/2128/3",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/1998/8295/0/82950833",
"title": "Affine Invariant Medial Axis and Skew Symmetry",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/1998/82950833/12OmNy4IF2a",
"parentPublication": {
"id": "proceedings/iccv/1998/8295/0",
"title": "Computer Vision, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aici/2009/3816/2/3816b544",
"title": "Medial Axis Extraction Using Growing Neural Gas",
"doi": null,
"abstractUrl": "/proceedings-article/aici/2009/3816b544/12OmNyS6REf",
"parentPublication": {
"id": "proceedings/aici/2009/3816/2",
"title": "2009 International Conference on Artificial Intelligence and Computational Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvd/2009/3781/0/3781a171",
"title": "Medial Axis Approximation with Bounded Error",
"doi": null,
"abstractUrl": "/proceedings-article/isvd/2009/3781a171/12OmNyUWR1g",
"parentPublication": {
"id": "proceedings/isvd/2009/3781/0",
"title": "2009 Sixth International Symposium on Voronoi Diagrams",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/03/07138635",
"title": "Medial Meshes – A Compact and Accurate Representation of Medial Axis Transform",
"doi": null,
"abstractUrl": "/journal/tg/2016/03/07138635/13rRUB7a1fU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/1982/04/04767267",
"title": "Medial Axis Transformation of a Planar Shape",
"doi": null,
"abstractUrl": "/journal/tp/1982/04/04767267/13rRUEgs2MJ",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "04767814",
"articleId": "13rRUxjQywg",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "04767816",
"articleId": "13rRUxjyX4W",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNy5hRch",
"title": "Nov.",
"year": "2019",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "25",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1cPXBdjp9yo",
"doi": "10.1109/TVCG.2019.2932223",
"abstract": "Shader lamp systems augment the real environment by projecting new textures on known target geometries. In dynamic scenes, object tracking maintains the illusion if the physical and virtual objects are well aligned. However, traditional trackers based on texture or contour information are often distracted by the projected content and tend to fail. In this paper, we present a model-based tracking strategy, which directly takes advantage from the projected content for pose estimation in a projector-camera system. An iterative pose estimation algorithm captures and exploits visible distortions caused by object movements. In a closed-loop, the corrected pose allows the update of the projection for the subsequent frame. Synthetic frames simulating the projection on the model are rendered and an optical flow-based method minimizes the difference between edges of the rendered and the camera image. Since the thresholds automatically adapt to the synthetic image, a complicated radiometric calibration can be avoided. The pixel-wise linear optimization is designed to be easily implemented on the GPU. Our approach can be combined with a regular contour-based tracker and is transferable to other problems, like the estimation of the extrinsic pose between projector and camera. We evaluate our procedure with real and synthetic images and obtain very precise registration results.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Shader lamp systems augment the real environment by projecting new textures on known target geometries. In dynamic scenes, object tracking maintains the illusion if the physical and virtual objects are well aligned. However, traditional trackers based on texture or contour information are often distracted by the projected content and tend to fail. In this paper, we present a model-based tracking strategy, which directly takes advantage from the projected content for pose estimation in a projector-camera system. An iterative pose estimation algorithm captures and exploits visible distortions caused by object movements. In a closed-loop, the corrected pose allows the update of the projection for the subsequent frame. Synthetic frames simulating the projection on the model are rendered and an optical flow-based method minimizes the difference between edges of the rendered and the camera image. Since the thresholds automatically adapt to the synthetic image, a complicated radiometric calibration can be avoided. The pixel-wise linear optimization is designed to be easily implemented on the GPU. Our approach can be combined with a regular contour-based tracker and is transferable to other problems, like the estimation of the extrinsic pose between projector and camera. We evaluate our procedure with real and synthetic images and obtain very precise registration results.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Shader lamp systems augment the real environment by projecting new textures on known target geometries. In dynamic scenes, object tracking maintains the illusion if the physical and virtual objects are well aligned. However, traditional trackers based on texture or contour information are often distracted by the projected content and tend to fail. In this paper, we present a model-based tracking strategy, which directly takes advantage from the projected content for pose estimation in a projector-camera system. An iterative pose estimation algorithm captures and exploits visible distortions caused by object movements. In a closed-loop, the corrected pose allows the update of the projection for the subsequent frame. Synthetic frames simulating the projection on the model are rendered and an optical flow-based method minimizes the difference between edges of the rendered and the camera image. Since the thresholds automatically adapt to the synthetic image, a complicated radiometric calibration can be avoided. The pixel-wise linear optimization is designed to be easily implemented on the GPU. Our approach can be combined with a regular contour-based tracker and is transferable to other problems, like the estimation of the extrinsic pose between projector and camera. We evaluate our procedure with real and synthetic images and obtain very precise registration results.",
"title": "Projection Distortion-based Object Tracking in Shader Lamp Scenarios",
"normalizedTitle": "Projection Distortion-based Object Tracking in Shader Lamp Scenarios",
"fno": "08794641",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Cameras",
"Three Dimensional Displays",
"Pose Estimation",
"Mathematical Model",
"Calibration",
"Object Tracking",
"Projector Camera Systems",
"Projector Camera Calibration",
"Shader Lamp Systems",
"Object Tracking",
"Object Registration",
"Spatial Augmented Reality",
"Projection Mapping"
],
"authors": [
{
"givenName": "Niklas",
"surname": "Gard",
"fullName": "Niklas Gard",
"affiliation": "Fraunhofer HHI",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Anna",
"surname": "Hilsmann",
"fullName": "Anna Hilsmann",
"affiliation": "Fraunhofer HHI",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peter",
"surname": "Eisert",
"fullName": "Peter Eisert",
"affiliation": "Fraunhofer HHI",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2019-11-01 00:00:00",
"pubType": "trans",
"pages": "3105-3113",
"year": "2019",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icpr/2008/2174/0/04761601",
"title": "Calibration of projector-camera systems from virtual mutual projection",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761601/12OmNBp52Hx",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2014/6184/0/06948421",
"title": "Sticky projections — A new approach to interactive shader lamp tracking",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2014/06948421/12OmNwkzupV",
"parentPublication": {
"id": "proceedings/ismar/2014/6184/0",
"title": "2014 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2010/7029/0/05544604",
"title": "One-shot scanning method using an unealibrated projector and camera system",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2010/05544604/12OmNybfr0f",
"parentPublication": {
"id": "proceedings/cvprw/2010/7029/0",
"title": "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2014/4308/0/4308a449",
"title": "Projection Center Calibration for a Co-located Projector Camera System",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2014/4308a449/12OmNypIYA4",
"parentPublication": {
"id": "proceedings/cvprw/2014/4308/0",
"title": "2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2010/7029/0/05543474",
"title": "Camera-projector matching using an unstructured video stream",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2010/05543474/12OmNzUxO57",
"parentPublication": {
"id": "proceedings/cvprw/2010/7029/0",
"title": "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/03/07138633",
"title": "Sticky Projections-A Model-Based Approach to Interactive Shader Lamps Tracking",
"doi": null,
"abstractUrl": "/journal/tg/2016/03/07138633/13rRUxly8XI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/11/08466021",
"title": "Auto-Calibration for Dynamic Multi-Projection Mapping on Arbitrary Surfaces",
"doi": null,
"abstractUrl": "/journal/tg/2018/11/08466021/14M3DYlzziw",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2018/7592/0/08699178",
"title": "A Single-Shot-Per-Pose Camera-Projector Calibration System for Imperfect Planar Targets",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2018/08699178/19F1O0IjR8k",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2018/7592/0",
"title": "2018 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/11/08821571",
"title": "Animated Stickies: Fast Video Projection Mapping onto a Markerless Plane through a Direct Closed-Loop Alignment",
"doi": null,
"abstractUrl": "/journal/tg/2019/11/08821571/1d6xCnoQsU0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2019/4765/0/476500a261",
"title": "A Projector Calibration Method Using a Mobile Camera for Projection Mapping System",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2019/476500a261/1gysikN6QOQ",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2019/4765/0",
"title": "2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08821571",
"articleId": "1d6xCnoQsU0",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08794584",
"articleId": "1dNHlOrNW5W",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1i4psw1SNTa",
"name": "ttg201911-08794641s1.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg201911-08794641s1.mp4",
"extension": "mp4",
"size": "52.7 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNB9bvmd",
"title": "May",
"year": "2002",
"issueNum": "05",
"idPrefix": "td",
"pubType": "journal",
"volume": "13",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxly95c",
"doi": "10.1109/TPDS.2002.1003856",
"abstract": "In this paper, an efficient algorithm to implement loop partitioning is introduced and evaluated. We start from results of Agarwal et al. whose aim is to minimize the number of accessed data throughout the computation of a tile; this number is called the cumulative footprint of the tile. We improve these results along several directions. First, we derive a new formulation of the cumulative footprint, allowing for an analytical solution of the optimization problem stated in. Second, we deal with arbitrary parallelepiped-shaped tiles, as opposed to rectangular tiles in. We design an efficient heuristic to determine the optimal tile shape in this general setting and we show its usefulness using both examples from and a large collection of randomly generated data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, an efficient algorithm to implement loop partitioning is introduced and evaluated. We start from results of Agarwal et al. whose aim is to minimize the number of accessed data throughout the computation of a tile; this number is called the cumulative footprint of the tile. We improve these results along several directions. First, we derive a new formulation of the cumulative footprint, allowing for an analytical solution of the optimization problem stated in. Second, we deal with arbitrary parallelepiped-shaped tiles, as opposed to rectangular tiles in. We design an efficient heuristic to determine the optimal tile shape in this general setting and we show its usefulness using both examples from and a large collection of randomly generated data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, an efficient algorithm to implement loop partitioning is introduced and evaluated. We start from results of Agarwal et al. whose aim is to minimize the number of accessed data throughout the computation of a tile; this number is called the cumulative footprint of the tile. We improve these results along several directions. First, we derive a new formulation of the cumulative footprint, allowing for an analytical solution of the optimization problem stated in. Second, we deal with arbitrary parallelepiped-shaped tiles, as opposed to rectangular tiles in. We design an efficient heuristic to determine the optimal tile shape in this general setting and we show its usefulness using both examples from and a large collection of randomly generated data.",
"title": "Automatic Partitioning of Parallel Loops with Parallelepiped-Shaped Tiles",
"normalizedTitle": "Automatic Partitioning of Parallel Loops with Parallelepiped-Shaped Tiles",
"fno": "l0460",
"hasPdf": true,
"idPrefix": "td",
"keywords": [
"Partitioning Algorithms",
"Arithmetic",
"Optimization Methods",
"Costs",
"Microelectronics",
"Computer Science"
],
"authors": [
{
"givenName": "Fabrice",
"surname": "Rastello",
"fullName": "Fabrice Rastello",
"affiliation": "ST Microelectron., Grenoble, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yves",
"surname": "Robert",
"fullName": "Yves Robert",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": false,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2002-05-01 00:00:00",
"pubType": "trans",
"pages": "460-470",
"year": "2002",
"issn": "1045-9219",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "l0447",
"articleId": "13rRUwbs2fZ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "l0471",
"articleId": "13rRUxBrGgo",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNBRKwCF",
"title": "Aug.",
"year": "2013",
"issueNum": "08",
"idPrefix": "tk",
"pubType": "journal",
"volume": "25",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwbaqVh",
"doi": "10.1109/TKDE.2012.110",
"abstract": "Principal composite kernel feature analysis (PC-KFA) is presented to show kernel adaptations for nonlinear features of medical image data sets (MIDS) in computer-aided diagnosis (CAD). The proposed algorithm PC-KFA has extended the existing studies on kernel feature analysis (KFA), which extracts salient features from a sample of unclassified patterns by use of a kernel method. The principal composite process for PC-KFA herein has been applied to kernel principal component analysis [34] and to our previously developed accelerated kernel feature analysis [20]. Unlike other kernel-based feature selection algorithms, PC-KFA iteratively constructs a linear subspace of a high-dimensional feature space by maximizing a variance condition for the nonlinearly transformed samples, which we call data-dependent kernel approach. The resulting kernel subspace can be first chosen by principal component analysis, and then be processed for composite kernel subspace through the efficient combination representations used for further reconstruction and classification. Numerical experiments based on several MID feature spaces of cancer CAD data have shown that PC-KFA generates efficient and an effective feature representation, and has yielded a better classification performance for the proposed composite kernel subspace using a simple pattern classifier.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Principal composite kernel feature analysis (PC-KFA) is presented to show kernel adaptations for nonlinear features of medical image data sets (MIDS) in computer-aided diagnosis (CAD). The proposed algorithm PC-KFA has extended the existing studies on kernel feature analysis (KFA), which extracts salient features from a sample of unclassified patterns by use of a kernel method. The principal composite process for PC-KFA herein has been applied to kernel principal component analysis [34] and to our previously developed accelerated kernel feature analysis [20]. Unlike other kernel-based feature selection algorithms, PC-KFA iteratively constructs a linear subspace of a high-dimensional feature space by maximizing a variance condition for the nonlinearly transformed samples, which we call data-dependent kernel approach. The resulting kernel subspace can be first chosen by principal component analysis, and then be processed for composite kernel subspace through the efficient combination representations used for further reconstruction and classification. Numerical experiments based on several MID feature spaces of cancer CAD data have shown that PC-KFA generates efficient and an effective feature representation, and has yielded a better classification performance for the proposed composite kernel subspace using a simple pattern classifier.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Principal composite kernel feature analysis (PC-KFA) is presented to show kernel adaptations for nonlinear features of medical image data sets (MIDS) in computer-aided diagnosis (CAD). The proposed algorithm PC-KFA has extended the existing studies on kernel feature analysis (KFA), which extracts salient features from a sample of unclassified patterns by use of a kernel method. The principal composite process for PC-KFA herein has been applied to kernel principal component analysis [34] and to our previously developed accelerated kernel feature analysis [20]. Unlike other kernel-based feature selection algorithms, PC-KFA iteratively constructs a linear subspace of a high-dimensional feature space by maximizing a variance condition for the nonlinearly transformed samples, which we call data-dependent kernel approach. The resulting kernel subspace can be first chosen by principal component analysis, and then be processed for composite kernel subspace through the efficient combination representations used for further reconstruction and classification. Numerical experiments based on several MID feature spaces of cancer CAD data have shown that PC-KFA generates efficient and an effective feature representation, and has yielded a better classification performance for the proposed composite kernel subspace using a simple pattern classifier.",
"title": "Principal Composite Kernel Feature Analysis: Data-Dependent Kernel Approach",
"normalizedTitle": "Principal Composite Kernel Feature Analysis: Data-Dependent Kernel Approach",
"fno": "ttk2013081863",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Kernel",
"Vectors",
"Feature Extraction",
"Principal Component Analysis",
"Eigenvalues And Eigenfunctions",
"Algorithm Design And Analysis",
"Image Reconstruction",
"Manifold Structures",
"Principal Component Analysis",
"Data Dependent Kernel",
"Nonlinear Subspace"
],
"authors": [
{
"givenName": "Yuichi",
"surname": "Motai",
"fullName": "Yuichi Motai",
"affiliation": "Virginia Commonwealth University, Richmond",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hiroyuki",
"surname": "Yoshida",
"fullName": "Hiroyuki Yoshida",
"affiliation": "Massachusetts General Hospital and Harvard Medical School, Boston",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2013-08-01 00:00:00",
"pubType": "trans",
"pages": "1863-1875",
"year": "2013",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/aici/2009/3816/2/3816b334",
"title": "Fault Detection for Process Monitoring Using Improved Kernel Principal Component Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/aici/2009/3816b334/12OmNAq3hDL",
"parentPublication": {
"id": "proceedings/aici/2009/3816/2",
"title": "2009 International Conference on Artificial Intelligence and Computational Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761209",
"title": "Kernel oriented discriminant analysis for speaker-independent phoneme spaces",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761209/12OmNqBbHvL",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icime/2009/3595/0/3595a196",
"title": "A Novel Face Feature Extraction Method Based on Two-dimensional Principal Component Analysis and Kernel Discriminant Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/icime/2009/3595a196/12OmNvDZEQZ",
"parentPublication": {
"id": "proceedings/icime/2009/3595/0",
"title": "Information Management and Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icia/2006/0528/0/04097864",
"title": "Data-Dependent Kernel Discriminant Analysis for Feature Extraction and Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icia/2006/04097864/12OmNvqmUCn",
"parentPublication": {
"id": "proceedings/icia/2006/0528/0",
"title": "2006 International Conference on Information Acquisition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/crv/2013/4983/0/4983a083",
"title": "Efficient, General Point Cloud Registration with Kernel Feature Maps",
"doi": null,
"abstractUrl": "/proceedings-article/crv/2013/4983a083/12OmNxaNGn9",
"parentPublication": {
"id": "proceedings/crv/2013/4983/0",
"title": "2013 International Conference on Computer and Robot Vision",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icassp/2004/8484/1/01325988",
"title": "A study of various composite kernels for kernel eigenvoice speaker adaptation",
"doi": null,
"abstractUrl": "/proceedings-article/icassp/2004/01325988/12OmNyQYtfT",
"parentPublication": {
"id": "proceedings/icassp/2004/8484/1",
"title": "2004 IEEE International Conference on Acoustics, Speech, and Signal Processing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2012/09/ttp2012091814",
"title": "Online Kernel Principal Component Analysis: A Reduced-Order Model",
"doi": null,
"abstractUrl": "/journal/tp/2012/09/ttp2012091814/13rRUyogGBn",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09864243",
"title": "Multiple Kernel Subspace Learning for Clustering and Classification",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09864243/1G2VM8Op4pa",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/04/09941008",
"title": "Learning Feature-Sparse Principal Subspace",
"doi": null,
"abstractUrl": "/journal/tp/2023/04/09941008/1I6NQAMqj28",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2020/9360/0/09150635",
"title": "Unsupervised Ensemble-Kernel Principal Component Analysis for Hyperspectral Anomaly Detection",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2020/09150635/1lPHo66hsgo",
"parentPublication": {
"id": "proceedings/cvprw/2020/9360/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttk2013081849",
"articleId": "13rRUy0HYRU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttk2013081876",
"articleId": "13rRUxjQyvO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwHhp0w",
"title": "June",
"year": "2015",
"issueNum": "06",
"idPrefix": "tk",
"pubType": "journal",
"volume": "27",
"label": "June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxOdD8C",
"doi": "10.1109/TKDE.2014.2373376",
"abstract": "Domain transfer learning generalizes a learning model across training data and testing data with different distributions. A general principle to tackle this problem is reducing the distribution difference between training data and testing data such that the generalization error can be bounded. Current methods typically model the sample distributions in input feature space, which depends on nonlinear feature mapping to embody the distribution discrepancy. However, this nonlinear feature space may not be optimal for the kernel-based learning machines. To this end, we propose a transfer kernel learning (TKL) approach to learn a domain-invariant kernel by directly matching source and target distributions in the reproducing kernel Hilbert space (RKHS). Specifically, we design a family of spectral kernels by extrapolating target eigensystem on source samples with Mercer’s theorem. The spectral kernel minimizing the approximation error to the ground truth kernel is selected to construct domain-invariant kernel machines. Comprehensive experimental evidence on a large number of text categorization, image classification, and video event recognition datasets verifies the effectiveness and efficiency of the proposed TKL approach over several state-of-the-art methods.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Domain transfer learning generalizes a learning model across training data and testing data with different distributions. A general principle to tackle this problem is reducing the distribution difference between training data and testing data such that the generalization error can be bounded. Current methods typically model the sample distributions in input feature space, which depends on nonlinear feature mapping to embody the distribution discrepancy. However, this nonlinear feature space may not be optimal for the kernel-based learning machines. To this end, we propose a transfer kernel learning (TKL) approach to learn a domain-invariant kernel by directly matching source and target distributions in the reproducing kernel Hilbert space (RKHS). Specifically, we design a family of spectral kernels by extrapolating target eigensystem on source samples with Mercer’s theorem. The spectral kernel minimizing the approximation error to the ground truth kernel is selected to construct domain-invariant kernel machines. Comprehensive experimental evidence on a large number of text categorization, image classification, and video event recognition datasets verifies the effectiveness and efficiency of the proposed TKL approach over several state-of-the-art methods.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Domain transfer learning generalizes a learning model across training data and testing data with different distributions. A general principle to tackle this problem is reducing the distribution difference between training data and testing data such that the generalization error can be bounded. Current methods typically model the sample distributions in input feature space, which depends on nonlinear feature mapping to embody the distribution discrepancy. However, this nonlinear feature space may not be optimal for the kernel-based learning machines. To this end, we propose a transfer kernel learning (TKL) approach to learn a domain-invariant kernel by directly matching source and target distributions in the reproducing kernel Hilbert space (RKHS). Specifically, we design a family of spectral kernels by extrapolating target eigensystem on source samples with Mercer’s theorem. The spectral kernel minimizing the approximation error to the ground truth kernel is selected to construct domain-invariant kernel machines. Comprehensive experimental evidence on a large number of text categorization, image classification, and video event recognition datasets verifies the effectiveness and efficiency of the proposed TKL approach over several state-of-the-art methods.",
"title": "Domain Invariant Transfer Kernel Learning",
"normalizedTitle": "Domain Invariant Transfer Kernel Learning",
"fno": "06964812",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Kernel",
"Approximation Error",
"Eigenvalues And Eigenfunctions",
"Testing",
"Standards",
"Hilbert Space",
"Video Recognition",
"Transfer Learning",
"Kernel Learning",
"Nystrom Method",
"Text Mining",
"Image Classification",
"Video Recognition",
"Transfer Learning",
"Kernel Learning",
"Nystrom Method",
"Text Mining",
"Image Classification"
],
"authors": [
{
"givenName": "Mingsheng",
"surname": "Long",
"fullName": "Mingsheng Long",
"affiliation": "School of Software and the Department of Computer Science, Tsinghua University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jianmin",
"surname": "Wang",
"fullName": "Jianmin Wang",
"affiliation": "School of Software and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jiaguang",
"surname": "Sun",
"fullName": "Jiaguang Sun",
"affiliation": "School of Software and Tsinghua National Laboratory for Information Science and Technology, Tsinghua University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Philip S.",
"surname": "Yu",
"fullName": "Philip S. Yu",
"affiliation": "Department of Computer Science, University of Illinois at Chicago, IL",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2015-06-01 00:00:00",
"pubType": "trans",
"pages": "1519-1532",
"year": "2015",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/2017/0457/0/0457d956",
"title": "Learning an Invariant Hilbert Space for Domain Adaptation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2017/0457d956/12OmNC3FG6D",
"parentPublication": {
"id": "proceedings/cvpr/2017/0457/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2014/4677/0/4677a114",
"title": "Scale-Invariant Heat Kernel Mapping",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2014/4677a114/12OmNwLOYQN",
"parentPublication": {
"id": "proceedings/cw/2014/4677/0",
"title": "2014 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2013/2840/0/2840a769",
"title": "Unsupervised Domain Adaptation by Domain Invariant Projection",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2013/2840a769/12OmNwudQO2",
"parentPublication": {
"id": "proceedings/iccv/2013/2840/0",
"title": "2013 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2016/6167/0/07838120",
"title": "Robust Kernel Embedding of Conditional and Posterior Distributions with Applications",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2016/07838120/12OmNzV70IY",
"parentPublication": {
"id": "proceedings/icmla/2016/6167/0",
"title": "2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2016/8851/0/8851f222",
"title": "Kernel Approximation via Empirical Orthogonal Decomposition for Unsupervised Feature Learning",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2016/8851f222/12OmNzhnaal",
"parentPublication": {
"id": "proceedings/cvpr/2016/8851/0",
"title": "2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2012/03/ttp2012030465",
"title": "Domain Transfer Multiple Kernel Learning",
"doi": null,
"abstractUrl": "/journal/tp/2012/03/ttp2012030465/13rRUwInvtZ",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2019/11/08444719",
"title": "Semi-Supervised Domain Adaptation by Covariance Matching",
"doi": null,
"abstractUrl": "/journal/tp/2019/11/08444719/13rRUxcbnDT",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000d437",
"title": "Aligning Infinite-Dimensional Covariance Matrices in Reproducing Kernel Hilbert Spaces for Domain Adaptation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000d437/17D45WLdYRf",
"parentPublication": {
"id": "proceedings/cvpr/2018/6420/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2020/07/08658140",
"title": "Optimal Transport in Reproducing Kernel Hilbert Spaces: Theory and Applications",
"doi": null,
"abstractUrl": "/journal/tp/2020/07/08658140/187Z9J2hSms",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/5555/01/10061269",
"title": "Contrastive Multi-View Kernel Learning",
"doi": null,
"abstractUrl": "/journal/tp/5555/01/10061269/1LiKLk3JxyU",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06990621",
"articleId": "13rRUxBa5xH",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06964811",
"articleId": "13rRUwbaqVi",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzV70s0",
"title": "May",
"year": "2015",
"issueNum": "05",
"idPrefix": "tg",
"pubType": "journal",
"volume": "21",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwInvsU",
"doi": "10.1109/TVCG.2014.2360403",
"abstract": "Recovery from tracking failure is essential in any simultaneous localization and tracking system. In this context, we explore an efficient keyframe-based relocalization method based on frame encoding using randomized ferns. The method enables automatic discovery of keyframes through online harvesting in tracking mode, and fast retrieval of pose candidates in the case when tracking is lost. Frame encoding is achieved by applying simple binary feature tests which are stored in the nodes of an ensemble of randomized ferns. The concatenation of small block codes generated by each fern yields a global compact representation of camera frames. Based on those representations we define the frame dissimilarity as the block-wise hamming distance (BlockHD). Dissimilarities between an incoming query frame and a large set of keyframes can be efficiently evaluated by simply traversing the nodes of the ferns and counting image co-occurrences in corresponding code tables. In tracking mode, those dissimilarities decide whether a frame/pose pair is considered as a novel keyframe. For tracking recovery, poses of the most similar keyframes are retrieved and used for reinitialization of the tracking algorithm. The integration of our relocalization method into a hand-held KinectFusion system allows seamless continuation of mapping even when tracking is frequently lost.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recovery from tracking failure is essential in any simultaneous localization and tracking system. In this context, we explore an efficient keyframe-based relocalization method based on frame encoding using randomized ferns. The method enables automatic discovery of keyframes through online harvesting in tracking mode, and fast retrieval of pose candidates in the case when tracking is lost. Frame encoding is achieved by applying simple binary feature tests which are stored in the nodes of an ensemble of randomized ferns. The concatenation of small block codes generated by each fern yields a global compact representation of camera frames. Based on those representations we define the frame dissimilarity as the block-wise hamming distance (BlockHD). Dissimilarities between an incoming query frame and a large set of keyframes can be efficiently evaluated by simply traversing the nodes of the ferns and counting image co-occurrences in corresponding code tables. In tracking mode, those dissimilarities decide whether a frame/pose pair is considered as a novel keyframe. For tracking recovery, poses of the most similar keyframes are retrieved and used for reinitialization of the tracking algorithm. The integration of our relocalization method into a hand-held KinectFusion system allows seamless continuation of mapping even when tracking is frequently lost.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recovery from tracking failure is essential in any simultaneous localization and tracking system. In this context, we explore an efficient keyframe-based relocalization method based on frame encoding using randomized ferns. The method enables automatic discovery of keyframes through online harvesting in tracking mode, and fast retrieval of pose candidates in the case when tracking is lost. Frame encoding is achieved by applying simple binary feature tests which are stored in the nodes of an ensemble of randomized ferns. The concatenation of small block codes generated by each fern yields a global compact representation of camera frames. Based on those representations we define the frame dissimilarity as the block-wise hamming distance (BlockHD). Dissimilarities between an incoming query frame and a large set of keyframes can be efficiently evaluated by simply traversing the nodes of the ferns and counting image co-occurrences in corresponding code tables. In tracking mode, those dissimilarities decide whether a frame/pose pair is considered as a novel keyframe. For tracking recovery, poses of the most similar keyframes are retrieved and used for reinitialization of the tracking algorithm. The integration of our relocalization method into a hand-held KinectFusion system allows seamless continuation of mapping even when tracking is frequently lost.",
"title": "Real-Time RGB-D Camera Relocalization via Randomized Ferns for Keyframe Encoding",
"normalizedTitle": "Real-Time RGB-D Camera Relocalization via Randomized Ferns for Keyframe Encoding",
"fno": "06912003",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Cameras",
"Image Coding",
"Image Colour Analysis",
"Image Representation",
"Image Retrieval",
"Object Tracking",
"Pose Estimation",
"SLAM Robots",
"Real Time RGB D Camera Relocalization",
"Randomized Ferns",
"Keyframe Encoding",
"Simultaneous Localization And Tracking System",
"Keyframe Based Relocalization Method",
"Automatic Keyframe Discovery",
"Online Harvesting",
"Tracking Mode",
"Pose Retrieval",
"Binary Feature Tests",
"Block Code Concatenation",
"Global Compact Camera Frame Representation",
"Frame Dissimilarity",
"Block Wise Hamming Distance",
"Block HD",
"Incoming Query Frame",
"Node Traversal",
"Image Co Occurrences",
"Code Tables",
"Frame Pose Pair",
"Tracking Failure Recovery",
"Tracking Algorithm Reinitialization",
"Hand Held Kinect Fusion System",
"Cameras",
"Three Dimensional Displays",
"Image Reconstruction",
"Real Time Systems",
"Simultaneous Localization And Mapping",
"Pipelines",
"Encoding",
"Camera Relocalization",
"Tracking Recovery",
"Dense Tracking And Mapping",
"Marker Free Augmented Reality",
"Camera Relocalization",
"Tracking Recovery",
"Dense Tracking And Mapping",
"Marker Free Augmented Reality"
],
"authors": [
{
"givenName": "Ben",
"surname": "Glocker",
"fullName": "Ben Glocker",
"affiliation": "Biomedical Image Analysis Group, Department of Computing, Imperial College London, United Kingdom",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jamie",
"surname": "Shotton",
"fullName": "Jamie Shotton",
"affiliation": "Microsoft Research, Cambridge, United Kingdom",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Antonio",
"surname": "Criminisi",
"fullName": "Antonio Criminisi",
"affiliation": "Microsoft Research, Cambridge, United Kingdom",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shahram",
"surname": "Izadi",
"fullName": "Shahram Izadi",
"affiliation": "Microsoft Research, Cambridge, United Kingdom",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "05",
"pubDate": "2015-05-01 00:00:00",
"pubType": "trans",
"pages": "571-583",
"year": "2015",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vr/2016/0836/0/07504740",
"title": "Fast and accurate relocalization for keyframe-based SLAM using geometric model selection",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2016/07504740/12OmNBB0bYl",
"parentPublication": {
"id": "proceedings/vr/2016/0836/0",
"title": "2016 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2013/2869/0/06671777",
"title": "Real-time RGB-D camera relocalization",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2013/06671777/12OmNqEAT3B",
"parentPublication": {
"id": "proceedings/ismar/2013/2869/0",
"title": "2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2013/2869/0/06671783",
"title": "Handling pure camera rotation in keyframe-based SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2013/06671783/12OmNvmG7YF",
"parentPublication": {
"id": "proceedings/ismar/2013/2869/0",
"title": "2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/07/ttg2011070875",
"title": "Robust Relocalization and Its Evaluation for Online Environment Map Construction",
"doi": null,
"abstractUrl": "/journal/tg/2011/07/ttg2011070875/13rRUyYSWsP",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08545173",
"title": "Em-SLAM: a Fast and Robust Monocular SLAM Method for Embedded Systems",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08545173/17D45XdBRQs",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2018/8425/0/842500a643",
"title": "Accurate Sparse Feature Regression Forest Learning for Real-Time Camera Relocalization",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2018/842500a643/17D45Xi9rWl",
"parentPublication": {
"id": "proceedings/3dv/2018/8425/0",
"title": "2018 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2022/5325/0/532500a720",
"title": "OA-SLAM: Leveraging Objects for Camera Relocalization in Visual SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2022/532500a720/1JrRdfQyove",
"parentPublication": {
"id": "proceedings/ismar/2022/5325/0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2019/12/08466599",
"title": "Active Camera Relocalization from a Single Reference Image without Hand-Eye Calibration",
"doi": null,
"abstractUrl": "/journal/tp/2019/12/08466599/1eEQ8CVkk6c",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2019/4765/0/476500a342",
"title": "FragmentFusion: A Light-Weight SLAM Pipeline for Dense Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2019/476500a342/1gysoC2gXC0",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2019/4765/0",
"title": "2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/4.803E306",
"title": "Unsupervised Collaborative Learning of Keyframe Detection and Visual Odometry Towards Monocular Deep SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/4.803E306/1hQqtAaoUes",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06892950",
"articleId": "13rRUwInvyC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06987340",
"articleId": "13rRUyuegp8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNyxXloY",
"title": "September",
"year": "2011",
"issueNum": "09",
"idPrefix": "tp",
"pubType": "journal",
"volume": "33",
"label": "September",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxEhFtT",
"doi": "10.1109/TPAMI.2011.41",
"abstract": "Monocular SLAM has the potential to turn inexpensive cameras into powerful pose sensors for applications such as robotics and augmented reality. We present a relocalization module for such systems which solves some of the problems encountered by previous monocular SLAM systems—tracking failure, map merging, and loop closure detection. This module extends recent advances in keypoint recognition to determine the camera pose relative to the landmarks within a single frame time of 33 ms. We first show how this module can be used to improve the robustness of these systems. Blur, sudden motion, and occlusion can all cause tracking to fail, leading to a corrupted map. Using the relocalization module, the system can automatically detect and recover from tracking failure while preserving map integrity. Extensive tests show that the system can then reliably generate maps for long sequences even in the presence of frequent tracking failure. We then show that the relocalization module can be used to recognize overlap in maps, i.e., when the camera has returned to a previously mapped area. Having established an overlap, we determine the relative pose of the maps using trajectory alignment so that independent maps can be merged and loop closure events can be recognized. The system combining all of these abilities is able to map larger environments and for significantly longer periods than previous systems.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Monocular SLAM has the potential to turn inexpensive cameras into powerful pose sensors for applications such as robotics and augmented reality. We present a relocalization module for such systems which solves some of the problems encountered by previous monocular SLAM systems—tracking failure, map merging, and loop closure detection. This module extends recent advances in keypoint recognition to determine the camera pose relative to the landmarks within a single frame time of 33 ms. We first show how this module can be used to improve the robustness of these systems. Blur, sudden motion, and occlusion can all cause tracking to fail, leading to a corrupted map. Using the relocalization module, the system can automatically detect and recover from tracking failure while preserving map integrity. Extensive tests show that the system can then reliably generate maps for long sequences even in the presence of frequent tracking failure. We then show that the relocalization module can be used to recognize overlap in maps, i.e., when the camera has returned to a previously mapped area. Having established an overlap, we determine the relative pose of the maps using trajectory alignment so that independent maps can be merged and loop closure events can be recognized. The system combining all of these abilities is able to map larger environments and for significantly longer periods than previous systems.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Monocular SLAM has the potential to turn inexpensive cameras into powerful pose sensors for applications such as robotics and augmented reality. We present a relocalization module for such systems which solves some of the problems encountered by previous monocular SLAM systems—tracking failure, map merging, and loop closure detection. This module extends recent advances in keypoint recognition to determine the camera pose relative to the landmarks within a single frame time of 33 ms. We first show how this module can be used to improve the robustness of these systems. Blur, sudden motion, and occlusion can all cause tracking to fail, leading to a corrupted map. Using the relocalization module, the system can automatically detect and recover from tracking failure while preserving map integrity. Extensive tests show that the system can then reliably generate maps for long sequences even in the presence of frequent tracking failure. We then show that the relocalization module can be used to recognize overlap in maps, i.e., when the camera has returned to a previously mapped area. Having established an overlap, we determine the relative pose of the maps using trajectory alignment so that independent maps can be merged and loop closure events can be recognized. The system combining all of these abilities is able to map larger environments and for significantly longer periods than previous systems.",
"title": "Automatic Relocalization and Loop Closing for Real-Time Monocular SLAM",
"normalizedTitle": "Automatic Relocalization and Loop Closing for Real-Time Monocular SLAM",
"fno": "ttp2011091699",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Tracking",
"3 D Stereo Scene Analysis",
"Autonomous Vehicles"
],
"authors": [
{
"givenName": "Brian",
"surname": "Williams",
"fullName": "Brian Williams",
"affiliation": "Jet Propulsion Laboratory, Pasadena",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Georg",
"surname": "Klein",
"fullName": "Georg Klein",
"affiliation": "Microsoft Corporation, Seattle",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ian",
"surname": "Reid",
"fullName": "Ian Reid",
"affiliation": "University of Oxford, Oxford",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "09",
"pubDate": "2011-09-01 00:00:00",
"pubType": "trans",
"pages": "1699-1712",
"year": "2011",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vr/2016/0836/0/07504740",
"title": "Fast and accurate relocalization for keyframe-based SLAM using geometric model selection",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2016/07504740/12OmNBB0bYl",
"parentPublication": {
"id": "proceedings/vr/2016/0836/0",
"title": "2016 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2013/2869/0/06671783",
"title": "Handling pure camera rotation in keyframe-based SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2013/06671783/12OmNvmG7YF",
"parentPublication": {
"id": "proceedings/ismar/2013/2869/0",
"title": "2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2018/5114/0/511401a350",
"title": "Monocular SLAM Algorithm Based on Improved Depth Map Estimation and Keyframe Selection",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2018/511401a350/12OmNyeECAZ",
"parentPublication": {
"id": "proceedings/icmtma/2018/5114/0",
"title": "2018 10th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2009/3992/0/05206769",
"title": "Visual loop closing using multi-resolution SIFT grids in metric-topological SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2009/05206769/12OmNyuPKYu",
"parentPublication": {
"id": "proceedings/cvpr/2009/3992/0",
"title": "2009 IEEE Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2006/05/i0684",
"title": "Component Optimization for Image Understanding: A Bayesian Approach",
"doi": null,
"abstractUrl": "/journal/tp/2006/05/i0684/13rRUwInvtR",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2008/03/ttp2008030493",
"title": "Constraint Integration for Efficient Multiview Pose Estimation with Self-Occlusions",
"doi": null,
"abstractUrl": "/journal/tp/2008/03/ttp2008030493/13rRUwhHcKm",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2013/06/ttp2013061451",
"title": "Monocular SLAM with Conditionally Independent Split Mapping",
"doi": null,
"abstractUrl": "/journal/tp/2013/06/ttp2013061451/13rRUxC0SXo",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/07/ttg2011070875",
"title": "Robust Relocalization and Its Evaluation for Online Environment Map Construction",
"doi": null,
"abstractUrl": "/journal/tg/2011/07/ttg2011070875/13rRUyYSWsP",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/091500a307",
"title": "StickyLocalization: Robust End-To-End Relocalization on Point Clouds using Graph Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500a307/1B12X0uGshy",
"parentPublication": {
"id": "proceedings/wacv/2022/0915/0",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2022/5325/0/532500a720",
"title": "OA-SLAM: Leveraging Objects for Camera Relocalization in Visual SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2022/532500a720/1JrRdfQyove",
"parentPublication": {
"id": "proceedings/ismar/2022/5325/0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttp2011091697",
"articleId": "13rRUxZzAiG",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttp2011091713",
"articleId": "13rRUxlgxXB",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNyaoDzi",
"title": "April",
"year": "2012",
"issueNum": "04",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwbs2b1",
"doi": "10.1109/TVCG.2012.45",
"abstract": "Head-mounted displays (HMDs) allow users to observe virtual environments (VEs) from an egocentric perspective. However, several experiments have provided evidence that egocentric distances are perceived as compressed in VEs relative to the real world. Recent experiments suggest that the virtual view frustum set for rendering the VE has an essential impact on the user's estimation of distances. In this article we analyze if distance estimation can be improved by calibrating the view frustum for a given HMD and user. Unfortunately, in an immersive virtual reality (VR) environment, a full per user calibration is not trivial and manual per user adjustment often leads to mini- or magnification of the scene. Therefore, we propose a novel per user calibration approach with optical see-through displays commonly used in augmented reality (AR). This calibration takes advantage of a geometric scheme based on 2D point - 3D line correspondences, which can be used intuitively by inexperienced users and requires less than a minute to complete. The required user interaction is based on taking aim at a distant target marker with a close marker, which ensures non-planar measurements covering a large area of the interaction space while also reducing the number of required measurements to five. We found the tendency that a calibrated view frustum reduced the average distance underestimation of users in an immersive VR environment, but even the correctly calibrated view frustum could not entirely compensate for the distance underestimation effects.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Head-mounted displays (HMDs) allow users to observe virtual environments (VEs) from an egocentric perspective. However, several experiments have provided evidence that egocentric distances are perceived as compressed in VEs relative to the real world. Recent experiments suggest that the virtual view frustum set for rendering the VE has an essential impact on the user's estimation of distances. In this article we analyze if distance estimation can be improved by calibrating the view frustum for a given HMD and user. Unfortunately, in an immersive virtual reality (VR) environment, a full per user calibration is not trivial and manual per user adjustment often leads to mini- or magnification of the scene. Therefore, we propose a novel per user calibration approach with optical see-through displays commonly used in augmented reality (AR). This calibration takes advantage of a geometric scheme based on 2D point - 3D line correspondences, which can be used intuitively by inexperienced users and requires less than a minute to complete. The required user interaction is based on taking aim at a distant target marker with a close marker, which ensures non-planar measurements covering a large area of the interaction space while also reducing the number of required measurements to five. We found the tendency that a calibrated view frustum reduced the average distance underestimation of users in an immersive VR environment, but even the correctly calibrated view frustum could not entirely compensate for the distance underestimation effects.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Head-mounted displays (HMDs) allow users to observe virtual environments (VEs) from an egocentric perspective. However, several experiments have provided evidence that egocentric distances are perceived as compressed in VEs relative to the real world. Recent experiments suggest that the virtual view frustum set for rendering the VE has an essential impact on the user's estimation of distances. In this article we analyze if distance estimation can be improved by calibrating the view frustum for a given HMD and user. Unfortunately, in an immersive virtual reality (VR) environment, a full per user calibration is not trivial and manual per user adjustment often leads to mini- or magnification of the scene. Therefore, we propose a novel per user calibration approach with optical see-through displays commonly used in augmented reality (AR). This calibration takes advantage of a geometric scheme based on 2D point - 3D line correspondences, which can be used intuitively by inexperienced users and requires less than a minute to complete. The required user interaction is based on taking aim at a distant target marker with a close marker, which ensures non-planar measurements covering a large area of the interaction space while also reducing the number of required measurements to five. We found the tendency that a calibrated view frustum reduced the average distance underestimation of users in an immersive VR environment, but even the correctly calibrated view frustum could not entirely compensate for the distance underestimation effects.",
"title": "Geometric Calibration of Head-Mounted Displays and its Effects on Distance Estimation",
"normalizedTitle": "Geometric Calibration of Head-Mounted Displays and its Effects on Distance Estimation",
"fno": "ttg2012040589",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Rendering Computer Graphics",
"Augmented Reality",
"Calibration",
"Helmet Mounted Displays",
"Human Computer Interaction",
"Distance Estimation",
"Geometric Calibration",
"Head Mounted Display",
"HMD",
"Egocentric Perspective",
"Egocentric Distance",
"Virtual View Frustum Set",
"Rendering",
"Immersive Virtual Reality Environment",
"Full Per User Calibration",
"Manual Per User Adjustment",
"Optical See Through Display",
"Augmented Reality",
"Geometric Scheme",
"2 D Point 3 D Line Correspondences",
"User Interaction",
"Calibrated View Frustum",
"Average Distance Underestimation Reduction",
"Immersive VR Environment",
"Distance Underestimation Effects",
"Cameras",
"Calibration",
"Three Dimensional Displays",
"Estimation",
"Noise",
"Vectors",
"Target Tracking",
"Distance Perception",
"Optical See Through",
"HMD Calibration"
],
"authors": [
{
"givenName": "F.",
"surname": "Kellner",
"fullName": "F. Kellner",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "B.",
"surname": "Bolte",
"fullName": "B. Bolte",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "G.",
"surname": "Bruder",
"fullName": "G. Bruder",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "U.",
"surname": "Rautenberg",
"fullName": "U. Rautenberg",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "F.",
"surname": "Steinicke",
"fullName": "F. Steinicke",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "M.",
"surname": "Lappe",
"fullName": "M. Lappe",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "R.",
"surname": "Koch",
"fullName": "R. Koch",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2012-04-01 00:00:00",
"pubType": "trans",
"pages": "589-596",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iwar/1999/0359/0/03590085",
"title": "Marker Tracking and HMD Calibration for a Video-Based Augmented Reality Conferencing System",
"doi": null,
"abstractUrl": "/proceedings-article/iwar/1999/03590085/12OmNBcAGLe",
"parentPublication": {
"id": "proceedings/iwar/1999/0359/0",
"title": "Augmented Reality, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2003/2006/0/20060161",
"title": "Evaluation of Calibration Procedures for Optical See-Through Head-Mounted Displays",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2003/20060161/12OmNCeK2b7",
"parentPublication": {
"id": "proceedings/ismar/2003/2006/0",
"title": "The Second IEEE and ACM International Symposium on Mixed and Augmented Reality, 2003. Proceedings.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2015/1727/0/07223450",
"title": "Evaluating optical see-through head-mounted display calibration via frustum visualization",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2015/07223450/12OmNrAv3Ap",
"parentPublication": {
"id": "proceedings/vr/2015/1727/0",
"title": "2015 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2013/4932/0/4932a716",
"title": "Non-contact 3D Measuring Machine Hardware Design and Precision Calibration",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2013/4932a716/12OmNwFRpax",
"parentPublication": {
"id": "proceedings/icmtma/2013/4932/0",
"title": "2013 Fifth International Conference on Measuring Technology and Mechatronics Automation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrais/1993/1363/0/00380772",
"title": "Calibration of head-mounted displays for augmented reality applications",
"doi": null,
"abstractUrl": "/proceedings-article/vrais/1993/00380772/12OmNwwuDRm",
"parentPublication": {
"id": "proceedings/vrais/1993/1363/0",
"title": "Virtual Reality Annual International Symposium",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iwar/1999/0359/0/03590075",
"title": "A Method for Calibrating See-Through Head-Mounted Displays for AR",
"doi": null,
"abstractUrl": "/proceedings-article/iwar/1999/03590075/12OmNxTVU20",
"parentPublication": {
"id": "proceedings/iwar/1999/0359/0",
"title": "Augmented Reality, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2014/2871/0/06802063",
"title": "Automated calibration of display characteristics (ACDC) for head-mounted displays and arbitrary surfaces",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2014/06802063/12OmNxwENpf",
"parentPublication": {
"id": "proceedings/vr/2014/2871/0",
"title": "2014 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/09/08052554",
"title": "A Survey of Calibration Methods for Optical See-Through Head-Mounted Displays",
"doi": null,
"abstractUrl": "/journal/tg/2018/09/08052554/13rRUILtJqY",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2015/04/07012105",
"title": "Corneal-Imaging Calibration for Optical See-Through Head-Mounted Displays",
"doi": null,
"abstractUrl": "/journal/tg/2015/04/07012105/13rRUxE04tC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2019/4765/0/476500a259",
"title": "OSTNet: Calibration Method for Optical See-Through Head-Mounted Displays via Non-Parametric Distortion Map Generation",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2019/476500a259/1gysj1o4L16",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2019/4765/0",
"title": "2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttg2012040581",
"articleId": "13rRUxASuGh",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttg2012040597",
"articleId": "13rRUxASuve",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNANBZkr",
"title": "Jan.-Mar.",
"year": "2015",
"issueNum": "01",
"idPrefix": "mu",
"pubType": "magazine",
"volume": "22",
"label": "Jan.-Mar.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwdrdMQ",
"doi": "10.1109/MMUL.2015.4",
"abstract": "This article presents a user-centered design approach for creating an audio interface in the context of climate science. The author's team used contextual inquiry to gather information about scientists' workflows and focus groups to assess data about the scientists' specific use of language. The goal was to realize a domain-specific sonification platform and to identify climate metaphors to build a metaphoric sound identity for the sonification. In a separate set of experiments, participants were asked to pair sound stimuli with climate terms extracted from the initial interviews and to evaluate the sound samples aesthetically. They were also asked to choose sound textures (from a given set of sounds) that best express the specific climate parameter and to rate the relevance of the sound to the metaphor. The author's team assessed correlations between climate terminology and sound stimuli for the sonification tool to improve the sound design. Results show a tendency toward natural sounds by climate scientists.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This article presents a user-centered design approach for creating an audio interface in the context of climate science. The author's team used contextual inquiry to gather information about scientists' workflows and focus groups to assess data about the scientists' specific use of language. The goal was to realize a domain-specific sonification platform and to identify climate metaphors to build a metaphoric sound identity for the sonification. In a separate set of experiments, participants were asked to pair sound stimuli with climate terms extracted from the initial interviews and to evaluate the sound samples aesthetically. They were also asked to choose sound textures (from a given set of sounds) that best express the specific climate parameter and to rate the relevance of the sound to the metaphor. The author's team assessed correlations between climate terminology and sound stimuli for the sonification tool to improve the sound design. Results show a tendency toward natural sounds by climate scientists.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This article presents a user-centered design approach for creating an audio interface in the context of climate science. The author's team used contextual inquiry to gather information about scientists' workflows and focus groups to assess data about the scientists' specific use of language. The goal was to realize a domain-specific sonification platform and to identify climate metaphors to build a metaphoric sound identity for the sonification. In a separate set of experiments, participants were asked to pair sound stimuli with climate terms extracted from the initial interviews and to evaluate the sound samples aesthetically. They were also asked to choose sound textures (from a given set of sounds) that best express the specific climate parameter and to rate the relevance of the sound to the metaphor. The author's team assessed correlations between climate terminology and sound stimuli for the sonification tool to improve the sound design. Results show a tendency toward natural sounds by climate scientists.",
"title": "Designing an Interactive Audio Interface for Climate Science",
"normalizedTitle": "Designing an Interactive Audio Interface for Climate Science",
"fno": "mmu2015010041",
"hasPdf": true,
"idPrefix": "mu",
"keywords": [
"Atmospheric Acoustics",
"Atmospheric Techniques",
"Audio User Interfaces",
"Climatology",
"Interactive Audio Interface",
"Climate Science",
"User Centered Design Approach",
"Contextual Inquiry",
"Scientist Workflows",
"Domain Specific Sonification Platform",
"Metaphoric Sound Identity",
"Sonification Tool",
"Climate Terminology",
"Sound Design",
"Natural Sounds",
"Sound Textures",
"Climate Scientists",
"Sound Samples",
"Sound Stimuli",
"Meteorology",
"Data Visualization",
"Data Analysis",
"Data Models",
"Multimedia Communication",
"Analytical Models",
"Atmospheric Modeling",
"Auditory Systems",
"Sonification",
"User Centered Design",
"Human Computer Interaction",
"Multimedia",
"Auditory Displays",
"Human Factors",
"Human Computer Interaction",
"Sonification",
"User Centered Design"
],
"authors": [
{
"givenName": "Visda",
"surname": "Goudarzi",
"fullName": "Visda Goudarzi",
"affiliation": "University of Music and Performing Arts, Graz",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2015-01-01 00:00:00",
"pubType": "mags",
"pages": "41-47",
"year": "2015",
"issn": "1070-986X",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/csse/2008/3336/3/3336e014",
"title": "Study on Application of CAD Sonification",
"doi": null,
"abstractUrl": "/proceedings-article/csse/2008/3336e014/12OmNwK7obY",
"parentPublication": {
"id": "proceedings/csse/2008/3336/3",
"title": "Computer Science and Software Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2015/9926/0/07363973",
"title": "Climate model diagnostic analyzer",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2015/07363973/12OmNwcl7BL",
"parentPublication": {
"id": "proceedings/big-data/2015/9926/0",
"title": "2015 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2011/0868/0/06004058",
"title": "Information Visualization in Climate Research",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2011/06004058/12OmNyO8tVC",
"parentPublication": {
"id": "proceedings/iv/2011/0868/0",
"title": "2011 15th International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2015/01/mmu2015010048",
"title": "Sonification of Surface Tapping Changes Behavior, Surface Perception, and Emotion",
"doi": null,
"abstractUrl": "/magazine/mu/2015/01/mmu2015010048/13rRUwd9CIo",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2013/05/mcs2013050032",
"title": "Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning",
"doi": null,
"abstractUrl": "/magazine/cs/2013/05/mcs2013050032/13rRUy2YLOR",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2015/06/mcs2015060043",
"title": "Can Topic Modeling Shed Light on Climate Extremes?",
"doi": null,
"abstractUrl": "/magazine/cs/2015/06/mcs2015060043/13rRUyYBlcf",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2015/01/mmu2015010074",
"title": "Sonic Trampoline: How Audio Feedback Impacts the User's Experience of Jumping",
"doi": null,
"abstractUrl": "/magazine/mu/2015/01/mmu2015010074/13rRUytnsTK",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sive/2018/5713/0/08577080",
"title": "Quantum: An art-science case study on sonification and sound design in virtual reality",
"doi": null,
"abstractUrl": "/proceedings-article/sive/2018/08577080/17D45We0UEe",
"parentPublication": {
"id": "proceedings/sive/2018/5713/0",
"title": "2018 IEEE 4th VR Workshop on Sonic Interactions for Virtual Environments (SIVE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2021/01/09325132",
"title": "Visualization of Climate Science Simulation Data",
"doi": null,
"abstractUrl": "/magazine/cg/2021/01/09325132/1qnQT22F5zq",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2020/6251/0/09377842",
"title": "Predicting Emotions Perceived from Sounds",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2020/09377842/1s64uMZiqsg",
"parentPublication": {
"id": "proceedings/big-data/2020/6251/0",
"title": "2020 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "mmu2015010032",
"articleId": "13rRUxlgy8H",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "mmu2015010048",
"articleId": "13rRUwd9CIo",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNxwENDW",
"title": "March",
"year": "2014",
"issueNum": "01",
"idPrefix": "th",
"pubType": "journal",
"volume": "7",
"label": "March",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUy2YLT8",
"doi": "10.1109/TOH.2014.2304734",
"abstract": "There are two main challenges in simulating bi-manual dental operations with six-degrees-of-freedom (6-DoF) haptic rendering. One is to simulate large deformation and force response of a tongue under multi-region contacts with a dental mirror, and the other is to simulate the force response when a dental probe inserts into a narrow periodontal pocket, which leads to simultaneous contacts of different types between the probe and both rigid and deformable objects (i.e., a rigid tooth and its surrounding deformable gingiva), which we call hybrid contacts, as well as frequent contact switches. In this paper, we address both challenges. We first introduce a novel method for modeling deformation based on a sphere-tree representation of deformable objects. A configuration-based constrained optimization method is utilized for determining the six-dimensional configuration of the graphic tool and the contact force/torque. This approach conducts collision detection, deformation computation, and tool configuration optimization very efficiently, avoids inter-penetration, and maintains stability of haptic display without using virtual coupling. To simulate the force response due to fine manipulation of the probe inside a narrow periodontal pocket, we propose an efficient method to simulate the local deformation of the gingiva and stable haptic feedback under frequent contact switches. Simulations on typical dental operations were carried out to validate the efficiency and stability of our approach.",
"abstracts": [
{
"abstractType": "Regular",
"content": "There are two main challenges in simulating bi-manual dental operations with six-degrees-of-freedom (6-DoF) haptic rendering. One is to simulate large deformation and force response of a tongue under multi-region contacts with a dental mirror, and the other is to simulate the force response when a dental probe inserts into a narrow periodontal pocket, which leads to simultaneous contacts of different types between the probe and both rigid and deformable objects (i.e., a rigid tooth and its surrounding deformable gingiva), which we call hybrid contacts, as well as frequent contact switches. In this paper, we address both challenges. We first introduce a novel method for modeling deformation based on a sphere-tree representation of deformable objects. A configuration-based constrained optimization method is utilized for determining the six-dimensional configuration of the graphic tool and the contact force/torque. This approach conducts collision detection, deformation computation, and tool configuration optimization very efficiently, avoids inter-penetration, and maintains stability of haptic display without using virtual coupling. To simulate the force response due to fine manipulation of the probe inside a narrow periodontal pocket, we propose an efficient method to simulate the local deformation of the gingiva and stable haptic feedback under frequent contact switches. Simulations on typical dental operations were carried out to validate the efficiency and stability of our approach.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "There are two main challenges in simulating bi-manual dental operations with six-degrees-of-freedom (6-DoF) haptic rendering. One is to simulate large deformation and force response of a tongue under multi-region contacts with a dental mirror, and the other is to simulate the force response when a dental probe inserts into a narrow periodontal pocket, which leads to simultaneous contacts of different types between the probe and both rigid and deformable objects (i.e., a rigid tooth and its surrounding deformable gingiva), which we call hybrid contacts, as well as frequent contact switches. In this paper, we address both challenges. We first introduce a novel method for modeling deformation based on a sphere-tree representation of deformable objects. A configuration-based constrained optimization method is utilized for determining the six-dimensional configuration of the graphic tool and the contact force/torque. This approach conducts collision detection, deformation computation, and tool configuration optimization very efficiently, avoids inter-penetration, and maintains stability of haptic display without using virtual coupling. To simulate the force response due to fine manipulation of the probe inside a narrow periodontal pocket, we propose an efficient method to simulate the local deformation of the gingiva and stable haptic feedback under frequent contact switches. Simulations on typical dental operations were carried out to validate the efficiency and stability of our approach.",
"title": "Haptic Simulation of Organ Deformation and Hybrid Contacts in Dental Operations",
"normalizedTitle": "Haptic Simulation of Organ Deformation and Hybrid Contacts in Dental Operations",
"fno": "06737331",
"hasPdf": true,
"idPrefix": "th",
"keywords": [
"Haptic Interfaces",
"Computational Modeling",
"Deformable Models",
"Force",
"Graphics",
"Skeleton",
"Dentistry",
"Hybrid Contacts",
"6 Do F Haptic Rendering",
"Organ Deformation",
"Sphere Tree",
"Configuration Based Optimization"
],
"authors": [
{
"givenName": null,
"surname": "Dangxiao Wang",
"fullName": "Dangxiao Wang",
"affiliation": "State Key Lab. of Virtual Reality Technol. & Syst., Beihang Univ., Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Youjiao Shi",
"fullName": "Youjiao Shi",
"affiliation": "State Key Lab. of Virtual Reality Technol. & Syst., Beihang Univ., Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Shuai Liu",
"fullName": "Shuai Liu",
"affiliation": "State Key Lab. of Virtual Reality Technol. & Syst., Beihang Univ., Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Yuru Zhang",
"fullName": "Yuru Zhang",
"affiliation": "State Key Lab. of Virtual Reality Technol. & Syst., Beihang Univ., Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Jing Xiao",
"fullName": "Jing Xiao",
"affiliation": "Dept. of Comput. Sci., Univ. of North Carolina-Charlotte, Charlotte, NC, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2014-01-01 00:00:00",
"pubType": "trans",
"pages": "48-60",
"year": "2014",
"issn": "1939-1412",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icisa/2012/1402/0/06220964",
"title": "Visual, Haptic, and Auditory Realities Based Dental Training Simulator",
"doi": null,
"abstractUrl": "/proceedings-article/icisa/2012/06220964/12OmNAle6mY",
"parentPublication": {
"id": "proceedings/icisa/2012/1402/0",
"title": "2012 International Conference on Information Science and Applications (ICISA 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2017/2089/0/2089a202",
"title": "Modeling Deformable Objects for Medical Training with Haptic Devices",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2017/2089a202/12OmNCbU2U1",
"parentPublication": {
"id": "proceedings/cw/2017/2089/0",
"title": "2017 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itme/2016/3906/0/3906a424",
"title": "Application of a 3D Haptic Virtual Reality Simulation System for Dental Crown Preparation Training",
"doi": null,
"abstractUrl": "/proceedings-article/itme/2016/3906a424/12OmNrAMEPv",
"parentPublication": {
"id": "proceedings/itme/2016/3906/0",
"title": "2016 8th International Conference on Information Technology in Medicine and Education (ITME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2011/4602/0/4602a179",
"title": "iFeel3: A Haptic Device for Virtual Reality Dental Surgery Simulation",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2011/4602a179/12OmNvT2pcK",
"parentPublication": {
"id": "proceedings/icvrv/2011/4602/0",
"title": "2011 International Conference on Virtual Reality and Visualization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/waina/2015/1775/0/1775a044",
"title": "Development of Virtual Palpation System for Dental Education",
"doi": null,
"abstractUrl": "/proceedings-article/waina/2015/1775a044/12OmNwMFMfZ",
"parentPublication": {
"id": "proceedings/waina/2015/1775/0",
"title": "2015 IEEE 29th International Conference on Advanced Information Networking and Applications Workshops (WAINA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bmei/2008/3118/2/3118b793",
"title": "Deformation Design Technology of Dental Restoration Model",
"doi": null,
"abstractUrl": "/proceedings-article/bmei/2008/3118b793/12OmNwwd2QJ",
"parentPublication": {
"id": "proceedings/bmei/2008/3118/2",
"title": "BioMedical Engineering and Informatics, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptic/2006/0226/0/01627085",
"title": "Impulse Response Deformation Model: an Approach to Haptic Interaction with Dynamically Deformable Object",
"doi": null,
"abstractUrl": "/proceedings-article/haptic/2006/01627085/12OmNylKAQY",
"parentPublication": {
"id": "proceedings/haptic/2006/0226/0",
"title": "Haptic Interfaces for Virtual Environment and Teleoperator Systems, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2011/01/tth2011010039",
"title": "Physics-Based Haptic Simulation of Bone Machining",
"doi": null,
"abstractUrl": "/journal/th/2011/01/tth2011010039/13rRUwIF6le",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2012/04/tth2012040332",
"title": "iDental: A Haptic-Based Dental Simulator and Its Preliminary User Evaluation",
"doi": null,
"abstractUrl": "/journal/th/2012/04/tth2012040332/13rRUy2YLYG",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2016/02/07412781",
"title": "Six Degree-of-Freedom Haptic Simulation of Probing Dental Caries Within a Narrow Oral Cavity",
"doi": null,
"abstractUrl": "/journal/th/2016/02/07412781/13rRUzpzeBh",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06674293",
"articleId": "13rRUxAASW5",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06678361",
"articleId": "13rRUwdrdKO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNqBKTZQ",
"title": "September/October",
"year": "2009",
"issueNum": "05",
"idPrefix": "tg",
"pubType": "journal",
"volume": "15",
"label": "September/October",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUy3gn7r",
"doi": "10.1109/TVCG.2009.40",
"abstract": "In this paper, we solve the problem of 3D shape interpolation with significant pose variation. For an ideal 3D shape interpolation, especially the articulated model, the shape should follow the movement of the underlying articulated structure and be transformed in a way that is as rigid as possible. Given input shapes with compatible connectivity, we propose a novel multiresolution mean shift (MMS) clustering algorithm to automatically extract their near-rigid components. Then, by building the hierarchical relationship among extracted components, we compute a common articulated structure for these input shapes. With the aid of this articulated structure, we solve the shape interpolation by combining 1) a global pose interpolation of near-rigid components from the source shape to the target shape with 2) a local gradient field interpolation for each pair of components, followed by solving a Poisson equation in order to reconstruct an interpolated shape. As a result, an aesthetically pleasing shape interpolation can be generated, with even the poses of shapes varying significantly. In contrast to a recent state-of-the-art work [CHECK END OF SENTENCE], the proposed approach can achieve comparable or even better results and have better computational efficiency as well.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, we solve the problem of 3D shape interpolation with significant pose variation. For an ideal 3D shape interpolation, especially the articulated model, the shape should follow the movement of the underlying articulated structure and be transformed in a way that is as rigid as possible. Given input shapes with compatible connectivity, we propose a novel multiresolution mean shift (MMS) clustering algorithm to automatically extract their near-rigid components. Then, by building the hierarchical relationship among extracted components, we compute a common articulated structure for these input shapes. With the aid of this articulated structure, we solve the shape interpolation by combining 1) a global pose interpolation of near-rigid components from the source shape to the target shape with 2) a local gradient field interpolation for each pair of components, followed by solving a Poisson equation in order to reconstruct an interpolated shape. As a result, an aesthetically pleasing shape interpolation can be generated, with even the poses of shapes varying significantly. In contrast to a recent state-of-the-art work [CHECK END OF SENTENCE], the proposed approach can achieve comparable or even better results and have better computational efficiency as well.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, we solve the problem of 3D shape interpolation with significant pose variation. For an ideal 3D shape interpolation, especially the articulated model, the shape should follow the movement of the underlying articulated structure and be transformed in a way that is as rigid as possible. Given input shapes with compatible connectivity, we propose a novel multiresolution mean shift (MMS) clustering algorithm to automatically extract their near-rigid components. Then, by building the hierarchical relationship among extracted components, we compute a common articulated structure for these input shapes. With the aid of this articulated structure, we solve the shape interpolation by combining 1) a global pose interpolation of near-rigid components from the source shape to the target shape with 2) a local gradient field interpolation for each pair of components, followed by solving a Poisson equation in order to reconstruct an interpolated shape. As a result, an aesthetically pleasing shape interpolation can be generated, with even the poses of shapes varying significantly. In contrast to a recent state-of-the-art work [CHECK END OF SENTENCE], the proposed approach can achieve comparable or even better results and have better computational efficiency as well.",
"title": "Multiresolution Mean Shift Clustering Algorithm for Shape Interpolation",
"normalizedTitle": "Multiresolution Mean Shift Clustering Algorithm for Shape Interpolation",
"fno": "ttg2009050853",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Shape Interpolation",
"Pose Configuration",
"Multiresolution Mean Shift MMS Clustering"
],
"authors": [
{
"givenName": "Hung-Kuo",
"surname": "Chu",
"fullName": "Hung-Kuo Chu",
"affiliation": "National Cheng-Kung University, Tainan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tong-Yee",
"surname": "Lee",
"fullName": "Tong-Yee Lee",
"affiliation": "National Cheng-Kung University, Tainan",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2009-09-01 00:00:00",
"pubType": "trans",
"pages": "853-866",
"year": "2009",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/pg/2001/1227/0/12270060",
"title": "Multiresolution Interpolation Meshes",
"doi": null,
"abstractUrl": "/proceedings-article/pg/2001/12270060/12OmNAYGlnv",
"parentPublication": {
"id": "proceedings/pg/2001/1227/0",
"title": "Computer Graphics and Applications, Pacific Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cmpeur/1993/4030/0/00289872",
"title": "Design by interpolation",
"doi": null,
"abstractUrl": "/proceedings-article/cmpeur/1993/00289872/12OmNAlvHXR",
"parentPublication": {
"id": "proceedings/cmpeur/1993/4030/0",
"title": "Proceedings of COMPEURO '93",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcs/1999/0253/2/02530939",
"title": "Shape-Based Interpolation of Binary 3-D Images using Morphological Skeletonization",
"doi": null,
"abstractUrl": "/proceedings-article/icmcs/1999/02530939/12OmNAqCtPp",
"parentPublication": {
"id": "proceedings/icmcs/1999/0253/2",
"title": "Multimedia Computing and Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/crv/2009/3651/0/3651a016",
"title": "Efficient Target Recovery Using STAGE for Mean-shift Tracking",
"doi": null,
"abstractUrl": "/proceedings-article/crv/2009/3651a016/12OmNBziBdU",
"parentPublication": {
"id": "proceedings/crv/2009/3651/0",
"title": "2009 Canadian Conference on Computer and Robot Vision",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnc/2008/3304/4/3304d177",
"title": "Multimodal Medical Image Elastic Registration Using Mean Shift",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2008/3304d177/12OmNqBbHx1",
"parentPublication": {
"id": "proceedings/icnc/2008/3304/4",
"title": "2008 Fourth International Conference on Natural Computation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2010/4319/0/4319a098",
"title": "Can Mean Shift Trackers Perform Better?",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2010/4319a098/12OmNscxj1p",
"parentPublication": {
"id": "proceedings/sitis/2010/4319/0",
"title": "2010 Sixth International Conference on Signal-Image Technology and Internet Based Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2010/4109/0/4109c094",
"title": "Shape Interpolation with Flattenings",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2010/4109c094/12OmNwt5sl1",
"parentPublication": {
"id": "proceedings/icpr/2010/4109/0",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/co/1995/09/r9057",
"title": "Similar-Shape Retrieval In Shape Data Management",
"doi": null,
"abstractUrl": "/magazine/co/1995/09/r9057/13rRUxBa5pR",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200m2981",
"title": "A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200m2981/1BmL8RNtcbu",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900h469",
"title": "NeuroMorph: Unsupervised Shape Interpolation and Correspondence in One Go",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900h469/1yeKwiTaEDe",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttg2009050841",
"articleId": "13rRUwInv4j",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttg2009050867",
"articleId": "13rRUxlgy3A",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "17ShDTYet4E",
"name": "ttg2009050853s.rar",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg2009050853s.rar",
"extension": "rar",
"size": "36.1 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNqG0SS0",
"title": "Sept.-Oct.",
"year": "2012",
"issueNum": "05",
"idPrefix": "tb",
"pubType": "journal",
"volume": "9",
"label": "Sept.-Oct.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUIJuxnX",
"doi": "10.1109/TCBB.2012.64",
"abstract": "In the last two decades, a lot of protein 3D shapes have been discovered, characterized, and made available thanks to the Protein Data Bank (PDB), that is nevertheless growing very quickly. New scalable methods are thus urgently required to search through the PDB efficiently. This paper presents an approach entitled LNA (Laplacian Norm Alignment) that performs a structural comparison of two proteins with dynamic programming algorithms. This is achieved by characterizing each residue in the protein with scalar features. The feature values are calculated using a Laplacian operator applied on the graph corresponding to the adjacency matrix of the residues. The weighted Laplacian operator we use estimates, at various scales, local deformations of the topology where each residue is located. On some benchmarks, which are widely shared by the community, we obtain qualitatively similar results compared to other competing approaches, but with an algorithm one or two order of magnitudes faster. 180,000 protein comparisons can be done within 1 second with a single recent Graphical Processing Unit (GPU), which makes our algorithm very scalable and suitable for real-time database querying across the web.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In the last two decades, a lot of protein 3D shapes have been discovered, characterized, and made available thanks to the Protein Data Bank (PDB), that is nevertheless growing very quickly. New scalable methods are thus urgently required to search through the PDB efficiently. This paper presents an approach entitled LNA (Laplacian Norm Alignment) that performs a structural comparison of two proteins with dynamic programming algorithms. This is achieved by characterizing each residue in the protein with scalar features. The feature values are calculated using a Laplacian operator applied on the graph corresponding to the adjacency matrix of the residues. The weighted Laplacian operator we use estimates, at various scales, local deformations of the topology where each residue is located. On some benchmarks, which are widely shared by the community, we obtain qualitatively similar results compared to other competing approaches, but with an algorithm one or two order of magnitudes faster. 180,000 protein comparisons can be done within 1 second with a single recent Graphical Processing Unit (GPU), which makes our algorithm very scalable and suitable for real-time database querying across the web.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In the last two decades, a lot of protein 3D shapes have been discovered, characterized, and made available thanks to the Protein Data Bank (PDB), that is nevertheless growing very quickly. New scalable methods are thus urgently required to search through the PDB efficiently. This paper presents an approach entitled LNA (Laplacian Norm Alignment) that performs a structural comparison of two proteins with dynamic programming algorithms. This is achieved by characterizing each residue in the protein with scalar features. The feature values are calculated using a Laplacian operator applied on the graph corresponding to the adjacency matrix of the residues. The weighted Laplacian operator we use estimates, at various scales, local deformations of the topology where each residue is located. On some benchmarks, which are widely shared by the community, we obtain qualitatively similar results compared to other competing approaches, but with an algorithm one or two order of magnitudes faster. 180,000 protein comparisons can be done within 1 second with a single recent Graphical Processing Unit (GPU), which makes our algorithm very scalable and suitable for real-time database querying across the web.",
"title": "LNA: Fast Protein Structural Comparison Using a Laplacian Characterization of Tertiary Structure",
"normalizedTitle": "LNA: Fast Protein Structural Comparison Using a Laplacian Characterization of Tertiary Structure",
"fno": "ttb2012051451",
"hasPdf": true,
"idPrefix": "tb",
"keywords": [
"Proteins",
"Biology Computing",
"Dynamic Programming",
"Graph Theory",
"Graphics Processing Units",
"Molecular Biophysics",
"Molecular Configurations",
"Web",
"Protein Structural Comparison",
"Laplacian Characterization",
"Tertiary Structure",
"Protein 3 D Shapes",
"Protein Data Bank",
"Laplacian Norm Alignment",
"Dynamic Programming Algorithms",
"Graph",
"Adjacency Matrix",
"Weighted Laplacian Operator",
"Local Deformations",
"Topology",
"Graphical Processing Unit",
"GPU",
"Real Time Database Querying",
"Proteins",
"Laplace Equations",
"Three Dimensional Displays",
"Dynamic Programming",
"Heuristic Algorithms",
"Graphics Processing Unit",
"Accuracy",
"GPU Implementation",
"Proteins",
"Structural Comparison",
"Laplacian",
"Classification"
],
"authors": [
{
"givenName": "Nicolas",
"surname": "Bonnel",
"fullName": "Nicolas Bonnel",
"affiliation": "IRISA, Universitede Bretagne Sud, Vannes, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Pierre-Francois",
"surname": "Marteau",
"fullName": "Pierre-Francois Marteau",
"affiliation": "IRISA, Universitede Bretagne Sud, Vannes, France",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2012-09-01 00:00:00",
"pubType": "trans",
"pages": "1451-1458",
"year": "2012",
"issn": "1545-5963",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2016/1611/0/07822503",
"title": "Improved protein residue-residue contacts prediction using learning-to-rank",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2016/07822503/12OmNqIQSeH",
"parentPublication": {
"id": "proceedings/bibm/2016/1611/0",
"title": "2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccabs/2011/4851/0/261",
"title": "Poster: PRDDs: A Protein Residue Distance & Angle Distribution Database for Secondary Structures",
"doi": null,
"abstractUrl": "/proceedings-article/iccabs/2011/261/12OmNvq5jxl",
"parentPublication": {
"id": "proceedings/iccabs/2011/4851/0",
"title": "2011 IEEE 1st International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dbkda/2009/3550/0/3550a001",
"title": "IRCDB: A Database of Inter-residues Contacts in Protein Chains",
"doi": null,
"abstractUrl": "/proceedings-article/dbkda/2009/3550a001/12OmNyvY9vp",
"parentPublication": {
"id": "proceedings/dbkda/2009/3550/0",
"title": "Advances in Databases, First International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ainaw/2008/3096/0/3096a796",
"title": "Protein Structure Comparison and Alignment Using Residue Contexts",
"doi": null,
"abstractUrl": "/proceedings-article/ainaw/2008/3096a796/12OmNyvoXeT",
"parentPublication": {
"id": "proceedings/ainaw/2008/3096/0",
"title": "2008 22nd International Conference on Advanced Information Networking and Applications (AINA 2008)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2012/03/06138846",
"title": "Protein Complexes Discovery Based on Protein-Protein Interaction Data via a Regularized Sparse Generative Network Model",
"doi": null,
"abstractUrl": "/journal/tb/2012/03/06138846/13rRUwdrdRd",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2008/03/ttb2008030357",
"title": "Reconstruction of 3D Structures From Protein Contact Maps",
"doi": null,
"abstractUrl": "/journal/tb/2008/03/ttb2008030357/13rRUxASuEr",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2012/04/06051424",
"title": "Efficient Approaches for Retrieving Protein Tertiary Structures",
"doi": null,
"abstractUrl": "/journal/tb/2012/04/06051424/13rRUxYrbT4",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995562",
"title": "S-PDB: Analysis and Classification of SARS-CoV-2 Spike Protein Structures",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995562/1JC3vGAkMzC",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/5555/01/10106042",
"title": "DeepSG2PPI: A Protein-Protein Interaction Prediction Method Based on Deep Learning",
"doi": null,
"abstractUrl": "/journal/tb/5555/01/10106042/1MuViSurZYY",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2020/9274/0/927400a308",
"title": "Fusion of BLAST and Ensemble of Classifiers for Protein Secondary Structure Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2020/927400a308/1p2VzIqeWd2",
"parentPublication": {
"id": "proceedings/sibgrapi/2020/9274/0",
"title": "2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttb2012051442",
"articleId": "13rRUxcbnAV",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttb2012051459",
"articleId": "13rRUxE04s4",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzDvSjl",
"title": "July",
"year": "1988",
"issueNum": "04",
"idPrefix": "tp",
"pubType": "journal",
"volume": "10",
"label": "July",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxBJhwm",
"doi": "10.1109/34.3914",
"abstract": "Line drawings of man-made scenes often exhibit instances of straight lines and conic sections, i.e. ellipses, parabolas, and hyperbolas. Constraints imposed on the scene by such instances are investigated, under the assumption of general viewpoint, i.e. the mapping of the viewed surface onto the line drawing is stable under perturbation of the viewpoint within some open set. Both orthographic and perspective projection are considered. The viewed surfaces are assumed to be piecewise C/sup 3/. It is shown that straight lines and conic sections in line drawings are projections of scene edges which are also straight lines and conic sections, respectively. It is also shown that scene events which project onto straight lines or conic sections cannot be combinations of view-point-independent and viewpoint-dependent edges. Further, continuous-surface-normal depth discontinuities which project onto straight lines can be locally described by developable surfaces, and those which project onto conic sections can be locally described by nondevelopable quadric surfaces. Each of these quadric surfaces is determined up to four degrees-of-freedom by its projection.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Line drawings of man-made scenes often exhibit instances of straight lines and conic sections, i.e. ellipses, parabolas, and hyperbolas. Constraints imposed on the scene by such instances are investigated, under the assumption of general viewpoint, i.e. the mapping of the viewed surface onto the line drawing is stable under perturbation of the viewpoint within some open set. Both orthographic and perspective projection are considered. The viewed surfaces are assumed to be piecewise C/sup 3/. It is shown that straight lines and conic sections in line drawings are projections of scene edges which are also straight lines and conic sections, respectively. It is also shown that scene events which project onto straight lines or conic sections cannot be combinations of view-point-independent and viewpoint-dependent edges. Further, continuous-surface-normal depth discontinuities which project onto straight lines can be locally described by developable surfaces, and those which project onto conic sections can be locally described by nondevelopable quadric surfaces. Each of these quadric surfaces is determined up to four degrees-of-freedom by its projection.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Line drawings of man-made scenes often exhibit instances of straight lines and conic sections, i.e. ellipses, parabolas, and hyperbolas. Constraints imposed on the scene by such instances are investigated, under the assumption of general viewpoint, i.e. the mapping of the viewed surface onto the line drawing is stable under perturbation of the viewpoint within some open set. Both orthographic and perspective projection are considered. The viewed surfaces are assumed to be piecewise C/sup 3/. It is shown that straight lines and conic sections in line drawings are projections of scene edges which are also straight lines and conic sections, respectively. It is also shown that scene events which project onto straight lines or conic sections cannot be combinations of view-point-independent and viewpoint-dependent edges. Further, continuous-surface-normal depth discontinuities which project onto straight lines can be locally described by developable surfaces, and those which project onto conic sections can be locally described by nondevelopable quadric surfaces. Each of these quadric surfaces is determined up to four degrees-of-freedom by its projection.",
"title": "Line-Drawing Interpretation: Straight Lines and Conic Sections",
"normalizedTitle": "Line-Drawing Interpretation: Straight Lines and Conic Sections",
"fno": "i0514",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Line Drawing Interpretation Picture Processing Pattern Recognition Straight Lines Conic Sections Ellipses Parabolas Hyperbolas Perturbation Line Drawings Scene Edges Quadric Surfaces Pattern Recognition Picture Processing"
],
"authors": [
{
"givenName": "V.S.",
"surname": "Nalwa",
"fullName": "V.S. Nalwa",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": false,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "1988-07-01 00:00:00",
"pubType": "trans",
"pages": "514-529",
"year": "1988",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [],
"adjacentArticles": {
"previous": {
"fno": "i0496",
"articleId": "13rRUxly8Ym",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "i0530",
"articleId": "13rRUygT7yS",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNBTawgO",
"title": "October-December",
"year": "2009",
"issueNum": "04",
"idPrefix": "tb",
"pubType": "journal",
"volume": "6",
"label": "October-December",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxYrbT0",
"doi": "10.1109/TCBB.2007.70257",
"abstract": "Until recently, numerous feature selection techniques have been proposed and found wide applications in genomics and proteomics. For instance, feature/gene selection has proven to be useful for biomarker discovery from microarray and mass spectrometry data. While supervised feature selection has been explored extensively, there are only a few unsupervised methods that can be applied to exploratory data analysis. In this paper, we address the problem of unsupervised feature selection. First, we extend Laplacian linear discriminant analysis (LLDA) to unsupervised cases. Second, we propose a novel algorithm for computing LLDA, which is efficient in the case of high dimensionality and small sample size as in microarray data. Finally, an unsupervised feature selection method, called LLDA-based Recursive Feature Elimination (LLDA-RFE), is proposed. We apply LLDA-RFE to several public data sets of cancer microarrays and compare its performance with those of Laplacian score and SVD-entropy, two state-of-the-art unsupervised methods, and with that of Fisher score, a supervised filter method. Our results demonstrate that LLDA-RFE outperforms Laplacian score and shows favorable performance against SVD-entropy. It performs even better than Fisher score for some of the data sets, despite the fact that LLDA-RFE is fully unsupervised.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Until recently, numerous feature selection techniques have been proposed and found wide applications in genomics and proteomics. For instance, feature/gene selection has proven to be useful for biomarker discovery from microarray and mass spectrometry data. While supervised feature selection has been explored extensively, there are only a few unsupervised methods that can be applied to exploratory data analysis. In this paper, we address the problem of unsupervised feature selection. First, we extend Laplacian linear discriminant analysis (LLDA) to unsupervised cases. Second, we propose a novel algorithm for computing LLDA, which is efficient in the case of high dimensionality and small sample size as in microarray data. Finally, an unsupervised feature selection method, called LLDA-based Recursive Feature Elimination (LLDA-RFE), is proposed. We apply LLDA-RFE to several public data sets of cancer microarrays and compare its performance with those of Laplacian score and SVD-entropy, two state-of-the-art unsupervised methods, and with that of Fisher score, a supervised filter method. Our results demonstrate that LLDA-RFE outperforms Laplacian score and shows favorable performance against SVD-entropy. It performs even better than Fisher score for some of the data sets, despite the fact that LLDA-RFE is fully unsupervised.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Until recently, numerous feature selection techniques have been proposed and found wide applications in genomics and proteomics. For instance, feature/gene selection has proven to be useful for biomarker discovery from microarray and mass spectrometry data. While supervised feature selection has been explored extensively, there are only a few unsupervised methods that can be applied to exploratory data analysis. In this paper, we address the problem of unsupervised feature selection. First, we extend Laplacian linear discriminant analysis (LLDA) to unsupervised cases. Second, we propose a novel algorithm for computing LLDA, which is efficient in the case of high dimensionality and small sample size as in microarray data. Finally, an unsupervised feature selection method, called LLDA-based Recursive Feature Elimination (LLDA-RFE), is proposed. We apply LLDA-RFE to several public data sets of cancer microarrays and compare its performance with those of Laplacian score and SVD-entropy, two state-of-the-art unsupervised methods, and with that of Fisher score, a supervised filter method. Our results demonstrate that LLDA-RFE outperforms Laplacian score and shows favorable performance against SVD-entropy. It performs even better than Fisher score for some of the data sets, despite the fact that LLDA-RFE is fully unsupervised.",
"title": "Laplacian Linear Discriminant Analysis Approach to Unsupervised Feature Selection",
"normalizedTitle": "Laplacian Linear Discriminant Analysis Approach to Unsupervised Feature Selection",
"fno": "ttb2009040605",
"hasPdf": true,
"idPrefix": "tb",
"keywords": [
"Unsupervised Feature Selection",
"Linear Discriminant Analysis",
"Graph Laplacian",
"Microarray Data Analysis"
],
"authors": [
{
"givenName": "Satoshi",
"surname": "Niijima",
"fullName": "Satoshi Niijima",
"affiliation": "Kyoto University, Kyoto",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yasushi",
"surname": "Okuno",
"fullName": "Yasushi Okuno",
"affiliation": "Kyoto University, Kyoto",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2009-10-01 00:00:00",
"pubType": "trans",
"pages": "605-614",
"year": "2009",
"issn": "1545-5963",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/isda/2009/3872/0/3872a560",
"title": "Measures for Unsupervised Fuzzy-Rough Feature Selection",
"doi": null,
"abstractUrl": "/proceedings-article/isda/2009/3872a560/12OmNAQJzU0",
"parentPublication": {
"id": "proceedings/isda/2009/3872/0",
"title": "Intelligent Systems Design and Applications, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2009/3804/4/3804e513",
"title": "Ensemble Method for Unsupervised Feature Selection",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2009/3804e513/12OmNBNM8MS",
"parentPublication": {
"id": "proceedings/icicta/2009/3804/4",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dcabes/2011/4415/0/4415a183",
"title": "A Novel Unsupervised Optimal Discriminant Plane",
"doi": null,
"abstractUrl": "/proceedings-article/dcabes/2011/4415a183/12OmNCdBDVH",
"parentPublication": {
"id": "proceedings/dcabes/2011/4415/0",
"title": "2011 10th International Symposium on Distributed Computing and Applications to Business, Engineering and Science",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdh/2012/4899/0/4899a201",
"title": "Graph Laplacian Based Visual Saliency Detection",
"doi": null,
"abstractUrl": "/proceedings-article/icdh/2012/4899a201/12OmNCeaPTQ",
"parentPublication": {
"id": "proceedings/icdh/2012/4899/0",
"title": "4th International Conference on Digital Home (ICDH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iita/2009/3859/3/3859c065",
"title": "An Unsupervised Feature Selection Algorithm: Laplacian Score Combined with Distance-Based Entropy Measure",
"doi": null,
"abstractUrl": "/proceedings-article/iita/2009/3859c065/12OmNrYlmAM",
"parentPublication": {
"id": "proceedings/iita/2009/3859/3",
"title": "2009 Third International Symposium on Intelligent Information Technology Application",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apcip/2009/3699/2/3699b196",
"title": "Univariate Filter Technique for Unsupervised Feature Selection Using a New Laplacian Score Based Local Nearest Neighbors",
"doi": null,
"abstractUrl": "/proceedings-article/apcip/2009/3699b196/12OmNvHY2HV",
"parentPublication": {
"id": "proceedings/apcip/2009/3699/1",
"title": "Information Processing, Asia-Pacific Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csie/2009/3507/6/3507f043",
"title": "Laplacian MinMax Discriminant Projections",
"doi": null,
"abstractUrl": "/proceedings-article/csie/2009/3507f043/12OmNxjjEe3",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fskd/2008/3305/2/3305b315",
"title": "Unsupervised Optimal Discriminant Plane Based Feature Extraction Method",
"doi": null,
"abstractUrl": "/proceedings-article/fskd/2008/3305b315/12OmNy6qfM3",
"parentPublication": {
"id": "fskd/2008/3305/2",
"title": "Fuzzy Systems and Knowledge Discovery, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibmw/2012/2746/0/06470231",
"title": "Graph based unsupervised feature selection for microarray data",
"doi": null,
"abstractUrl": "/proceedings-article/bibmw/2012/06470231/12OmNzcPAKR",
"parentPublication": {
"id": "proceedings/bibmw/2012/2746/0",
"title": "2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2011/4408/0/4408a161",
"title": "An Efficient Greedy Method for Unsupervised Feature Selection",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2011/4408a161/12OmNzwHvhP",
"parentPublication": {
"id": "proceedings/icdm/2011/4408/0",
"title": "2011 IEEE 11th International Conference on Data Mining",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttb2009040594",
"articleId": "13rRUyY28WM",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttb2009040629",
"articleId": "13rRUwhHcPl",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1MET2WIbdvy",
"title": "May",
"year": "2023",
"issueNum": "05",
"idPrefix": "co",
"pubType": "magazine",
"volume": "56",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1MET41UR3QA",
"doi": "10.1109/MC.2023.3234978",
"abstract": "We evaluate the racial bias in face recognition application programming interfaces (APIs) using real and deepfake celebrity images. We use deepfake generation methods to introduce small, imperceptible changes to the real images to shift the racial class of predictions, showing how deepfake images exacerbated racial bias in web-based face recognition APIs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We evaluate the racial bias in face recognition application programming interfaces (APIs) using real and deepfake celebrity images. We use deepfake generation methods to introduce small, imperceptible changes to the real images to shift the racial class of predictions, showing how deepfake images exacerbated racial bias in web-based face recognition APIs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We evaluate the racial bias in face recognition application programming interfaces (APIs) using real and deepfake celebrity images. We use deepfake generation methods to introduce small, imperceptible changes to the real images to shift the racial class of predictions, showing how deepfake images exacerbated racial bias in web-based face recognition APIs.",
"title": "Evaluating Trustworthiness and Racial Bias in Face Recognition APIs Using Deepfakes",
"normalizedTitle": "Evaluating Trustworthiness and Racial Bias in Face Recognition APIs Using Deepfakes",
"fno": "10109304",
"hasPdf": true,
"idPrefix": "co",
"keywords": [
"Deepfakes",
"Face Recognition",
"Application Programming Interfaces",
"Trust Computing",
"Cultural Aspects",
"Image Recognition"
],
"authors": [
{
"givenName": "Shahroz",
"surname": "Tariq",
"fullName": "Shahroz Tariq",
"affiliation": "Data61 CSIRO, Sydney, Australia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sowon",
"surname": "Jeon",
"fullName": "Sowon Jeon",
"affiliation": "KPMG Korea, Suwon, South Korea",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Simon S.",
"surname": "Woo",
"fullName": "Simon S. Woo",
"affiliation": "Department of Applied Data Science, and the Department of Computer Science and Engineering, SKKU Institute for Convergence, Sungkyunkwan University, Suwon, Korea",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2023-05-01 00:00:00",
"pubType": "mags",
"pages": "51-61",
"year": "2023",
"issn": "0018-9162",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2022/0915/0/091500d202",
"title": "Measuring Hidden Bias within Face Recognition via Racial Phenotypes",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500d202/1B12FxwJfcA",
"parentPublication": {
"id": "proceedings/wacv/2022/0915/0",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2022/9062/0/09956501",
"title": "Defending Against Deepfakes with Ensemble Adversarial Perturbation",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2022/09956501/1IHqzRyH48o",
"parentPublication": {
"id": "proceedings/icpr/2022/9062/0",
"title": "2022 26th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tq/5555/01/10035845",
"title": "Making DeepFakes More Spurious: Evading Deep Face Forgery Detection via Trace Removal Attack",
"doi": null,
"abstractUrl": "/journal/tq/5555/01/10035845/1KrcdrD92gg",
"parentPublication": {
"id": "trans/tq",
"title": "IEEE Transactions on Dependable and Secure Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacvw/2023/2056/0/205600a313",
"title": "The Impact of Racial Distribution in Training Data on Face Recognition Bias: A Closer Look",
"doi": null,
"abstractUrl": "/proceedings-article/wacvw/2023/205600a313/1Kzz6yIsuAM",
"parentPublication": {
"id": "proceedings/wacvw/2023/2056/0",
"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08798122",
"title": "An Initial Investigation into Stereotypical Influences on Implicit Racial Bias and Embodied Avatars",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798122/1cJ0MR4xjWg",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08798008",
"title": "[DC] Embodied Virtual Avatars and Potential Negative Effects on Implicit Racial Bias",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798008/1cJ0WBlYR7G",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300a692",
"title": "Racial Faces in the Wild: Reducing Racial Bias by Information Maximization Adaptation Network",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300a692/1hQql9tdgWI",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2020/9360/0/09150678",
"title": "Exploring Racial Bias within Face Recognition via per-subject Adversarially-Enabled Data Augmentation",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2020/09150678/1lPH2dVH9du",
"parentPublication": {
"id": "proceedings/cvprw/2020/9360/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09382876",
"title": "Evidence of Racial Bias Using Immersive Virtual Reality: Analysis of Head and Hand Motions During Shooting Decisions",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09382876/1saZsrqdHJm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/1.91E110",
"title": "Rethinking Common Assumptions to Mitigate Racial Bias in Face Recognition Datasets",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/1.91E110/1yNivKe9xbW",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "10109293",
"articleId": "1MET7vZzqLu",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "10109264",
"articleId": "1MET6LZ8mFa",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1sP18ke9Y64",
"title": "May",
"year": "2021",
"issueNum": "05",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1saZCLk2sSI",
"doi": "10.1109/TVCG.2021.3067687",
"abstract": "Hands are the most important tool to interact with virtual environments, and they should be available to perform the most critical tasks. For example, a surgeon in VR should keep his/her hands on the instruments and be able to do secondary tasks without performing a disruptive event to the operative task. In this common scenario, one can observe that hands are not available for interaction. The goal of this systematic review is to survey the literature and identify which hands-free interfaces are used, the performed interaction tasks, what metrics are used for interface evaluation, and the results of such evaluations. From 79 studies that met the eligibility criteria, the voice is the most studied interface, followed by the eye and head gaze. Some novel interfaces were brain interfaces and face expressions. System control and selection represent most of the interaction tasks studied and most studies evaluate interfaces for usability. Despite the best interface depending on the task and study, the voice was found to be versatile and showed good results amongst the studies. More research is recommended to improve the practical use of the interfaces and to evaluate the interfaces more formally.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Hands are the most important tool to interact with virtual environments, and they should be available to perform the most critical tasks. For example, a surgeon in VR should keep his/her hands on the instruments and be able to do secondary tasks without performing a disruptive event to the operative task. In this common scenario, one can observe that hands are not available for interaction. The goal of this systematic review is to survey the literature and identify which hands-free interfaces are used, the performed interaction tasks, what metrics are used for interface evaluation, and the results of such evaluations. From 79 studies that met the eligibility criteria, the voice is the most studied interface, followed by the eye and head gaze. Some novel interfaces were brain interfaces and face expressions. System control and selection represent most of the interaction tasks studied and most studies evaluate interfaces for usability. Despite the best interface depending on the task and study, the voice was found to be versatile and showed good results amongst the studies. More research is recommended to improve the practical use of the interfaces and to evaluate the interfaces more formally.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Hands are the most important tool to interact with virtual environments, and they should be available to perform the most critical tasks. For example, a surgeon in VR should keep his/her hands on the instruments and be able to do secondary tasks without performing a disruptive event to the operative task. In this common scenario, one can observe that hands are not available for interaction. The goal of this systematic review is to survey the literature and identify which hands-free interfaces are used, the performed interaction tasks, what metrics are used for interface evaluation, and the results of such evaluations. From 79 studies that met the eligibility criteria, the voice is the most studied interface, followed by the eye and head gaze. Some novel interfaces were brain interfaces and face expressions. System control and selection represent most of the interaction tasks studied and most studies evaluate interfaces for usability. Despite the best interface depending on the task and study, the voice was found to be versatile and showed good results amongst the studies. More research is recommended to improve the practical use of the interfaces and to evaluate the interfaces more formally.",
"title": "Hands-free interaction in immersive virtual reality: A systematic review",
"normalizedTitle": "Hands-free interaction in immersive virtual reality: A systematic review",
"fno": "09382869",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Human Computer Interaction",
"Reviews",
"Virtual Reality",
"Operative Task",
"Systematic Review",
"Hands Free Interfaces",
"Interface Evaluation",
"Brain Interfaces",
"Hands Free Interaction",
"Immersive Virtual Reality",
"Virtual Environments",
"Secondary Tasks",
"Disruptive Event",
"System Control",
"Task Analysis",
"Three Dimensional Displays",
"Navigation",
"Systematics",
"Control Systems",
"Human Computer Interaction",
"Two Dimensional Displays",
"Systematic Review",
"Virtual Reality",
"Human Computer Interaction",
"Hands Free"
],
"authors": [
{
"givenName": "Pedro",
"surname": "Monteiro",
"fullName": "Pedro Monteiro",
"affiliation": "INESC TEC, Porto, Portugal",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Guilherme",
"surname": "Gonçalves",
"fullName": "Guilherme Gonçalves",
"affiliation": "INESC TEC, Porto, Portugal",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hugo",
"surname": "Coelho",
"fullName": "Hugo Coelho",
"affiliation": "INESC TEC, Porto, Portugal",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Miguel",
"surname": "Melo",
"fullName": "Miguel Melo",
"affiliation": "INESC TEC, Porto, Portugal",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Maximino",
"surname": "Bessa",
"fullName": "Maximino Bessa",
"affiliation": "INESC TEC, Porto, Portugal",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2021-05-01 00:00:00",
"pubType": "trans",
"pages": "2702-2713",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ismar/2014/6184/0/06948466",
"title": "[Poster] Interacting with your own hands in a fully immersive MR system",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2014/06948466/12OmNrMHOkY",
"parentPublication": {
"id": "proceedings/ismar/2014/6184/0",
"title": "2014 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2013/6097/0/06550236",
"title": "Poster: Using the whole body for multi-channel gestural interface",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2013/06550236/12OmNx8wTmi",
"parentPublication": {
"id": "proceedings/3dui/2013/6097/0",
"title": "2013 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08446259",
"title": "Hands-Free Interaction for Augmented Reality in Vascular Interventions",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08446259/13bd1gQYgEU",
"parentPublication": {
"id": "proceedings/vr/2018/3365/0",
"title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2022/9617/0/961700a693",
"title": "Systematic Design Space Exploration of Discrete Virtual Rotations in VR",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2022/961700a693/1CJbHGJZxeM",
"parentPublication": {
"id": "proceedings/vr/2022/9617/0",
"title": "2022 IEEE on Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2023/4815/0/481500a123",
"title": "Tell Me Where To Go: Voice-Controlled Hands-Free Locomotion for Virtual Reality Systems",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2023/481500a123/1MNgCwutI3u",
"parentPublication": {
"id": "proceedings/vr/2023/4815/0",
"title": "2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2019/2297/0/229700a057",
"title": "Music in the Air with Leap Motion Controller",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2019/229700a057/1fHkkZzKire",
"parentPublication": {
"id": "proceedings/cw/2019/2297/0",
"title": "2019 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/06/09064606",
"title": "Analysis of the Hands in Egocentric Vision: A Survey",
"doi": null,
"abstractUrl": "/journal/tp/2023/06/09064606/1j4mrhzYkw0",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222346",
"title": "Shared Surfaces and Spaces: Collaborative Data Visualisation in a Co-located Immersive Environment",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222346/1nTqW9mGTrG",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2020/7303/0/730300a400",
"title": "Machine Learning Applied to Support Medical Decision in Transthoracic Echocardiogram Exams: A Systematic Review",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2020/730300a400/1nkDglfxgB2",
"parentPublication": {
"id": "proceedings/compsac/2020/7303/0",
"title": "2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2020/8508/0/850800a344",
"title": "Exploration of Hands-free Text Entry Techniques For Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2020/850800a344/1pysyrYBX5C",
"parentPublication": {
"id": "proceedings/ismar/2020/8508/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09382921",
"articleId": "1saZpvEpGrS",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09382916",
"articleId": "1saZna718yY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNyq0zFI",
"title": "May",
"year": "2020",
"issueNum": "05",
"idPrefix": "tg",
"pubType": "journal",
"volume": "26",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1hpPBi8EjJe",
"doi": "10.1109/TVCG.2020.2973474",
"abstract": "We analyzed the design space of group navigation tasks in distributed virtual environments and present a framework consisting of techniques to form groups, distribute responsibilities, navigate together, and eventually split up again. To improve joint navigation, our work focused on an extension of the Multi-Ray Jumping technique that allows adjusting the spatial formation of two distributed users as part of the target specification process. The results of a quantitative user study showed that these adjustments lead to significant improvements in joint two-user travel, which is evidenced by more efficient travel sequences and lower task loads imposed on the navigator and the passenger. In a qualitative expert review involving all four stages of group navigation, we confirmed the effective and efficient use of our technique in a more realistic use-case scenario and concluded that remote collaboration benefits from fluent transitions between individual and group navigation.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We analyzed the design space of group navigation tasks in distributed virtual environments and present a framework consisting of techniques to form groups, distribute responsibilities, navigate together, and eventually split up again. To improve joint navigation, our work focused on an extension of the Multi-Ray Jumping technique that allows adjusting the spatial formation of two distributed users as part of the target specification process. The results of a quantitative user study showed that these adjustments lead to significant improvements in joint two-user travel, which is evidenced by more efficient travel sequences and lower task loads imposed on the navigator and the passenger. In a qualitative expert review involving all four stages of group navigation, we confirmed the effective and efficient use of our technique in a more realistic use-case scenario and concluded that remote collaboration benefits from fluent transitions between individual and group navigation.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We analyzed the design space of group navigation tasks in distributed virtual environments and present a framework consisting of techniques to form groups, distribute responsibilities, navigate together, and eventually split up again. To improve joint navigation, our work focused on an extension of the Multi-Ray Jumping technique that allows adjusting the spatial formation of two distributed users as part of the target specification process. The results of a quantitative user study showed that these adjustments lead to significant improvements in joint two-user travel, which is evidenced by more efficient travel sequences and lower task loads imposed on the navigator and the passenger. In a qualitative expert review involving all four stages of group navigation, we confirmed the effective and efficient use of our technique in a more realistic use-case scenario and concluded that remote collaboration benefits from fluent transitions between individual and group navigation.",
"title": "Getting There Together: Group Navigation in Distributed Virtual Environments",
"normalizedTitle": "Getting There Together: Group Navigation in Distributed Virtual Environments",
"fno": "08998307",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Groupware",
"User Interfaces",
"Virtual Reality",
"Individual Navigation",
"Group Navigation",
"Remote Collaboration",
"Realistic Use Case Scenario",
"Travel Sequences",
"Joint Two User Travel",
"Navigator",
"Two User Travel",
"Quantitative User Study",
"Distributed Users",
"Multiray Jumping Technique",
"Joint Navigation",
"Group Navigation Tasks",
"Distributed Virtual Environments",
"Navigation",
"Virtual Environments",
"Collaboration",
"Task Analysis",
"Teleportation",
"Avatars",
"Virtual Reality",
"Collaborative Virtual Environments",
"Remote Collaboration",
"Group Navigation",
"Teleportation",
"Jumping"
],
"authors": [
{
"givenName": "Tim",
"surname": "Weissker",
"fullName": "Tim Weissker",
"affiliation": "Virtual Reality and Visualization Research Group, Bauhaus-Universität Weimar",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Pauline",
"surname": "Bimberg",
"fullName": "Pauline Bimberg",
"affiliation": "Virtual Reality and Visualization Research Group, Bauhaus-Universität Weimar",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Bernd",
"surname": "Froehlich",
"fullName": "Bernd Froehlich",
"affiliation": "Virtual Reality and Visualization Research Group, Bauhaus-Universität Weimar",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2020-05-01 00:00:00",
"pubType": "trans",
"pages": "1860-1870",
"year": "2020",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/sive/2014/5781/0/07006288",
"title": "Reproducible sonification for virtual navigation",
"doi": null,
"abstractUrl": "/proceedings-article/sive/2014/07006288/12OmNAtaS0G",
"parentPublication": {
"id": "proceedings/sive/2014/5781/0",
"title": "2014 IEEE VR Workshop: Sonic Interaction in Virtual Environments (SIVE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2012/1204/0/06184223",
"title": "A gaming interface using body gestures for collaborative navigation",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2012/06184223/12OmNwwMf5A",
"parentPublication": {
"id": "proceedings/3dui/2012/1204/0",
"title": "2012 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a556",
"title": "Group WiM: A Group Navigation Technique for Collaborative Virtual Reality Environments",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a556/1CJdXqzjctO",
"parentPublication": {
"id": "proceedings/vrw/2022/8402/0",
"title": "2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/05/10049698",
"title": "Gaining the High Ground: Teleportation to Mid-Air Targets in Immersive Virtual Environments",
"doi": null,
"abstractUrl": "/journal/tg/2023/05/10049698/1KYotugT0xW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aivr/2022/5725/0/572500a082",
"title": "WiM-Based Group Navigation for Collaborative Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/aivr/2022/572500a082/1KmFfzv6fWo",
"parentPublication": {
"id": "proceedings/aivr/2022/5725/0",
"title": "2022 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08797807",
"title": "Multi-Ray Jumping: Comprehensible Group Navigation for Collocated Users in Immersive Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08797807/1cJ0MXFzine",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2021/04/09351621",
"title": "Improved Speaker and Navigator for Vision-and-Language Navigation",
"doi": null,
"abstractUrl": "/magazine/mu/2021/04/09351621/1r50rE3jRZe",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09382870",
"title": "Group Navigation for Guided Tours in Distributed Virtual Environments",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09382870/1saZCxsOG9q",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2021/4057/0/405700a363",
"title": "An Overview of Group Navigation in Multi-User Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2021/405700a363/1tnXytVyks8",
"parentPublication": {
"id": "proceedings/vrw/2021/4057/0",
"title": "2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2021/0477/0/047700d742",
"title": "Auto-Navigator: Decoupled Neural Architecture Search for Visual Navigation",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700d742/1uqGAyRc3Go",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08998337",
"articleId": "1hrXgdu8Bkk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08998139",
"articleId": "1hrXe0Hbv0I",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1iEguSwO6rK",
"name": "ttg202005-08998307s1-supp1-2973474.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202005-08998307s1-supp1-2973474.mp4",
"extension": "mp4",
"size": "55 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1LUpyYLBfeo",
"title": "May",
"year": "2023",
"issueNum": "05",
"idPrefix": "tg",
"pubType": "journal",
"volume": "29",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1KYoqi0DQK4",
"doi": "10.1109/TVCG.2023.3247048",
"abstract": "Virtual and mixed-reality (XR) technology has advanced significantly in the last few years and will enable the future of work, education, socialization, and entertainment. Eye-tracking data is required for supporting novel modes of interaction, animating virtual avatars, and implementing rendering or streaming optimizations. While eye tracking enables many beneficial applications in XR, it also introduces a risk to privacy by enabling re-identification of users. We applied privacy definitions of k-anonymity and plausible deniability (PD) to datasets of eye-tracking samples and evaluated them against the state-of-the-art differential privacy (DP) approach. Two VR datasets were processed to reduce identification rates while minimizing the impact on the performance of trained machine-learning models. Our results suggest that both PD and DP mechanisms produced practical privacy-utility trade-offs with respect to re-identification and activity classification accuracy, while k-anonymity performed best at retaining utility for gaze prediction.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Virtual and mixed-reality (XR) technology has advanced significantly in the last few years and will enable the future of work, education, socialization, and entertainment. Eye-tracking data is required for supporting novel modes of interaction, animating virtual avatars, and implementing rendering or streaming optimizations. While eye tracking enables many beneficial applications in XR, it also introduces a risk to privacy by enabling re-identification of users. We applied privacy definitions of k-anonymity and plausible deniability (PD) to datasets of eye-tracking samples and evaluated them against the state-of-the-art differential privacy (DP) approach. Two VR datasets were processed to reduce identification rates while minimizing the impact on the performance of trained machine-learning models. Our results suggest that both PD and DP mechanisms produced practical privacy-utility trade-offs with respect to re-identification and activity classification accuracy, while k-anonymity performed best at retaining utility for gaze prediction.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Virtual and mixed-reality (XR) technology has advanced significantly in the last few years and will enable the future of work, education, socialization, and entertainment. Eye-tracking data is required for supporting novel modes of interaction, animating virtual avatars, and implementing rendering or streaming optimizations. While eye tracking enables many beneficial applications in XR, it also introduces a risk to privacy by enabling re-identification of users. We applied privacy definitions of k-anonymity and plausible deniability (PD) to datasets of eye-tracking samples and evaluated them against the state-of-the-art differential privacy (DP) approach. Two VR datasets were processed to reduce identification rates while minimizing the impact on the performance of trained machine-learning models. Our results suggest that both PD and DP mechanisms produced practical privacy-utility trade-offs with respect to re-identification and activity classification accuracy, while k-anonymity performed best at retaining utility for gaze prediction.",
"title": "Privacy-preserving datasets of eye-tracking samples with applications in XR",
"normalizedTitle": "Privacy-preserving datasets of eye-tracking samples with applications in XR",
"fno": "10049660",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Avatars",
"Computer Animation",
"Data Privacy",
"Gaze Tracking",
"Learning Artificial Intelligence",
"Virtual Reality",
"Beneficial Applications",
"Eye Tracking",
"Eye Tracking Data",
"Eye Tracking Samples",
"Implementing Rendering",
"Mixed Reality",
"Practical Privacy Utility Trade Offs",
"Privacy Definitions",
"Privacy Preserving Datasets",
"State Of The Art Differential Privacy Approach",
"Virtual Avatars",
"VR Datasets",
"XR",
"Decoding",
"Computer Architecture",
"Privacy",
"Eye Tracking",
"Re Identification",
"Biometrics"
],
"authors": [
{
"givenName": "Brendan",
"surname": "David-John",
"fullName": "Brendan David-John",
"affiliation": "Assistant Professor at the Virginia Polytechnic Institute and State University, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Kevin",
"surname": "Butler",
"fullName": "Kevin Butler",
"affiliation": "Professor at the University of Florida, United States",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Eakta",
"surname": "Jain",
"fullName": "Eakta Jain",
"affiliation": "Associate Professor at the University of Florida, United States",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2023-05-01 00:00:00",
"pubType": "trans",
"pages": "2774-2784",
"year": "2023",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/estimedia/2009/5169/0/05336818",
"title": "A high-throughput pipelined architecture for JPEG XR encoding",
"doi": null,
"abstractUrl": "/proceedings-article/estimedia/2009/05336818/12OmNC4eSGu",
"parentPublication": {
"id": "proceedings/estimedia/2009/5169/0",
"title": "2009 IEEE/ACM/IFIP 7th Workshop on Embedded Systems for Real-Time Multimedia. ESTIMedia 2009",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ised/2011/4570/0/4570a158",
"title": "Addressing the Interoperability Issues While Using JPEG-XR",
"doi": null,
"abstractUrl": "/proceedings-article/ised/2011/4570a158/12OmNweTvPp",
"parentPublication": {
"id": "proceedings/ised/2011/4570/0",
"title": "2011 International Symposium on Electronic System Design",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2016/0842/0/07460055",
"title": "A schematic eye for virtual environments",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2016/07460055/12OmNx6xHsF",
"parentPublication": {
"id": "proceedings/3dui/2016/0842/0",
"title": "2016 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2011/4589/0/4589a319",
"title": "Affective Video Summarization and Story Board Generation Using Pupillary Dilation and Eye Gaze",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2011/4589a319/12OmNy4IF0d",
"parentPublication": {
"id": "proceedings/ism/2011/4589/0",
"title": "2011 IEEE International Symposium on Multimedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/5555/01/09907830",
"title": "DiOS - An Extended Reality Operating System for the Metaverse",
"doi": null,
"abstractUrl": "/magazine/mu/5555/01/09907830/1HbanLOikKs",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2023/4839/0/483900a067",
"title": "IEEE VR 2023 Workshop: Datasets for developing intelligent XR applications (DATA4XR)",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2023/483900a067/1N0wLk9I85W",
"parentPublication": {
"id": "proceedings/vrw/2023/4839/null",
"title": "2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300d694",
"title": "Eye Semantic Segmentation with A Lightweight Model",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300d694/1i5muSosJkk",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2020/6532/0/09090438",
"title": "XREye: Simulating Visual Impairments in Eye-Tracked XR",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2020/09090438/1jIxryb9Jkc",
"parentPublication": {
"id": "proceedings/vrw/2020/6532/0",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09382914",
"title": "A privacy-preserving approach to streaming eye-tracking data",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09382914/1saZw54tjDa",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412066",
"title": "Detection and Correspondence Matching of Corneal Reflections for Eye Tracking Using Deep Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412066/1tmjH1aA4dG",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "10049631",
"articleId": "1KYouFY43ks",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "10049700",
"articleId": "1KYoAxyw5c4",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNyq0zFI",
"title": "May",
"year": "2020",
"issueNum": "05",
"idPrefix": "tg",
"pubType": "journal",
"volume": "26",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1hrXiCmKkak",
"doi": "10.1109/TVCG.2020.2973064",
"abstract": "Today's Virtual Reality (VR) displays are dramatically better than the head-worn displays offered 30 years ago, but today's displays remain nearly as bulky as their predecessors in the 1980's. Also, almost all consumer VR displays today provide 90-110 degrees field of view (FOV), which is much smaller than the human visual system's FOV which extends beyond 180 degrees horizontally. In this paper, we propose ThinVR as a new approach to simultaneously address the bulk and limited FOV of head-worn VR displays. ThinVR enables a head-worn VR display to provide 180 degrees horizontal FOV in a thin, compact form factor. Our approach is to replace traditional large optics with a curved microlens array of custom-designed heterogeneous lenslets and place these in front of a curved display. We found that heterogeneous optics were crucial to make this approach work, since over a wide FOV, many lenslets are viewed off the central axis. We developed a custom optimizer for designing custom heterogeneous lenslets to ensure a sufficient eyebox while reducing distortions. The contribution includes an analysis of the design space for curved microlens arrays, implementation of physical prototypes, and an assessment of the image quality, eyebox, FOV, reduction in volume and pupil swim distortion. To our knowledge, this is the first work to demonstrate and analyze the potential for curved, heterogeneous microlens arrays to enable compact, wide FOV head-worn VR displays.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Today's Virtual Reality (VR) displays are dramatically better than the head-worn displays offered 30 years ago, but today's displays remain nearly as bulky as their predecessors in the 1980's. Also, almost all consumer VR displays today provide 90-110 degrees field of view (FOV), which is much smaller than the human visual system's FOV which extends beyond 180 degrees horizontally. In this paper, we propose ThinVR as a new approach to simultaneously address the bulk and limited FOV of head-worn VR displays. ThinVR enables a head-worn VR display to provide 180 degrees horizontal FOV in a thin, compact form factor. Our approach is to replace traditional large optics with a curved microlens array of custom-designed heterogeneous lenslets and place these in front of a curved display. We found that heterogeneous optics were crucial to make this approach work, since over a wide FOV, many lenslets are viewed off the central axis. We developed a custom optimizer for designing custom heterogeneous lenslets to ensure a sufficient eyebox while reducing distortions. The contribution includes an analysis of the design space for curved microlens arrays, implementation of physical prototypes, and an assessment of the image quality, eyebox, FOV, reduction in volume and pupil swim distortion. To our knowledge, this is the first work to demonstrate and analyze the potential for curved, heterogeneous microlens arrays to enable compact, wide FOV head-worn VR displays.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Today's Virtual Reality (VR) displays are dramatically better than the head-worn displays offered 30 years ago, but today's displays remain nearly as bulky as their predecessors in the 1980's. Also, almost all consumer VR displays today provide 90-110 degrees field of view (FOV), which is much smaller than the human visual system's FOV which extends beyond 180 degrees horizontally. In this paper, we propose ThinVR as a new approach to simultaneously address the bulk and limited FOV of head-worn VR displays. ThinVR enables a head-worn VR display to provide 180 degrees horizontal FOV in a thin, compact form factor. Our approach is to replace traditional large optics with a curved microlens array of custom-designed heterogeneous lenslets and place these in front of a curved display. We found that heterogeneous optics were crucial to make this approach work, since over a wide FOV, many lenslets are viewed off the central axis. We developed a custom optimizer for designing custom heterogeneous lenslets to ensure a sufficient eyebox while reducing distortions. The contribution includes an analysis of the design space for curved microlens arrays, implementation of physical prototypes, and an assessment of the image quality, eyebox, FOV, reduction in volume and pupil swim distortion. To our knowledge, this is the first work to demonstrate and analyze the potential for curved, heterogeneous microlens arrays to enable compact, wide FOV head-worn VR displays.",
"title": "ThinVR: Heterogeneous microlens arrays for compact, 180 degree FOV VR near-eye displays",
"normalizedTitle": "ThinVR: Heterogeneous microlens arrays for compact, 180 degree FOV VR near-eye displays",
"fno": "08998293",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Helmet Mounted Displays",
"Image Processing",
"Microlenses",
"Optical Arrays",
"Optical Design Techniques",
"Optical Distortion",
"Optical Images",
"Virtual Reality",
"Field Of View Virtual Reality Near Eye Displays",
"Wide Field Of View Head Worn Virtual Reality Displays",
"Compact Field Of View Head Worn Virtual Reality Displays",
"Curved Microlens Arrays",
"Curved Display",
"Custom Designed Heterogeneous Lenslets",
"Human Visual System",
"Heterogeneous Microlens Arrays",
"Lenses",
"Microoptics",
"Prototypes",
"Optical Imaging",
"Optical Diffraction",
"Optical Distortion",
"Computational Display",
"Lenslets",
"Wide Field Of View",
"Head Worn Display"
],
"authors": [
{
"givenName": "Joshua",
"surname": "Ratcliff",
"fullName": "Joshua Ratcliff",
"affiliation": "Intel Labs",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alexey",
"surname": "Supikov",
"fullName": "Alexey Supikov",
"affiliation": "Intel Labs",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Santiago",
"surname": "Alfaro",
"fullName": "Santiago Alfaro",
"affiliation": "Intel Labs",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ronald",
"surname": "Azuma",
"fullName": "Ronald Azuma",
"affiliation": "Intel Labs",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2020-05-01 00:00:00",
"pubType": "trans",
"pages": "1981-1990",
"year": "2020",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icisce/2016/2535/0/2535b449",
"title": "The Study of Optical Links Establishment with Ultra-Wide FOV Acquisition Scheme in FSO Network",
"doi": null,
"abstractUrl": "/proceedings-article/icisce/2016/2535b449/12OmNAJm0qq",
"parentPublication": {
"id": "proceedings/icisce/2016/2535/0",
"title": "2016 3rd International Conference on Information Science and Control Engineering (ICISCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2012/2216/0/06460264",
"title": "A visual marker for precise pose estimation based on a microlens array",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460264/12OmNC2OSLm",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/memsys/1997/3744/0/00581856",
"title": "Optical properties of a Si binary optic microlens for infrared ray",
"doi": null,
"abstractUrl": "/proceedings-article/memsys/1997/00581856/12OmNqC2uVO",
"parentPublication": {
"id": "proceedings/memsys/1997/3744/0",
"title": "Proceedings IEEE The Tenth Annual International Workshop on Micro Electro Mechanical Systems. An Investigation of Micro Structures, Sensors, Actuators, Machines and Robots",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a746",
"title": "Depth Reduction in Light-Field Head-Mounted Displays by Generating Intermediate Images as Virtual Images",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a746/1CJcGN8dsS4",
"parentPublication": {
"id": "proceedings/vrw/2022/8402/0",
"title": "2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/11/08827571",
"title": "Varifocal Occlusion-Capable Optical See-through Augmented Reality Display based on Focus-tunable Optics",
"doi": null,
"abstractUrl": "/journal/tg/2019/11/08827571/1dgvaPxmhbi",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2020/5608/0/09089608",
"title": "Angular Dependence of the Spatial Resolution in Virtual Reality Displays",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2020/09089608/1jIxaeEdNkc",
"parentPublication": {
"id": "proceedings/vr/2020/5608/0",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2020/8508/0/850800a301",
"title": "Super Wide-view Optical See-through Head Mounted Displays with Per-pixel Occlusion Capability",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2020/850800a301/1pysxIK95Yc",
"parentPublication": {
"id": "proceedings/ismar/2020/8508/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2020/8508/0/850800a312",
"title": "Towards Eyeglass-style Holographic Near-eye Displays with Statically",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2020/850800a312/1pysyaCOe76",
"parentPublication": {
"id": "proceedings/ismar/2020/8508/0",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09383112",
"title": "Beaming Displays",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09383112/1saZzKxYSqI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09384477",
"title": "Lenslet VR: Thin, Flat and Wide-FOV Virtual Reality Display Using Fresnel Lens and Lenslet Array",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09384477/1scDuWhBPY4",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09005240",
"articleId": "1hzNcOce8OQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08998301",
"articleId": "1hpPBqG2djy",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1iEfG202JeU",
"name": "ttg202005-08998293s1-tvcg-2973064-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202005-08998293s1-tvcg-2973064-mm.zip",
"extension": "zip",
"size": "66.8 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzcPAm0",
"title": "April-June",
"year": "2014",
"issueNum": "02",
"idPrefix": "th",
"pubType": "journal",
"volume": "7",
"label": "April-June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUNvyaf8",
"doi": "10.1109/TOH.2013.2297102",
"abstract": "Recent developments in neurorehabilitation have spawned numerous new robotic rehabilitation therapies. However, many of the concepts upon which these therapies are based are not fully understood and it may be necessary to explore some of the motor learning principles that apply to the use of haptics for motor learning in non-clinical scenarios/populations. We conducted a review of studies that utilized a haptic training paradigm teaching healthy participants to perform a motor skill involving the upper extremities. We discuss studies in the context of four important motor learning concepts: performance versus learning, feedback, observational learning, and functional task difficulty. Additionally, we note that the proliferation of research in haptic training has led to an extensive vocabulary of terms, some of which may be misnomers or redundant. We propose a classification of terms describing haptic training in an effort to provide clarity and further contextualize the studies. We believe that making connections to motor learning principles and clarifying meanings will facilitate a fuller understanding of the outcomes of studies in basic science research and allow for more directed applications of these training techniques to clinical populations.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recent developments in neurorehabilitation have spawned numerous new robotic rehabilitation therapies. However, many of the concepts upon which these therapies are based are not fully understood and it may be necessary to explore some of the motor learning principles that apply to the use of haptics for motor learning in non-clinical scenarios/populations. We conducted a review of studies that utilized a haptic training paradigm teaching healthy participants to perform a motor skill involving the upper extremities. We discuss studies in the context of four important motor learning concepts: performance versus learning, feedback, observational learning, and functional task difficulty. Additionally, we note that the proliferation of research in haptic training has led to an extensive vocabulary of terms, some of which may be misnomers or redundant. We propose a classification of terms describing haptic training in an effort to provide clarity and further contextualize the studies. We believe that making connections to motor learning principles and clarifying meanings will facilitate a fuller understanding of the outcomes of studies in basic science research and allow for more directed applications of these training techniques to clinical populations.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recent developments in neurorehabilitation have spawned numerous new robotic rehabilitation therapies. However, many of the concepts upon which these therapies are based are not fully understood and it may be necessary to explore some of the motor learning principles that apply to the use of haptics for motor learning in non-clinical scenarios/populations. We conducted a review of studies that utilized a haptic training paradigm teaching healthy participants to perform a motor skill involving the upper extremities. We discuss studies in the context of four important motor learning concepts: performance versus learning, feedback, observational learning, and functional task difficulty. Additionally, we note that the proliferation of research in haptic training has led to an extensive vocabulary of terms, some of which may be misnomers or redundant. We propose a classification of terms describing haptic training in an effort to provide clarity and further contextualize the studies. We believe that making connections to motor learning principles and clarifying meanings will facilitate a fuller understanding of the outcomes of studies in basic science research and allow for more directed applications of these training techniques to clinical populations.",
"title": "Motor Learning Perspectives on Haptic Training for the Upper Extremities",
"normalizedTitle": "Motor Learning Perspectives on Haptic Training for the Upper Extremities",
"fno": "06701132",
"hasPdf": true,
"idPrefix": "th",
"keywords": [
"Haptic Interfaces",
"Training",
"Robots",
"Trajectory",
"Context",
"Extremities",
"Medical Treatment",
"Review",
"Haptics",
"Motor Skill",
"Rehabilitation"
],
"authors": [
{
"givenName": "Camille K.",
"surname": "Williams",
"fullName": "Camille K. Williams",
"affiliation": "Dept. of Rehabilitation Sci., Univ. of Toronto, Toronto, ON, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Heather",
"surname": "Carnahan",
"fullName": "Heather Carnahan",
"affiliation": "Sch. of Human Kinetics & Recreation, Memorial Univ. of Newfoundland, St. John's, NL, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2014-04-01 00:00:00",
"pubType": "trans",
"pages": "240-250",
"year": "2014",
"issn": "1939-1412",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/haptics/2010/6821/0/05444635",
"title": "Effects of haptic guidance and disturbance on motor learning: Potential advantage of haptic disturbance",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2010/05444635/12OmNBtl1sT",
"parentPublication": {
"id": "proceedings/haptics/2010/6821/0",
"title": "2010 IEEE Haptics Symposium (Formerly known as Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/whc/2005/2310/0/23100452",
"title": "Motor Skill Training Assistance Using Haptic Attributes",
"doi": null,
"abstractUrl": "/proceedings-article/whc/2005/23100452/12OmNvlxJoQ",
"parentPublication": {
"id": "proceedings/whc/2005/2310/0",
"title": "Proceedings. First Joint Eurohaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems. World Haptics Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismarw/2016/3740/0/07836471",
"title": "A Haptic Serious Augmented Reality Game for Motor Assessment of Parkinson's Disease Patients",
"doi": null,
"abstractUrl": "/proceedings-article/ismarw/2016/07836471/12OmNwFidfy",
"parentPublication": {
"id": "proceedings/ismarw/2016/3740/0",
"title": "2016 IEEE International Symposium on Mixed and Augmented Reality (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2010/6821/0/05444622",
"title": "ReFlex, a haptic wrist interface for motor learning and rehabilitation",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2010/05444622/12OmNyp9MpL",
"parentPublication": {
"id": "proceedings/haptics/2010/6821/0",
"title": "2010 IEEE Haptics Symposium (Formerly known as Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2008/2005/0/04479929",
"title": "Validating the Performance of Haptic Motor Skill Training",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2008/04479929/12OmNz5apNY",
"parentPublication": {
"id": "proceedings/haptics/2008/2005/0",
"title": "IEEE Haptics Symposium 2008",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2015/04/07105411",
"title": "Learning of Temporal and Spatial Movement Aspects: A Comparison of Four Types of Haptic Control and Concurrent Visual Feedback",
"doi": null,
"abstractUrl": "/journal/th/2015/04/07105411/13rRUB6Sq0I",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2014/02/06613475",
"title": "Design and Development of an Affordable Haptic Robot with Force-Feedback and Compliant Actuation to Improve Therapy for Patients with Severe Hemiparesis",
"doi": null,
"abstractUrl": "/journal/th/2014/02/06613475/13rRUILtJzD",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2014/02/06710112",
"title": "Effects of Kinesthetic and Cutaneous Stimulation During the Learning of a Viscous Force Field",
"doi": null,
"abstractUrl": "/journal/th/2014/02/06710112/13rRUNvgz4r",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2016/02/07378499",
"title": "Movement Strategy Discovery during Training via Haptic Guidance",
"doi": null,
"abstractUrl": "/journal/th/2016/02/07378499/13rRUxBa5xt",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2015/02/06967807",
"title": "The Effect of Haptic Guidance on Learning a Hybrid Rhythmic-Discrete Motor Task",
"doi": null,
"abstractUrl": "/journal/th/2015/02/06967807/13rRUxcKzVq",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06671609",
"articleId": "13rRUxASuGo",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06710112",
"articleId": "13rRUNvgz4r",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNC8uRnx",
"title": "April-June",
"year": "2015",
"issueNum": "02",
"idPrefix": "th",
"pubType": "journal",
"volume": "8",
"label": "April-June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxcKzVq",
"doi": "10.1109/TOH.2014.2375173",
"abstract": "Bouncing a ball with a racket is a hybrid rhythmic-discrete motor task, combining continuous rhythmic racket movements with discrete impact events. Rhythmicity is exceptionally important in motor learning, because it underlies fundamental movements such as walking. Studies suggested that rhythmic and discrete movements are governed by different control mechanisms at different levels of the Central Nervous System. The aim of this study is to evaluate the effect of fixed/fading haptic guidance on learning to bounce a ball to a desired apex in virtual reality with varying gravity. Changing gravity changes dominance of rhythmic versus discrete control: The higher the value of gravity, the more rhythmic the task; lower values reduce the bouncing frequency and increase dwell times, eventually leading to a repetitive discrete task that requires initiation and termination, resembling target-oriented reaching. Although motor learning in the ball-bouncing task with varying gravity has been studied, the effect of haptic guidance on learning such a hybrid rhythmic-discrete motor task has not been addressed. We performed an experiment with thirty healthy subjects and found that the most effective training condition depended on the degree of rhythmicity: Haptic guidance seems to hamper learning of continuous rhythmic tasks, but it seems to promote learning for repetitive tasks that resemble discrete movements.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Bouncing a ball with a racket is a hybrid rhythmic-discrete motor task, combining continuous rhythmic racket movements with discrete impact events. Rhythmicity is exceptionally important in motor learning, because it underlies fundamental movements such as walking. Studies suggested that rhythmic and discrete movements are governed by different control mechanisms at different levels of the Central Nervous System. The aim of this study is to evaluate the effect of fixed/fading haptic guidance on learning to bounce a ball to a desired apex in virtual reality with varying gravity. Changing gravity changes dominance of rhythmic versus discrete control: The higher the value of gravity, the more rhythmic the task; lower values reduce the bouncing frequency and increase dwell times, eventually leading to a repetitive discrete task that requires initiation and termination, resembling target-oriented reaching. Although motor learning in the ball-bouncing task with varying gravity has been studied, the effect of haptic guidance on learning such a hybrid rhythmic-discrete motor task has not been addressed. We performed an experiment with thirty healthy subjects and found that the most effective training condition depended on the degree of rhythmicity: Haptic guidance seems to hamper learning of continuous rhythmic tasks, but it seems to promote learning for repetitive tasks that resemble discrete movements.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Bouncing a ball with a racket is a hybrid rhythmic-discrete motor task, combining continuous rhythmic racket movements with discrete impact events. Rhythmicity is exceptionally important in motor learning, because it underlies fundamental movements such as walking. Studies suggested that rhythmic and discrete movements are governed by different control mechanisms at different levels of the Central Nervous System. The aim of this study is to evaluate the effect of fixed/fading haptic guidance on learning to bounce a ball to a desired apex in virtual reality with varying gravity. Changing gravity changes dominance of rhythmic versus discrete control: The higher the value of gravity, the more rhythmic the task; lower values reduce the bouncing frequency and increase dwell times, eventually leading to a repetitive discrete task that requires initiation and termination, resembling target-oriented reaching. Although motor learning in the ball-bouncing task with varying gravity has been studied, the effect of haptic guidance on learning such a hybrid rhythmic-discrete motor task has not been addressed. We performed an experiment with thirty healthy subjects and found that the most effective training condition depended on the degree of rhythmicity: Haptic guidance seems to hamper learning of continuous rhythmic tasks, but it seems to promote learning for repetitive tasks that resemble discrete movements.",
"title": "The Effect of Haptic Guidance on Learning a Hybrid Rhythmic-Discrete Motor Task",
"normalizedTitle": "The Effect of Haptic Guidance on Learning a Hybrid Rhythmic-Discrete Motor Task",
"fno": "06967807",
"hasPdf": true,
"idPrefix": "th",
"keywords": [
"Gravity",
"Haptic Interfaces",
"Robots",
"Trajectory",
"Training",
"Elbow",
"Fading",
"Hybrid Rhythmic Discrete Task",
"Haptic Guidance",
"Fading Guidance",
"Motor Learning"
],
"authors": [
{
"givenName": "Laura",
"surname": "Marchal-Crespo",
"fullName": "Laura Marchal-Crespo",
"affiliation": "Sensory-Motor Syst. (SMS) Lab., ETH Zurich, Zurich, Switzerland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mathias",
"surname": "Bannwart",
"fullName": "Mathias Bannwart",
"affiliation": "Inst. of Neuroinf. (INI), ETH Zurich, Zurich, Switzerland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Robert",
"surname": "Riener",
"fullName": "Robert Riener",
"affiliation": "Sensory-Motor Syst. (SMS) Lab., ETH Zurich, Zurich, Switzerland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Heike",
"surname": "Vallery",
"fullName": "Heike Vallery",
"affiliation": "Sensory-Motor Syst. (SMS) Lab., ETH Zurich, Zurich, Switzerland",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2015-04-01 00:00:00",
"pubType": "trans",
"pages": "222-234",
"year": "2015",
"issn": "1939-1412",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/haptics/2002/1489/0/14890159",
"title": "Development of a Wearable Haptic Display for Situation Awareness in Altered-gravity Environment: Some Initial Findings",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2002/14890159/12OmNAlvHub",
"parentPublication": {
"id": "proceedings/haptics/2002/1489/0",
"title": "Haptic Interfaces for Virtual Environment and Teleoperator Systems, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2010/6821/0/05444635",
"title": "Effects of haptic guidance and disturbance on motor learning: Potential advantage of haptic disturbance",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2010/05444635/12OmNBtl1sT",
"parentPublication": {
"id": "proceedings/haptics/2010/6821/0",
"title": "2010 IEEE Haptics Symposium (Formerly known as Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2008/2005/0/04479984",
"title": "Haptic Guidance Benefits Musical Motor Learning",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2008/04479984/12OmNButq3Q",
"parentPublication": {
"id": "proceedings/haptics/2008/2005/0",
"title": "IEEE Haptics Symposium 2008",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2008/2005/0/04479997",
"title": "Haptic Simulation of Elbow Joint Spasticity",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2008/04479997/12OmNqIQSin",
"parentPublication": {
"id": "proceedings/haptics/2008/2005/0",
"title": "IEEE Haptics Symposium 2008",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2006/0226/0/02260069",
"title": "Haptic Attributes and Human Motor Skills",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2006/02260069/12OmNvSKNDj",
"parentPublication": {
"id": "proceedings/haptics/2006/0226/0",
"title": "2006 14th Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2010/6821/0/05444678",
"title": "Haptic illusion of elasticity by tactile suppression during motor activity",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2010/05444678/12OmNwc3wtY",
"parentPublication": {
"id": "proceedings/haptics/2010/6821/0",
"title": "2010 IEEE Haptics Symposium (Formerly known as Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2008/2005/0/04479929",
"title": "Validating the Performance of Haptic Motor Skill Training",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2008/04479929/12OmNz5apNY",
"parentPublication": {
"id": "proceedings/haptics/2008/2005/0",
"title": "IEEE Haptics Symposium 2008",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2014/02/06701132",
"title": "Motor Learning Perspectives on Haptic Training for the Upper Extremities",
"doi": null,
"abstractUrl": "/journal/th/2014/02/06701132/13rRUNvyaf8",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2016/02/07378499",
"title": "Movement Strategy Discovery during Training via Haptic Guidance",
"doi": null,
"abstractUrl": "/journal/th/2016/02/07378499/13rRUxBa5xt",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2016/03/07412776",
"title": "Rhythmic Haptic Stimuli Improve Short-Term Attention",
"doi": null,
"abstractUrl": "/journal/th/2016/03/07412776/13rRUypp57L",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07027232",
"articleId": "13rRUx0geA3",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07102756",
"articleId": "13rRUy3gn7G",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwMob9A",
"title": "July-Sept.",
"year": "2017",
"issueNum": "03",
"idPrefix": "lt",
"pubType": "journal",
"volume": "10",
"label": "July-Sept.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUyY2919",
"doi": "10.1109/TLT.2016.2599537",
"abstract": "In the past few decades, simulation training has been used to help nurses improve their patient-transfer skills. However, the effectiveness of such training remains limited because it lacks effective ways of simulating patients’ actions realistically. It is difficult for nurses to use the skills learned from simulation training to transfer an actual patient. Therefore, we developed a robot patient that could simulate the behavior of patients’ limbs for patient-transfer training. This study examined the performance of the robot used in training and evaluated its training effectiveness. Four nursing teachers individually transferred the robot patient and then scored the robot patient's ability to simulate patients’ actions and its suitability for skill training. An experiment using pre-post control group design was carried out to examine the robot patient's training effectiveness compared with the human simulated patient. The participants were 20 nursing students and one nursing teacher who was responsible for scoring the students’ skills in the pre-test and post-test. All of the students were assigned to train with either the proposed robot patient or a healthy person simulating the patient. The results show that all four nursing teachers regarded the robot patient's actions as realistic. In addition, all four teachers agreed that the robot patient was suitable for skill training. The results also show that the proposed robot patient is more challenging than the current method, which employs a healthy person to simulate the patient. Significant skill improvement (p < 0.01) was observed in the experimental group when transferring the robot patient.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In the past few decades, simulation training has been used to help nurses improve their patient-transfer skills. However, the effectiveness of such training remains limited because it lacks effective ways of simulating patients’ actions realistically. It is difficult for nurses to use the skills learned from simulation training to transfer an actual patient. Therefore, we developed a robot patient that could simulate the behavior of patients’ limbs for patient-transfer training. This study examined the performance of the robot used in training and evaluated its training effectiveness. Four nursing teachers individually transferred the robot patient and then scored the robot patient's ability to simulate patients’ actions and its suitability for skill training. An experiment using pre-post control group design was carried out to examine the robot patient's training effectiveness compared with the human simulated patient. The participants were 20 nursing students and one nursing teacher who was responsible for scoring the students’ skills in the pre-test and post-test. All of the students were assigned to train with either the proposed robot patient or a healthy person simulating the patient. The results show that all four nursing teachers regarded the robot patient's actions as realistic. In addition, all four teachers agreed that the robot patient was suitable for skill training. The results also show that the proposed robot patient is more challenging than the current method, which employs a healthy person to simulate the patient. Significant skill improvement (p < 0.01) was observed in the experimental group when transferring the robot patient.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In the past few decades, simulation training has been used to help nurses improve their patient-transfer skills. However, the effectiveness of such training remains limited because it lacks effective ways of simulating patients’ actions realistically. It is difficult for nurses to use the skills learned from simulation training to transfer an actual patient. Therefore, we developed a robot patient that could simulate the behavior of patients’ limbs for patient-transfer training. This study examined the performance of the robot used in training and evaluated its training effectiveness. Four nursing teachers individually transferred the robot patient and then scored the robot patient's ability to simulate patients’ actions and its suitability for skill training. An experiment using pre-post control group design was carried out to examine the robot patient's training effectiveness compared with the human simulated patient. The participants were 20 nursing students and one nursing teacher who was responsible for scoring the students’ skills in the pre-test and post-test. All of the students were assigned to train with either the proposed robot patient or a healthy person simulating the patient. The results show that all four nursing teachers regarded the robot patient's actions as realistic. In addition, all four teachers agreed that the robot patient was suitable for skill training. The results also show that the proposed robot patient is more challenging than the current method, which employs a healthy person to simulate the patient. Significant skill improvement (p < 0.01) was observed in the experimental group when transferring the robot patient.",
"title": "Impact of Using a Robot Patient for Nursing Skill Training in Patient Transfer",
"normalizedTitle": "Impact of Using a Robot Patient for Nursing Skill Training in Patient Transfer",
"fno": "07542122",
"hasPdf": true,
"idPrefix": "lt",
"keywords": [
"Training",
"Medical Services",
"Mobile Robots",
"Wheelchairs",
"Servomotors",
"Haptic Interfaces",
"Computer Uses In Education",
"Educational Technology",
"Training",
"Robot Patient"
],
"authors": [
{
"givenName": "Zhifeng",
"surname": "Huang",
"fullName": "Zhifeng Huang",
"affiliation": "School of Automation, Guangdong University of Technology, Guangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chingszu",
"surname": "Lin",
"fullName": "Chingszu Lin",
"affiliation": "Research into Artifacts, Center for Engineering (RACE), University of Tokyo, Chiba, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Masako",
"surname": "Kanai-Pak",
"fullName": "Masako Kanai-Pak",
"affiliation": "Faculty of Nursing, Tokyo Ariake University of Medical and Health Sciences, Tokyo, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jukai",
"surname": "Maeda",
"fullName": "Jukai Maeda",
"affiliation": "Faculty of Nursing, Tokyo Ariake University of Medical and Health Sciences, Tokyo, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yasuko",
"surname": "Kitajima",
"fullName": "Yasuko Kitajima",
"affiliation": "Faculty of Nursing, Tokyo Ariake University of Medical and Health Sciences, Tokyo, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mitsuhiro",
"surname": "Nakamura",
"fullName": "Mitsuhiro Nakamura",
"affiliation": "Faculty of Nursing, Tokyo Ariake University of Medical and Health Sciences, Tokyo, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Noriaki",
"surname": "Kuwahara",
"fullName": "Noriaki Kuwahara",
"affiliation": "Department of Advanced Fibro-Science, Kyoto Institute of Technology, Kyoto, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Taiki",
"surname": "Ogata",
"fullName": "Taiki Ogata",
"affiliation": "Research into Artifacts, Center for Engineering (RACE), University of Tokyo, Chiba, Japan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jun",
"surname": "Ota",
"fullName": "Jun Ota",
"affiliation": "Research into Artifacts, Center for Engineering (RACE), University of Tokyo, Chiba, Japan",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "03",
"pubDate": "2017-07-01 00:00:00",
"pubType": "trans",
"pages": "355-366",
"year": "2017",
"issn": "1939-1382",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/eitt/2017/0629/0/0629a159",
"title": "Changes in Subjective Understanding of an Accident and Risk Awareness in First-Year Nursing Students Following Medical Accident Simulation-Based Experimental Learning",
"doi": null,
"abstractUrl": "/proceedings-article/eitt/2017/0629a159/12OmNBQkwYr",
"parentPublication": {
"id": "proceedings/eitt/2017/0629/0",
"title": "2017 International Conference of Educational Innovation through Technology (EITT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rvsp/2013/3184/0/3184a247",
"title": "Android Patient Robot Simulating Depressed Patients for Diagnosis Training of Psychiatric Trainees",
"doi": null,
"abstractUrl": "/proceedings-article/rvsp/2013/3184a247/12OmNrJRPiL",
"parentPublication": {
"id": "proceedings/rvsp/2013/3184/0",
"title": "2013 Second International Conference on Robot, Vision and Signal Processing (RVSP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbms/1992/2742/0/00244945",
"title": "Nursing workload management for a patient data management system",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/1992/00244945/12OmNvjQ8VJ",
"parentPublication": {
"id": "proceedings/cbms/1992/2742/0",
"title": "Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icisa/2010/5942/0/05480413",
"title": "Graphic Visualization of the Co-Occurrence Analysis Network of Lung Cancer In-Patient Nursing Record",
"doi": null,
"abstractUrl": "/proceedings-article/icisa/2010/05480413/12OmNwMXnne",
"parentPublication": {
"id": "proceedings/icisa/2010/5942/0",
"title": "2010 International Conference on Information Science and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2014/02/06613475",
"title": "Design and Development of an Affordable Haptic Robot with Force-Feedback and Compliant Actuation to Improve Therapy for Patients with Severe Hemiparesis",
"doi": null,
"abstractUrl": "/journal/th/2014/02/06613475/13rRUILtJzD",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icict/2022/6960/0/696000a153",
"title": "Mixed reality (MR) Enabled Proprio and Teleoperation of a Humanoid Robot for Paraplegic Patients",
"doi": null,
"abstractUrl": "/proceedings-article/icict/2022/696000a153/1FJ5bdmciJO",
"parentPublication": {
"id": "proceedings/icict/2022/6960/0",
"title": "2022 5th International Conference on Information and Computer Technologies (ICICT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2019/2165/0/216500a561",
"title": "Research on Application of Information System to Nursing Management",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2019/216500a561/1dUnR4EQaE8",
"parentPublication": {
"id": "proceedings/icmtma/2019/2165/0",
"title": "2019 11th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2020/7081/0/708100a770",
"title": "Research on Nursing Management Based on Big Data",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2020/708100a770/1iEREt5m9uo",
"parentPublication": {
"id": "proceedings/icmtma/2020/7081/0",
"title": "2020 12th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2020/5382/0/09374306",
"title": "Comparison between a Continuous and Proactive Robot Assistance Approach for the Execution of Collaborative Tasks in Nursing Care",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2020/09374306/1rUJ2tkYGn6",
"parentPublication": {
"id": "proceedings/ichi/2020/5382/0",
"title": "2020 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iciddt/2020/0367/0/036700a049",
"title": "Design of an intelligent desktop nursing dual-arm robot based on FAST and TRIZ",
"doi": null,
"abstractUrl": "/proceedings-article/iciddt/2020/036700a049/1wutKasToR2",
"parentPublication": {
"id": "proceedings/iciddt/2020/0367/0",
"title": "2020 International Conference on Innovation Design and Digital Technology (ICIDDT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07755754",
"articleId": "13rRUxE04q3",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07496957",
"articleId": "13rRUwbs2d6",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1HGJ6XQen96",
"title": "Nov.",
"year": "2022",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1GhRV18KGvC",
"doi": "10.1109/TVCG.2022.3203100",
"abstract": "Current methods for segmenting eye imagery into skin, sclera, pupil, and iris cannot leverage information about eye motion. This is because the datasets on which models are trained are limited to temporally non-contiguous frames. We present Temporal RIT-Eyes, a Blender pipeline that draws data from real eye videos for the rendering of synthetic imagery depicting natural gaze dynamics. These sequences are accompanied by ground-truth segmentation maps that may be used for training image-segmentation networks. Temporal RIT-Eyes relies on a novel method for the extraction of 3D eyelid pose (top and bottom apex of eyelids/eyeball boundary) from raw eye images for the rendering of gaze-dependent eyelid pose and blink behavior. The pipeline is parameterized to vary in appearance, eye/head/camera/illuminant geometry, and environment settings (indoor/outdoor). We present two open-source datasets of synthetic eye imagery: sGiW is a set of synthetic-image sequences whose dynamics are modeled on those of the Gaze in Wild dataset, and sOpenEDS2 is a series of temporally non-contiguous eye images that approximate the OpenEDS-2019 dataset. We also analyze and demonstrate the quality of the rendered dataset qualitatively and show significant overlap between latent-space representations of the source and the rendered datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Current methods for segmenting eye imagery into skin, sclera, pupil, and iris cannot leverage information about eye motion. This is because the datasets on which models are trained are limited to temporally non-contiguous frames. We present Temporal RIT-Eyes, a Blender pipeline that draws data from real eye videos for the rendering of synthetic imagery depicting natural gaze dynamics. These sequences are accompanied by ground-truth segmentation maps that may be used for training image-segmentation networks. Temporal RIT-Eyes relies on a novel method for the extraction of 3D eyelid pose (top and bottom apex of eyelids/eyeball boundary) from raw eye images for the rendering of gaze-dependent eyelid pose and blink behavior. The pipeline is parameterized to vary in appearance, eye/head/camera/illuminant geometry, and environment settings (indoor/outdoor). We present two open-source datasets of synthetic eye imagery: sGiW is a set of synthetic-image sequences whose dynamics are modeled on those of the Gaze in Wild dataset, and sOpenEDS2 is a series of temporally non-contiguous eye images that approximate the OpenEDS-2019 dataset. We also analyze and demonstrate the quality of the rendered dataset qualitatively and show significant overlap between latent-space representations of the source and the rendered datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Current methods for segmenting eye imagery into skin, sclera, pupil, and iris cannot leverage information about eye motion. This is because the datasets on which models are trained are limited to temporally non-contiguous frames. We present Temporal RIT-Eyes, a Blender pipeline that draws data from real eye videos for the rendering of synthetic imagery depicting natural gaze dynamics. These sequences are accompanied by ground-truth segmentation maps that may be used for training image-segmentation networks. Temporal RIT-Eyes relies on a novel method for the extraction of 3D eyelid pose (top and bottom apex of eyelids/eyeball boundary) from raw eye images for the rendering of gaze-dependent eyelid pose and blink behavior. The pipeline is parameterized to vary in appearance, eye/head/camera/illuminant geometry, and environment settings (indoor/outdoor). We present two open-source datasets of synthetic eye imagery: sGiW is a set of synthetic-image sequences whose dynamics are modeled on those of the Gaze in Wild dataset, and sOpenEDS2 is a series of temporally non-contiguous eye images that approximate the OpenEDS-2019 dataset. We also analyze and demonstrate the quality of the rendered dataset qualitatively and show significant overlap between latent-space representations of the source and the rendered datasets.",
"title": ": From real infrared eye-images to synthetic sequences of gaze behavior<italic/>",
"normalizedTitle": ": From real infrared eye-images to synthetic sequences of gaze behavior",
"fno": "09872121",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Eye",
"Feature Extraction",
"Image Segmentation",
"Image Sequences",
"Rendering Computer Graphics",
"Video Signal Processing",
"Eye Motion",
"Eye Videos",
"Gaze Behavior",
"Gaze Dependent Eyelid Pose",
"Ground Truth Segmentation Maps",
"Infrared Eye Images",
"Natural Gaze Dynamics",
"Noncontiguous Eye Images",
"Noncontiguous Frames",
"Open Source Datasets",
"Open EDS 2019 Dataset",
"Raw Eye Images",
"Rendered Dataset",
"Rendering",
"Synthetic Eye Imagery",
"Synthetic Imagery",
"Synthetic Sequences",
"Synthetic Image Sequences",
"Temporal RIT Eyes",
"Training Image Segmentation Networks",
"Eyelids",
"Pupils",
"Rendering Computer Graphics",
"Image Segmentation",
"Three Dimensional Displays",
"Head",
"Behavioral Sciences",
"Eye Tracking",
"Image Segmentation",
"Synthetic Dataset",
"Temporal Dataset",
"Eye Rendering",
"Renderings For ML",
"AR VR"
],
"authors": [
{
"givenName": "Aayush K.",
"surname": "Chaudhary",
"fullName": "Aayush K. Chaudhary",
"affiliation": "Rochester Institute of Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nitinraj",
"surname": "Nair",
"fullName": "Nitinraj Nair",
"affiliation": "Rochester Institute of Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Reynold J.",
"surname": "Bailey",
"fullName": "Reynold J. Bailey",
"affiliation": "Rochester Institute of Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jeff B.",
"surname": "Pelz",
"fullName": "Jeff B. Pelz",
"affiliation": "Rochester Institute of Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sachin S.",
"surname": "Talathi",
"fullName": "Sachin S. Talathi",
"affiliation": "Reality Research Labs, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gabriel J.",
"surname": "Diaz",
"fullName": "Gabriel J. Diaz",
"affiliation": "Rochester Institute of Technology, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2022-11-01 00:00:00",
"pubType": "trans",
"pages": "3948-3958",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cse/2014/7981/0/7981a458",
"title": "Eye Detection for Gaze Tracker with Near Infrared Illuminator",
"doi": null,
"abstractUrl": "/proceedings-article/cse/2014/7981a458/12OmNx3q6Yv",
"parentPublication": {
"id": "proceedings/cse/2014/7981/0",
"title": "2014 IEEE 17th International Conference on Computational Science and Engineering (CSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2014/5118/0/5118b773",
"title": "Geometric Generative Gaze Estimation (G3E) for Remote RGB-D Cameras",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2014/5118b773/12OmNyKJipS",
"parentPublication": {
"id": "proceedings/cvpr/2014/5118/0",
"title": "2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2012/11/ttg2012111902",
"title": "Live Speech Driven Head-and-Eye Motion Generators",
"doi": null,
"abstractUrl": "/journal/tg/2012/11/ttg2012111902/13rRUyv53Fo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2018/7123/0/08493406",
"title": "A Model for Eye and Head Motion for Virtual Agents",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2018/08493406/14tNJoD4Uxi",
"parentPublication": {
"id": "proceedings/vs-games/2018/7123/0",
"title": "2018 10th International Conference on Virtual Worlds and Games for Serious Applications (VS-Games)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10044277",
"title": "Real-time Multi-map Saliency-driven Gaze Behavior for Non-conversational Characters",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10044277/1KL728MHdtu",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/5555/01/10076795",
"title": "A High-Quality Landmarked Infrared Eye Video Dataset (IREye4Task): Eye Behaviors, Insights and Benchmarks for Wearable Mental State Analysis",
"doi": null,
"abstractUrl": "/journal/ta/5555/01/10076795/1LFOIJwV6KI",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2021/03/08920005",
"title": "A Differential Approach for Gaze Estimation",
"doi": null,
"abstractUrl": "/journal/tp/2021/03/08920005/1fsFnejO2IM",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300e416",
"title": "Weakly-Supervised Degree of Eye-Closeness Estimation",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300e416/1i5msGHDmec",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093433",
"title": "EyeGAN: Gaze–Preserving, Mask–Mediated Eye Image Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093433/1jPbyYn40WA",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09389490",
"title": "Event-Based Near-Eye Gaze Tracking Beyond 10,000 Hz",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09389490/1smZT5W55V6",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09872143",
"articleId": "1GhRXEVRVZK",
"__typename": "AdjacentArticleType"
},
"next": null,
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1HGJcvTcpRm",
"name": "ttg202211-09872121s1-supp1-3203100.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202211-09872121s1-supp1-3203100.mp4",
"extension": "mp4",
"size": "93.9 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1p1cntpQSWc",
"title": "Jan.",
"year": "2021",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1cRBtd0YTN6",
"doi": "10.1109/TVCG.2019.2938165",
"abstract": "This paper presents a realtime and accurate method for 3D eye gaze tracking with a monocular RGB camera. Our key idea is to train a deep convolutional neural network(DCNN) that automatically extracts the iris and pupil pixels of each eye from input images. To achieve this goal, we combine the power of Unet [1] and Squeezenet [2] to train an efficient convolutional neural network for pixel classification. In addition, we track the 3D eye gaze state in the Maximum A Posteriori (MAP) framework, which sequentially searches for the most likely state of the 3D eye gaze at each frame. When eye blinking occurs, the eye gaze tracker can obtain an inaccurate result. We further extend the convolutional neural network for eye close detection in order to improve the robustness and accuracy of the eye gaze tracker. Our system runs in realtime on desktop PCs and smart phones. We have evaluated our system on live videos and Internet videos, and our results demonstrate that the system is robust and accurate for various genders, races, lighting conditions, poses, shapes and facial expressions. A comparison against Wang et al. [3] shows that our method advances the state of the art in 3D eye tracking using a single RGB camera.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents a realtime and accurate method for 3D eye gaze tracking with a monocular RGB camera. Our key idea is to train a deep convolutional neural network(DCNN) that automatically extracts the iris and pupil pixels of each eye from input images. To achieve this goal, we combine the power of Unet [1] and Squeezenet [2] to train an efficient convolutional neural network for pixel classification. In addition, we track the 3D eye gaze state in the Maximum A Posteriori (MAP) framework, which sequentially searches for the most likely state of the 3D eye gaze at each frame. When eye blinking occurs, the eye gaze tracker can obtain an inaccurate result. We further extend the convolutional neural network for eye close detection in order to improve the robustness and accuracy of the eye gaze tracker. Our system runs in realtime on desktop PCs and smart phones. We have evaluated our system on live videos and Internet videos, and our results demonstrate that the system is robust and accurate for various genders, races, lighting conditions, poses, shapes and facial expressions. A comparison against Wang et al. [3] shows that our method advances the state of the art in 3D eye tracking using a single RGB camera.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents a realtime and accurate method for 3D eye gaze tracking with a monocular RGB camera. Our key idea is to train a deep convolutional neural network(DCNN) that automatically extracts the iris and pupil pixels of each eye from input images. To achieve this goal, we combine the power of Unet [1] and Squeezenet [2] to train an efficient convolutional neural network for pixel classification. In addition, we track the 3D eye gaze state in the Maximum A Posteriori (MAP) framework, which sequentially searches for the most likely state of the 3D eye gaze at each frame. When eye blinking occurs, the eye gaze tracker can obtain an inaccurate result. We further extend the convolutional neural network for eye close detection in order to improve the robustness and accuracy of the eye gaze tracker. Our system runs in realtime on desktop PCs and smart phones. We have evaluated our system on live videos and Internet videos, and our results demonstrate that the system is robust and accurate for various genders, races, lighting conditions, poses, shapes and facial expressions. A comparison against Wang et al. [3] shows that our method advances the state of the art in 3D eye tracking using a single RGB camera.",
"title": "Realtime and Accurate 3D Eye Gaze Capture with DCNN-Based Iris and Pupil Segmentation",
"normalizedTitle": "Realtime and Accurate 3D Eye Gaze Capture with DCNN-Based Iris and Pupil Segmentation",
"fno": "08818661",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Cameras",
"Convolutional Neural Nets",
"Eye",
"Face Recognition",
"Feature Extraction",
"Gaze Tracking",
"Image Capture",
"Image Classification",
"Image Colour Analysis",
"Image Segmentation",
"Iris Recognition",
"Maximum Likelihood Estimation",
"Object Detection",
"Object Tracking",
"Video Signal Processing",
"Pupil Pixels",
"Eye Blinking",
"Deep Convolutional Neural Network",
"Eye Gaze Tracker",
"Realtime 3 D Eye Gaze Capture",
"DCNN",
"Iris Segmentation",
"Pupil Segmentation",
"Monocular RGB Camera",
"Iris Extraction",
"Unet",
"Squeezenet",
"Pixel Classification",
"Maximum A Posteriori",
"Eye Close Detection",
"Desktop PC",
"Smart Phone",
"Live Videos",
"Internet Videos",
"Three Dimensional Displays",
"Gaze Tracking",
"Iris",
"Cameras",
"Convolutional Neural Nets",
"Image Reconstruction",
"Videos",
"3 D Eye Gaze Tracking",
"Convolutional Neural Network",
"Facial Capture"
],
"authors": [
{
"givenName": "Zhiyong",
"surname": "Wang",
"fullName": "Zhiyong Wang",
"affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jinxiang",
"surname": "Chai",
"fullName": "Jinxiang Chai",
"affiliation": "Texas A&M University, College Station, TX, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shihong",
"surname": "Xia",
"fullName": "Shihong Xia",
"affiliation": "Beijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2021-01-01 00:00:00",
"pubType": "trans",
"pages": "190-203",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/gcis/2009/3571/2/3571b133",
"title": "Key Techniques of Eye Gaze Tracking Based on Pupil Corneal Reflection",
"doi": null,
"abstractUrl": "/proceedings-article/gcis/2009/3571b133/12OmNA0vo1q",
"parentPublication": {
"id": "proceedings/gcis/2009/3571/2",
"title": "2009 WRI Global Congress on Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2011/0394/0/05995675",
"title": "Probabilistic gaze estimation without active personal calibration",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2011/05995675/12OmNC8MsAV",
"parentPublication": {
"id": "proceedings/cvpr/2011/0394/0",
"title": "CVPR 2011",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209b156",
"title": "Gaze Estimation Based on 3D Face Structure and Pupil Centers",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209b156/12OmNvCi45y",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2014/4761/0/06890322",
"title": "Realtime gaze estimation with online calibration",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2014/06890322/12OmNvjyxUU",
"parentPublication": {
"id": "proceedings/icme/2014/4761/0",
"title": "2014 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2013/5053/0/06475042",
"title": "Unwrapping the eye for visible-spectrum gaze tracking on wearable devices",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2013/06475042/12OmNwE9OwM",
"parentPublication": {
"id": "proceedings/wacv/2013/5053/0",
"title": "Applications of Computer Vision, IEEE Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icoip/2010/4252/1/4252a131",
"title": "A Simplified 3D Gaze Tracking Technology with Stereo Vision",
"doi": null,
"abstractUrl": "/proceedings-article/icoip/2010/4252a131/12OmNwqft0F",
"parentPublication": {
"id": "proceedings/icoip/2010/4252/2",
"title": "Optoelectronics and Image Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/05/08643434",
"title": "SGaze: A Data-Driven Eye-Head Coordination Model for Realtime Gaze Prediction",
"doi": null,
"abstractUrl": "/journal/tg/2019/05/08643434/18K0lRIKi7m",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2022/5325/0/532500a375",
"title": "Neural 3D Gaze: 3D Pupil Localization and Gaze Tracking based on Anatomical Eye Model and Neural Refraction Correction",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2022/532500a375/1JrQRCijhMk",
"parentPublication": {
"id": "proceedings/ismar/2022/5325/0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ithings-greencom-cpscom-smartdata/2019/2980/0/298000a655",
"title": "A Multi-Modal Gaze Tracking Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/ithings-greencom-cpscom-smartdata/2019/298000a655/1ehBL8sk06I",
"parentPublication": {
"id": "proceedings/ithings-greencom-cpscom-smartdata/2019/2980/0",
"title": "2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2021/0158/0/015800a367",
"title": "TEyeD: Over 20 Million Real-World Eye Images with Pupil, Eyelid, and Iris 2D and 3D Segmentations, 2D and 3D Landmarks, 3D Eyeball, Gaze Vector, and Eye Movement Types",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2021/015800a367/1yeD3XlUpBS",
"parentPublication": {
"id": "proceedings/ismar/2021/0158/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08771128",
"articleId": "1bVvOZfToJy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08758372",
"articleId": "1bwCk2J4N7q",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvSbBJI",
"title": "August",
"year": "2008",
"issueNum": "08",
"idPrefix": "tp",
"pubType": "journal",
"volume": "30",
"label": "August",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUNvPLaM",
"doi": "10.1109/TPAMI.2007.70797",
"abstract": "We propose a new two-stage framework for joint analysis of head gesture and speech prosody patterns of a speaker towards automatic realistic synthesis of head gestures from speech prosody. In the first stage analysis, we perform Hidden Markov Model (HMM) based unsupervised temporal segmentation of head gesture and speech prosody features separately to determine elementary head gesture and speech prosody patterns, respectively, for a particular speaker. In the second stage, joint analysis of correlations between these elementary head gesture and prosody patterns is performed using Multi-Stream HMMs to determine an audio-visual mapping model. The resulting audio-visual mapping model is then employed to synthesize natural head gestures from arbitrary input test speech given a head model for the speaker. In the synthesis stage, the audio-visual mapping model is used to predict a sequence of gesture patterns from the prosody pattern sequence computed for the input test speech. The Euler angles associated with each gesture pattern are then applied to animate the speaker head model. Objective and subjective evaluations indicate that the proposed synthesis by analysis scheme provides natural looking head gestures for the speaker with any input test speech, as well as in ``prosody transplant\" and ``gesture transplant\" scenarios.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose a new two-stage framework for joint analysis of head gesture and speech prosody patterns of a speaker towards automatic realistic synthesis of head gestures from speech prosody. In the first stage analysis, we perform Hidden Markov Model (HMM) based unsupervised temporal segmentation of head gesture and speech prosody features separately to determine elementary head gesture and speech prosody patterns, respectively, for a particular speaker. In the second stage, joint analysis of correlations between these elementary head gesture and prosody patterns is performed using Multi-Stream HMMs to determine an audio-visual mapping model. The resulting audio-visual mapping model is then employed to synthesize natural head gestures from arbitrary input test speech given a head model for the speaker. In the synthesis stage, the audio-visual mapping model is used to predict a sequence of gesture patterns from the prosody pattern sequence computed for the input test speech. The Euler angles associated with each gesture pattern are then applied to animate the speaker head model. Objective and subjective evaluations indicate that the proposed synthesis by analysis scheme provides natural looking head gestures for the speaker with any input test speech, as well as in ``prosody transplant\" and ``gesture transplant\" scenarios.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose a new two-stage framework for joint analysis of head gesture and speech prosody patterns of a speaker towards automatic realistic synthesis of head gestures from speech prosody. In the first stage analysis, we perform Hidden Markov Model (HMM) based unsupervised temporal segmentation of head gesture and speech prosody features separately to determine elementary head gesture and speech prosody patterns, respectively, for a particular speaker. In the second stage, joint analysis of correlations between these elementary head gesture and prosody patterns is performed using Multi-Stream HMMs to determine an audio-visual mapping model. The resulting audio-visual mapping model is then employed to synthesize natural head gestures from arbitrary input test speech given a head model for the speaker. In the synthesis stage, the audio-visual mapping model is used to predict a sequence of gesture patterns from the prosody pattern sequence computed for the input test speech. The Euler angles associated with each gesture pattern are then applied to animate the speaker head model. Objective and subjective evaluations indicate that the proposed synthesis by analysis scheme provides natural looking head gestures for the speaker with any input test speech, as well as in ``prosody transplant\" and ``gesture transplant\" scenarios.",
"title": "Analysis of Head Gesture and Prosody Patterns for Prosody-Driven Head-Gesture Animation",
"normalizedTitle": "Analysis of Head Gesture and Prosody Patterns for Prosody-Driven Head-Gesture Animation",
"fno": "ttp2008081330",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Audio Input Output",
"Face And Gesture Recognition",
"Pattern Analysis"
],
"authors": [
{
"givenName": "Mehmet E.",
"surname": "Sargin",
"fullName": "Mehmet E. Sargin",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yucel",
"surname": "Yemez",
"fullName": "Yucel Yemez",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Engin",
"surname": "Erzin",
"fullName": "Engin Erzin",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ahmet M.",
"surname": "Tekalp",
"fullName": "Ahmet M. Tekalp",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2008-08-01 00:00:00",
"pubType": "trans",
"pages": "1330-1345",
"year": "2008",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ozchi/1998/9206/0/92060006",
"title": "Integrating Speech and Two-Dimensional Gesture Input - A Study of Redundancy between Modes",
"doi": null,
"abstractUrl": "/proceedings-article/ozchi/1998/92060006/12OmNBfZSmg",
"parentPublication": {
"id": "proceedings/ozchi/1998/9206/0",
"title": "Computer-Human Interaction, Australasian Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/kse/2012/4760/0/4760a151",
"title": "A Study on Prosody of Vietnamese Emotional Speech",
"doi": null,
"abstractUrl": "/proceedings-article/kse/2012/4760a151/12OmNBiPRBv",
"parentPublication": {
"id": "proceedings/kse/2012/4760/0",
"title": "Knowledge and Systems Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2000/0580/0/05800422",
"title": "Exploiting Speech/Gesture Co-occurrence for Improving Continuous Gesture Recognition in Weather Narration",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2000/05800422/12OmNCwUmBP",
"parentPublication": {
"id": "proceedings/fg/2000/0580/0",
"title": "Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cmvit/2017/4993/0/07878718",
"title": "Head Gesture Recognition Based on SAE",
"doi": null,
"abstractUrl": "/proceedings-article/cmvit/2017/07878718/12OmNvxKu48",
"parentPublication": {
"id": "proceedings/cmvit/2017/4993/0",
"title": "2017 International Conference on Machine Vision and Information Technology (CMVIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2002/1602/0/16020396",
"title": "Visual Prosody: Facial Movements Accompanying Speech",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2002/16020396/12OmNwkzusE",
"parentPublication": {
"id": "proceedings/fg/2002/1602/0",
"title": "Proceedings of Fifth IEEE International Conference on Automatic Face Gesture Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2015/7082/0/07177478",
"title": "Affect-expressive hand gestures synthesis and animation",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2015/07177478/12OmNxGja0m",
"parentPublication": {
"id": "proceedings/icme/2015/7082/0",
"title": "2015 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2003/1900/1/190010565",
"title": "Improving Continuous Gesture Recognition with Spoken Prosody",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2003/190010565/12OmNxYbSWY",
"parentPublication": {
"id": "proceedings/cvpr/2003/1900/1",
"title": "2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2006/0366/0/04036744",
"title": "Combined Gesture-Speech Analysis and Speech Driven Gesture Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2006/04036744/12OmNyywxFz",
"parentPublication": {
"id": "proceedings/icme/2006/0366/0",
"title": "2006 IEEE International Conference on Multimedia and Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2012/1204/0/06184206",
"title": "Poster: Head gesture 3D interface using a head mounted camera",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2012/06184206/12OmNzayNwg",
"parentPublication": {
"id": "proceedings/3dui/2012/1204/0",
"title": "2012 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2023/4544/0/10042658",
"title": "Zero-Shot Style Transfer for Multimodal Data-Driven Gesture Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2023/10042658/1KOv3RuySnC",
"parentPublication": {
"id": "proceedings/fg/2023/4544/0",
"title": "2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttp2008081313",
"articleId": "13rRUxBrGi2",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttp2008081346",
"articleId": "13rRUyfbwrW",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNBl6EKh",
"title": "April",
"year": "2017",
"issueNum": "04",
"idPrefix": "tg",
"pubType": "journal",
"volume": "23",
"label": "April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwgQpqL",
"doi": "10.1109/TVCG.2017.2656978",
"abstract": "We define the concept of Dynamic Passive Haptic Feedback (DPHF) for virtual reality by introducing the weight-shifting physical DPHF proxy object Shifty. This concept combines actuators known from active haptics and physical proxies known from passive haptics to construct proxies that automatically adapt their passive haptic feedback. We describe the concept behind our ungrounded weight-shifting DPHF proxy Shifty and the implementation of our prototype. We then investigate how Shifty can, by automatically changing its internal weight distribution, enhance the user's perception of virtual objects interacted with in two experiments. In a first experiment, we show that Shifty can enhance the perception of virtual objects changing in shape, especially in length and thickness. Here, Shifty was shown to increase the user's fun and perceived realism significantly, compared to an equivalent passive haptic proxy. In a second experiment, Shifty is used to pick up virtual objects of different virtual weights. The results show that Shifty enhances the perception of weight and thus the perceived realism by adapting its kinesthetic feedback to the picked-up virtual object. In the same experiment, we additionally show that specific combinations of haptic, visual and auditory feedback during the pick-up interaction help to compensate for visual-haptic mismatch perceived during the shifting process.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We define the concept of Dynamic Passive Haptic Feedback (DPHF) for virtual reality by introducing the weight-shifting physical DPHF proxy object Shifty. This concept combines actuators known from active haptics and physical proxies known from passive haptics to construct proxies that automatically adapt their passive haptic feedback. We describe the concept behind our ungrounded weight-shifting DPHF proxy Shifty and the implementation of our prototype. We then investigate how Shifty can, by automatically changing its internal weight distribution, enhance the user's perception of virtual objects interacted with in two experiments. In a first experiment, we show that Shifty can enhance the perception of virtual objects changing in shape, especially in length and thickness. Here, Shifty was shown to increase the user's fun and perceived realism significantly, compared to an equivalent passive haptic proxy. In a second experiment, Shifty is used to pick up virtual objects of different virtual weights. The results show that Shifty enhances the perception of weight and thus the perceived realism by adapting its kinesthetic feedback to the picked-up virtual object. In the same experiment, we additionally show that specific combinations of haptic, visual and auditory feedback during the pick-up interaction help to compensate for visual-haptic mismatch perceived during the shifting process.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We define the concept of Dynamic Passive Haptic Feedback (DPHF) for virtual reality by introducing the weight-shifting physical DPHF proxy object Shifty. This concept combines actuators known from active haptics and physical proxies known from passive haptics to construct proxies that automatically adapt their passive haptic feedback. We describe the concept behind our ungrounded weight-shifting DPHF proxy Shifty and the implementation of our prototype. We then investigate how Shifty can, by automatically changing its internal weight distribution, enhance the user's perception of virtual objects interacted with in two experiments. In a first experiment, we show that Shifty can enhance the perception of virtual objects changing in shape, especially in length and thickness. Here, Shifty was shown to increase the user's fun and perceived realism significantly, compared to an equivalent passive haptic proxy. In a second experiment, Shifty is used to pick up virtual objects of different virtual weights. The results show that Shifty enhances the perception of weight and thus the perceived realism by adapting its kinesthetic feedback to the picked-up virtual object. In the same experiment, we additionally show that specific combinations of haptic, visual and auditory feedback during the pick-up interaction help to compensate for visual-haptic mismatch perceived during the shifting process.",
"title": "Shifty: A Weight-Shifting Dynamic Passive Haptic Proxy to Enhance Object Perception in Virtual Reality",
"normalizedTitle": "Shifty: A Weight-Shifting Dynamic Passive Haptic Proxy to Enhance Object Perception in Virtual Reality",
"fno": "07833030",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Actuators",
"Haptic Interfaces",
"Human Computer Interaction",
"Virtual Reality",
"Visual Perception",
"Object Perception",
"Dynamic Passive Haptic Feedback",
"Virtual Reality",
"Weight Shifting Physical DPHF Proxy Object",
"Shifty",
"Actuators",
"Kinesthetic Feedback",
"Virtual Object",
"Auditory Feedback",
"Visual Feedback",
"Visual Haptic Mismatch",
"Haptic Interfaces",
"Visualization",
"Actuators",
"Shape",
"Augmented Reality",
"Augmented Virtuality",
"Dynamic Passive Haptic Feedback",
"Input Devices",
"Virtual Reality",
"Haptics",
"Perception"
],
"authors": [
{
"givenName": "André",
"surname": "Zenner",
"fullName": "André Zenner",
"affiliation": "German Research Center for Artificial Intelligence (DFKI)",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Antonio",
"surname": "Krüger",
"fullName": "Antonio Krüger",
"affiliation": "German Research Center for Artificial Intelligence (DFKI)",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2017-04-01 00:00:00",
"pubType": "trans",
"pages": "1285-1294",
"year": "2017",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/th/2017/04/07892978",
"title": "Evaluation of Wearable Haptic Systems for the Fingers in Augmented Reality Applications",
"doi": null,
"abstractUrl": "/journal/th/2017/04/07892978/13rRUwInv4D",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/04/08260962",
"title": "Ascending and Descending in Virtual Reality: Simple and Safe System Using Passive Haptics",
"doi": null,
"abstractUrl": "/journal/tg/2018/04/08260962/13rRUwjGoLM",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a824",
"title": "Touch the History in Virtuality: Combine Passive Haptic with 360° Videos in History Learning",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a824/1CJdh3RT5wQ",
"parentPublication": {
"id": "proceedings/vrw/2022/8402/0",
"title": "2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/5555/01/09999325",
"title": "Presenting Morphing Shape Illusion: Enhanced Sense of Morphing Virtual Object with Weight Shifting VR Controller by Computational Perception Model",
"doi": null,
"abstractUrl": "/magazine/cg/5555/01/09999325/1JqD9O3nz68",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2022/5325/0/532500a748",
"title": "Wormholes in VR: Teleporting Hands for Flexible Passive Haptics",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2022/532500a748/1JrR93EDicE",
"parentPublication": {
"id": "proceedings/ismar/2022/5325/0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2022/5325/0/532500a538",
"title": "CardsVR: A Two-Person VR Experience with Passive Haptic Feedback from a Deck of Playing Cards",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2022/532500a538/1JrRaySJ7So",
"parentPublication": {
"id": "proceedings/ismar/2022/5325/0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2019/4765/0/476500a042",
"title": "Smart Haproxy: A Novel Vibrotactile Feedback Prototype Combining Passive and Active Haptic in AR Interaction",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2019/476500a042/1gysov56h20",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2019/4765/0",
"title": "2019 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2020/6532/0/09090415",
"title": "Enhancing Proxy-Based Haptics in Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2020/09090415/1jIxtWMak6c",
"parentPublication": {
"id": "proceedings/vrw/2020/6532/0",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09382898",
"title": "Combining Dynamic Passive Haptics and Haptic Retargeting for Enhanced Haptic Feedback in Virtual Reality",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09382898/1saZv7Dd9Ty",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2021/4057/0/405700a575",
"title": "The Effect of the Virtual Object Size on Weight Perception Augmented with Pseudo-Haptic Feedback",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2021/405700a575/1tnWwW9JGXC",
"parentPublication": {
"id": "proceedings/vrw/2021/4057/0",
"title": "2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07829397",
"articleId": "13rRUy2YLT5",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07829409",
"articleId": "13rRUNvgz4l",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "17ShDTXFgxV",
"name": "ttg201704-07833030s1.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg201704-07833030s1.zip",
"extension": "zip",
"size": "74.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNrJRP29",
"title": "July-Sept.",
"year": "2013",
"issueNum": "03",
"idPrefix": "th",
"pubType": "journal",
"volume": "6",
"label": "July-Sept.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwhHcJv",
"doi": "10.1109/TOH.2013.20",
"abstract": "This paper presents a new haptic rendering method for streaming point cloud data. It provides haptic rendering of moving physical objects using data obtained from RGB-D cameras. Thus, real-time haptic interaction with moving objects can be achieved using noncontact sensors. This method extends \"virtual coupling\"-based proxy methods in a way that does not require preprocessing of points and allows for spatial point cloud discontinuities. The key ideas of the algorithm are iterative motion of the proxy with respect to the points, and the use of a variable proxy step size that results in better accuracy for short proxy movements and faster convergence for longer movements. This method provides highly accurate haptic interaction for geometries in which the proxy can physically fit. Another advantage is a significant reduction in the risk of \"pop through\" during haptic interaction with dynamic point clouds, even in the presence of noise. This haptic rendering method is computationally efficient; it can run in real time on available personal computers without the need for downsampling of point clouds from commercially available depth cameras.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents a new haptic rendering method for streaming point cloud data. It provides haptic rendering of moving physical objects using data obtained from RGB-D cameras. Thus, real-time haptic interaction with moving objects can be achieved using noncontact sensors. This method extends \"virtual coupling\"-based proxy methods in a way that does not require preprocessing of points and allows for spatial point cloud discontinuities. The key ideas of the algorithm are iterative motion of the proxy with respect to the points, and the use of a variable proxy step size that results in better accuracy for short proxy movements and faster convergence for longer movements. This method provides highly accurate haptic interaction for geometries in which the proxy can physically fit. Another advantage is a significant reduction in the risk of \"pop through\" during haptic interaction with dynamic point clouds, even in the presence of noise. This haptic rendering method is computationally efficient; it can run in real time on available personal computers without the need for downsampling of point clouds from commercially available depth cameras.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents a new haptic rendering method for streaming point cloud data. It provides haptic rendering of moving physical objects using data obtained from RGB-D cameras. Thus, real-time haptic interaction with moving objects can be achieved using noncontact sensors. This method extends \"virtual coupling\"-based proxy methods in a way that does not require preprocessing of points and allows for spatial point cloud discontinuities. The key ideas of the algorithm are iterative motion of the proxy with respect to the points, and the use of a variable proxy step size that results in better accuracy for short proxy movements and faster convergence for longer movements. This method provides highly accurate haptic interaction for geometries in which the proxy can physically fit. Another advantage is a significant reduction in the risk of \"pop through\" during haptic interaction with dynamic point clouds, even in the presence of noise. This haptic rendering method is computationally efficient; it can run in real time on available personal computers without the need for downsampling of point clouds from commercially available depth cameras.",
"title": "A Proxy Method for Real-Time 3-DOF Haptic Rendering of Streaming Point Cloud Data",
"normalizedTitle": "A Proxy Method for Real-Time 3-DOF Haptic Rendering of Streaming Point Cloud Data",
"fno": "tth2013030257",
"hasPdf": true,
"idPrefix": "th",
"keywords": [
"Haptic Interfaces",
"Rendering Computer Graphics",
"Hip",
"Vectors",
"Real Time Systems",
"Cameras",
"Force",
"Point Cloud Velocity Estimation",
"Haptic Rendering",
"Streaming Point Cloud Data"
],
"authors": [
{
"givenName": "F.",
"surname": "Ryden",
"fullName": "F. Ryden",
"affiliation": "Dept. of Electr. Eng., Univ. of Washington, Seattle, WA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "H. J.",
"surname": "Chizeck",
"fullName": "H. J. Chizeck",
"affiliation": "Dept. of Electr. Eng., Univ. of Washington, Seattle, WA, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "03",
"pubDate": "2013-07-01 00:00:00",
"pubType": "trans",
"pages": "257-267",
"year": "2013",
"issn": "1939-1412",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cw/2012/4814/0/4814a157",
"title": "Stable Dynamic Algorithm Based on Virtual Coupling for 6-DOF Haptic Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2012/4814a157/12OmNqJ8tk6",
"parentPublication": {
"id": "proceedings/cw/2012/4814/0",
"title": "2012 International Conference on Cyberworlds",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2008/2005/0/04479948",
"title": "Perceptual Rendering for Learning Haptic Skills",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2008/04479948/12OmNqJq4vK",
"parentPublication": {
"id": "proceedings/haptics/2008/2005/0",
"title": "IEEE Haptics Symposium 2008",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/gcis/2009/3571/4/3571d259",
"title": "Contact Elements Prediction Based Haptic Rendering Method for Collaborative Virtual Assembly System",
"doi": null,
"abstractUrl": "/proceedings-article/gcis/2009/3571d259/12OmNwJybQW",
"parentPublication": {
"id": "proceedings/gcis/2009/3571/4",
"title": "2009 WRI Global Congress on Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2011/4602/0/4602a271",
"title": "Haptic Rendering of Virtual Hand with Force Smoothing",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2011/4602a271/12OmNx3q6XD",
"parentPublication": {
"id": "proceedings/icvrv/2011/4602/0",
"title": "2011 International Conference on Virtual Reality and Visualization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2013/2246/0/2246a294",
"title": "A Prediction Method Using Interpolation for Smooth Six-DOF Haptic Rendering in Multirate Simulation",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2013/2246a294/12OmNyKrHlI",
"parentPublication": {
"id": "proceedings/cw/2013/2246/0",
"title": "2013 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2013/2246/0/2246a286",
"title": "Image-Driven Haptic Rendering in Virtual Environments",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2013/2246a286/12OmNyuy9Q9",
"parentPublication": {
"id": "proceedings/cw/2013/2246/0",
"title": "2013 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/whc/2007/2738/0/04145225",
"title": "Fast Rendering for a Multifinger Haptic Display",
"doi": null,
"abstractUrl": "/proceedings-article/whc/2007/04145225/12OmNzyp5Vq",
"parentPublication": {
"id": "proceedings/whc/2007/2738/0",
"title": "2007 2nd Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environments and Teleoperator Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2008/01/tth2008010039",
"title": "Six-DoF Haptic Rendering of Contact Between Geometrically Complex Reduced Deformable Models",
"doi": null,
"abstractUrl": "/journal/th/2008/01/tth2008010039/13rRUEgarBB",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/th/2016/04/07476889",
"title": "Data-Driven Haptic Modeling and Rendering of Viscoelastic and Frictional Responses of Deformable Objects",
"doi": null,
"abstractUrl": "/journal/th/2016/04/07476889/13rRUwfZBVt",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2018/7315/0/731500a431",
"title": "Real-Time Haptic Rendering of Double-Points Interaction",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2018/731500a431/17D45WaTkft",
"parentPublication": {
"id": "proceedings/cw/2018/7315/0",
"title": "2018 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "tth20130300c2",
"articleId": "13rRUxD9gXU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "tth2013030268",
"articleId": "13rRUxcbnHq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "17ShDTXnFrQ",
"name": "tth2013030257s1.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/tth2013030257s1.mp4",
"extension": "mp4",
"size": "7.25 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1HGJ6XQen96",
"title": "Nov.",
"year": "2022",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1GjwGUGyCuk",
"doi": "10.1109/TVCG.2022.3203098",
"abstract": "Stereoscopic AR and VR headsets have displays and lenses that are either fixed or adjustable to match a limited range of user inter-pupillary distances (IPDs). Projective geometry predicts a misperception of depth when either the displays or virtual cameras used to render images are misaligned with the eyes. However, misalignment between the eyes and lenses might also affect binocular convergence, which could further distort perceived depth. This possibility has been largely ignored in previous studies. Here, we evaluated this phenomenon in a VR headset in which the inter-lens and inter-axial camera separations are coupled and adjustable. In a baseline condition, both were matched to observers' IPDs. In two other conditions, the inter-lens and inter-axial camera separations were set to the maximum and minimum allowed by the headset. In each condition, observers were instructed to adjust a fold created by two intersecting, textured surfaces until it appeared to have an angle of 90°. The task was performed at three randomly interleaved viewing distances, monocularly and binocularly. In the monocular condition, observers underestimated the fold angle and there was no effect of viewing distance on their settings. In the binocular conditions, we found that when the lens and camera separation were less than the viewer's IPD, they exhibited compression of perceived slant relative to baseline. The reverse pattern was seen when the lens and camera separation were larger than the viewer's IPD. These results were well explained by a geometric model that considers shifts in convergence due to lens and display misalignment with the eyes, as well as the relative contribution of monocular cues.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Stereoscopic AR and VR headsets have displays and lenses that are either fixed or adjustable to match a limited range of user inter-pupillary distances (IPDs). Projective geometry predicts a misperception of depth when either the displays or virtual cameras used to render images are misaligned with the eyes. However, misalignment between the eyes and lenses might also affect binocular convergence, which could further distort perceived depth. This possibility has been largely ignored in previous studies. Here, we evaluated this phenomenon in a VR headset in which the inter-lens and inter-axial camera separations are coupled and adjustable. In a baseline condition, both were matched to observers' IPDs. In two other conditions, the inter-lens and inter-axial camera separations were set to the maximum and minimum allowed by the headset. In each condition, observers were instructed to adjust a fold created by two intersecting, textured surfaces until it appeared to have an angle of 90°. The task was performed at three randomly interleaved viewing distances, monocularly and binocularly. In the monocular condition, observers underestimated the fold angle and there was no effect of viewing distance on their settings. In the binocular conditions, we found that when the lens and camera separation were less than the viewer's IPD, they exhibited compression of perceived slant relative to baseline. The reverse pattern was seen when the lens and camera separation were larger than the viewer's IPD. These results were well explained by a geometric model that considers shifts in convergence due to lens and display misalignment with the eyes, as well as the relative contribution of monocular cues.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Stereoscopic AR and VR headsets have displays and lenses that are either fixed or adjustable to match a limited range of user inter-pupillary distances (IPDs). Projective geometry predicts a misperception of depth when either the displays or virtual cameras used to render images are misaligned with the eyes. However, misalignment between the eyes and lenses might also affect binocular convergence, which could further distort perceived depth. This possibility has been largely ignored in previous studies. Here, we evaluated this phenomenon in a VR headset in which the inter-lens and inter-axial camera separations are coupled and adjustable. In a baseline condition, both were matched to observers' IPDs. In two other conditions, the inter-lens and inter-axial camera separations were set to the maximum and minimum allowed by the headset. In each condition, observers were instructed to adjust a fold created by two intersecting, textured surfaces until it appeared to have an angle of 90°. The task was performed at three randomly interleaved viewing distances, monocularly and binocularly. In the monocular condition, observers underestimated the fold angle and there was no effect of viewing distance on their settings. In the binocular conditions, we found that when the lens and camera separation were less than the viewer's IPD, they exhibited compression of perceived slant relative to baseline. The reverse pattern was seen when the lens and camera separation were larger than the viewer's IPD. These results were well explained by a geometric model that considers shifts in convergence due to lens and display misalignment with the eyes, as well as the relative contribution of monocular cues.",
"title": "The impacts of lens and stereo camera separation on perceived slant in Virtual Reality head-mounted displays",
"normalizedTitle": "The impacts of lens and stereo camera separation on perceived slant in Virtual Reality head-mounted displays",
"fno": "09873994",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Cameras",
"Eye",
"Geometry",
"Helmet Mounted Displays",
"Human Factors",
"Lenses",
"Rendering Computer Graphics",
"Stereo Image Processing",
"Three Dimensional Displays",
"Virtual Reality",
"Visual Perception",
"Baseline Condition",
"Binocular Conditions",
"Binocular Convergence",
"Display Misalignment",
"Inter Axial Camera Separations",
"Inter Lens",
"Lenses",
"Monocular Condition",
"Observers",
"Perceived Depth",
"Perceived Slant",
"Randomly Interleaved Viewing Distances",
"Stereo Camera Separation",
"User Inter Pupillary Distances",
"Viewer",
"Viewing Distance",
"Virtual Cameras",
"Virtual Reality Head Mounted Displays",
"VR Headset",
"Cameras",
"Observers",
"Lenses",
"Convergence",
"Task Analysis",
"Predictive Models",
"Headphones",
"Virtual Reality",
"Interpupillary Distance",
"Depth Perception"
],
"authors": [
{
"givenName": "Jonathan",
"surname": "Tong",
"fullName": "Jonathan Tong",
"affiliation": "Centre for Vision Research, York University, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Laurie M",
"surname": "Wilcox",
"fullName": "Laurie M Wilcox",
"affiliation": "Centre for Vision Research, York University, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Robert S",
"surname": "Allison",
"fullName": "Robert S Allison",
"affiliation": "Centre for Vision Research, York University, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2022-11-01 00:00:00",
"pubType": "trans",
"pages": "3759-3766",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/robot/1992/2720/0/00220032",
"title": "Modeling of a computer-controlled zoom lens",
"doi": null,
"abstractUrl": "/proceedings-article/robot/1992/00220032/12OmNC8MsH7",
"parentPublication": {
"id": "proceedings/robot/1992/2720/0",
"title": "Proceedings 1992 IEEE International Conference on Robotics and Automation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccp/2011/707/0/05753127",
"title": "Motion invariance and custom blur from lens motion",
"doi": null,
"abstractUrl": "/proceedings-article/iccp/2011/05753127/12OmNqIzh8Z",
"parentPublication": {
"id": "proceedings/iccp/2011/707/0",
"title": "IEEE International Conference on Computational Photography (ICCP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccp/2009/4534/0/05559009",
"title": "Image destabilization: Programmable defocus using lens and sensor motion",
"doi": null,
"abstractUrl": "/proceedings-article/iccp/2009/05559009/12OmNvxsSTw",
"parentPublication": {
"id": "proceedings/iccp/2009/4534/0",
"title": "IEEE International Conference on Computational Photography (ICCP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ised/2014/6965/0/6965a025",
"title": "Plasmonic Lens Based on Elliptically Tapered Metallic Nano Slits",
"doi": null,
"abstractUrl": "/proceedings-article/ised/2014/6965a025/12OmNwdtw8Y",
"parentPublication": {
"id": "proceedings/ised/2014/6965/0",
"title": "2014 Fifth International Symposium on Electronic System Design (ISED)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2017/0733/0/0733b763",
"title": "Optimizing the Lens Selection Process for Multi-focus Plenoptic Cameras and Numerical Evaluation",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2017/0733b763/12OmNwtn3En",
"parentPublication": {
"id": "proceedings/cvprw/2017/0733/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09760161",
"title": "Predicting Subjective Discomfort Associated with Lens Distortion in VR Headsets During Vestibulo-Ocular Response to VR Scenes",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09760161/1CHsCvUiJQA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08797912",
"title": "Edible Lens Made of Agar",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08797912/1cJ1gTRZdIs",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2020/6532/0/09090461",
"title": "Front Camera Eye Tracking For Mobile VR",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2020/09090461/1jIxzvZw4YU",
"parentPublication": {
"id": "proceedings/vrw/2020/6532/0",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093558",
"title": "Online Lens Motion Smoothing for Video Autofocus",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093558/1jPbDql8Ptu",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trustcom/2020/4380/0/438000b285",
"title": "Explicitly Privacy-Aware Space Usage Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/trustcom/2020/438000b285/1r547dOl85i",
"parentPublication": {
"id": "proceedings/trustcom/2020/4380/0",
"title": "2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09872027",
"articleId": "1GhRUPatDmU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09873971",
"articleId": "1GjwLJt4CaI",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1HGJ8FLJtDO",
"name": "ttg202211-09873994s1-supp1-3203098.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202211-09873994s1-supp1-3203098.pdf",
"extension": "pdf",
"size": "272 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwMob9C",
"title": "April",
"year": "2018",
"issueNum": "04",
"idPrefix": "tg",
"pubType": "journal",
"volume": "24",
"label": "April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxDqS8o",
"doi": "10.1109/TVCG.2018.2793599",
"abstract": "Understanding how people explore immersive virtual environments is crucial for many applications, such as designing virtual reality (VR) content, developing new compression algorithms, or learning computational models of saliency or visual attention. Whereas a body of recent work has focused on modeling saliency in desktop viewing conditions, VR is very different from these conditions in that viewing behavior is governed by stereoscopic vision and by the complex interaction of head orientation, gaze, and other kinematic constraints. To further our understanding of viewing behavior and saliency in VR, we capture and analyze gaze and head orientation data of 169 users exploring stereoscopic, static omni-directional panoramas, for a total of 1980 head and gaze trajectories for three different viewing conditions. We provide a thorough analysis of our data, which leads to several important insights, such as the existence of a particular fixation bias, which we then use to adapt existing saliency predictors to immersive VR conditions. In addition, we explore other applications of our data and analysis, including automatic alignment of VR video cuts, panorama thumbnails, panorama video synopsis, and saliency-basedcompression.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Understanding how people explore immersive virtual environments is crucial for many applications, such as designing virtual reality (VR) content, developing new compression algorithms, or learning computational models of saliency or visual attention. Whereas a body of recent work has focused on modeling saliency in desktop viewing conditions, VR is very different from these conditions in that viewing behavior is governed by stereoscopic vision and by the complex interaction of head orientation, gaze, and other kinematic constraints. To further our understanding of viewing behavior and saliency in VR, we capture and analyze gaze and head orientation data of 169 users exploring stereoscopic, static omni-directional panoramas, for a total of 1980 head and gaze trajectories for three different viewing conditions. We provide a thorough analysis of our data, which leads to several important insights, such as the existence of a particular fixation bias, which we then use to adapt existing saliency predictors to immersive VR conditions. In addition, we explore other applications of our data and analysis, including automatic alignment of VR video cuts, panorama thumbnails, panorama video synopsis, and saliency-basedcompression.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Understanding how people explore immersive virtual environments is crucial for many applications, such as designing virtual reality (VR) content, developing new compression algorithms, or learning computational models of saliency or visual attention. Whereas a body of recent work has focused on modeling saliency in desktop viewing conditions, VR is very different from these conditions in that viewing behavior is governed by stereoscopic vision and by the complex interaction of head orientation, gaze, and other kinematic constraints. To further our understanding of viewing behavior and saliency in VR, we capture and analyze gaze and head orientation data of 169 users exploring stereoscopic, static omni-directional panoramas, for a total of 1980 head and gaze trajectories for three different viewing conditions. We provide a thorough analysis of our data, which leads to several important insights, such as the existence of a particular fixation bias, which we then use to adapt existing saliency predictors to immersive VR conditions. In addition, we explore other applications of our data and analysis, including automatic alignment of VR video cuts, panorama thumbnails, panorama video synopsis, and saliency-basedcompression.",
"title": "Saliency in VR: How Do People Explore Virtual Environments?",
"normalizedTitle": "Saliency in VR: How Do People Explore Virtual Environments?",
"fno": "08269807",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Gaze Tracking",
"Image Motion Analysis",
"Stereo Image Processing",
"Virtual Reality",
"Immersive Virtual Environments",
"Virtual Reality Content",
"Compression Algorithms",
"Computational Models",
"Visual Attention",
"Modeling Saliency",
"Desktop Viewing Conditions",
"Viewing Behavior",
"Stereoscopic Vision",
"Head Orientation Data",
"Stereoscopic Omni Directional Panoramas",
"Static Omni Directional Panoramas",
"Immersive VR Conditions",
"VR Video Cuts",
"Viewing Conditions",
"Saliency Predictors",
"Gaze Orientation Data",
"Saliency Based Compression",
"Head",
"Visualization",
"Magnetic Heads",
"Virtual Environments",
"Stereo Image Processing",
"Predictive Models",
"Computational Modeling",
"Saliency",
"Omnidirectional Stereoscopic Panoramas"
],
"authors": [
{
"givenName": "Vincent",
"surname": "Sitzmann",
"fullName": "Vincent Sitzmann",
"affiliation": "Stanford University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ana",
"surname": "Serrano",
"fullName": "Ana Serrano",
"affiliation": "Universidad de Zaragoza",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Amy",
"surname": "Pavel",
"fullName": "Amy Pavel",
"affiliation": "University of California, Berkeley",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Maneesh",
"surname": "Agrawala",
"fullName": "Maneesh Agrawala",
"affiliation": "Stanford University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Diego",
"surname": "Gutierrez",
"fullName": "Diego Gutierrez",
"affiliation": "Universidad de Zaragoza",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Belen",
"surname": "Masia",
"fullName": "Belen Masia",
"affiliation": "Universidad de Zaragoza",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gordon",
"surname": "Wetzstein",
"fullName": "Gordon Wetzstein",
"affiliation": "Stanford University",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2018-04-01 00:00:00",
"pubType": "trans",
"pages": "1633-1642",
"year": "2018",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iciev/2013/0400/0/06572539",
"title": "An intelligent human-robot interaction framework to control the human attention",
"doi": null,
"abstractUrl": "/proceedings-article/iciev/2013/06572539/12OmNrH1PAr",
"parentPublication": {
"id": "proceedings/iciev/2013/0400/0",
"title": "2013 2nd International Conference on Informatics, Electronics and Vision (ICIEV 2013)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209b869",
"title": "Appearance-Based Gaze Tracking with Free Head Movement",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209b869/12OmNyo1nKa",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08446495",
"title": "Head-to-Body-Pose Classification in No-Pose VR Tracking Systems",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08446495/13bd1f3HvEZ",
"parentPublication": {
"id": "proceedings/vr/2018/3365/0",
"title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2018/6100/0/610000c237",
"title": "Light-Weight Head Pose Invariant Gaze Tracking",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2018/610000c237/17D45WXIkI8",
"parentPublication": {
"id": "proceedings/cvprw/2018/6100/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a744",
"title": "Who do you look like? - Gaze-based authentication for workers in VR",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a744/1CJdaD5K7Vm",
"parentPublication": {
"id": "proceedings/vrw/2022/8402/0",
"title": "2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2022/02/09779506",
"title": "Why VR Games Sickness? An Empirical Study of Capturing and Analyzing VR Games Head Movement Dataset",
"doi": null,
"abstractUrl": "/magazine/mu/2022/02/09779506/1DwUBBXPkVG",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2019/2297/0/229700a061",
"title": "Visual Saliency Prediction in Dynamic Virtual Reality Environments Experienced with Head-Mounted Displays: An Exploratory Study",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2019/229700a061/1fHkoP8izEQ",
"parentPublication": {
"id": "proceedings/cw/2019/2297/0",
"title": "2019 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800e472",
"title": "How Much Time Do You Have? Modeling Multi-Duration Saliency",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800e472/1m3njRPpHdC",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2021/4057/0/405700a707",
"title": "[DC] Eye Fixation Forecasting in Task-Oriented Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2021/405700a707/1tnWQmeJsZi",
"parentPublication": {
"id": "proceedings/vrw/2021/4057/0",
"title": "2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/04/09664291",
"title": "EHTask: Recognizing User Tasks From Eye and Head Movements in Immersive Virtual Reality",
"doi": null,
"abstractUrl": "/journal/tg/2023/04/09664291/1zHDIPIlNBe",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08260943",
"articleId": "13rRUNvyato",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08263407",
"articleId": "13rRUILtJqW",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1lxvrWRk8WA",
"name": "ttg201804-08269807s1-supp1-2793599.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg201804-08269807s1-supp1-2793599.mp4",
"extension": "mp4",
"size": "29.1 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvvc5OL",
"title": "April",
"year": "2013",
"issueNum": "04",
"idPrefix": "tg",
"pubType": "journal",
"volume": "19",
"label": "April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxlgy3G",
"doi": "10.1109/TVCG.2013.36",
"abstract": "The perception of objects, depth, and distance has been repeatedly shown to be divergent between virtual and physical environments. We hypothesize that many of these discrepancies stem from incorrect geometric viewing parameters, specifically that physical measurements of eye position are insufficiently precise to provide proper viewing parameters. In this paper, we introduce a perceptual calibration procedure derived from geometric models. While most research has used geometric models to predict perceptual errors, we instead use these models inversely to determine perceptually correct viewing parameters. We study the advantages of these new psychophysically determined viewing parameters compared to the commonly used measured viewing parameters in an experiment with 20 subjects. The perceptually calibrated viewing parameters for the subjects generally produced new virtual eye positions that were wider and deeper than standard practices would estimate. Our study shows that perceptually calibrated viewing parameters can significantly improve depth acuity, distance estimation, and the perception of shape.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The perception of objects, depth, and distance has been repeatedly shown to be divergent between virtual and physical environments. We hypothesize that many of these discrepancies stem from incorrect geometric viewing parameters, specifically that physical measurements of eye position are insufficiently precise to provide proper viewing parameters. In this paper, we introduce a perceptual calibration procedure derived from geometric models. While most research has used geometric models to predict perceptual errors, we instead use these models inversely to determine perceptually correct viewing parameters. We study the advantages of these new psychophysically determined viewing parameters compared to the commonly used measured viewing parameters in an experiment with 20 subjects. The perceptually calibrated viewing parameters for the subjects generally produced new virtual eye positions that were wider and deeper than standard practices would estimate. Our study shows that perceptually calibrated viewing parameters can significantly improve depth acuity, distance estimation, and the perception of shape.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The perception of objects, depth, and distance has been repeatedly shown to be divergent between virtual and physical environments. We hypothesize that many of these discrepancies stem from incorrect geometric viewing parameters, specifically that physical measurements of eye position are insufficiently precise to provide proper viewing parameters. In this paper, we introduce a perceptual calibration procedure derived from geometric models. While most research has used geometric models to predict perceptual errors, we instead use these models inversely to determine perceptually correct viewing parameters. We study the advantages of these new psychophysically determined viewing parameters compared to the commonly used measured viewing parameters in an experiment with 20 subjects. The perceptually calibrated viewing parameters for the subjects generally produced new virtual eye positions that were wider and deeper than standard practices would estimate. Our study shows that perceptually calibrated viewing parameters can significantly improve depth acuity, distance estimation, and the perception of shape.",
"title": "Perceptual Calibration for Immersive Display Environments",
"normalizedTitle": "Perceptual Calibration for Immersive Display Environments",
"fno": "ttg2013040691",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Calibration",
"Solid Modeling",
"Estimation",
"Shape",
"Virtual Environments",
"Cameras",
"Stereo Vision Displays",
"Virtual Reality",
"Calibration",
"Perception",
"Distance Estimation",
"Shape Perception",
"Depth Compression"
],
"authors": [
{
"givenName": "K.",
"surname": "Ponto",
"fullName": "K. Ponto",
"affiliation": "Dept. of Comput. Sci., Univ. of Wisconsin, Madison, WI, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "M.",
"surname": "Gleicher",
"fullName": "M. Gleicher",
"affiliation": "Dept. of Comput. Sci., Univ. of Wisconsin, Madison, WI, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "R. G.",
"surname": "Radwin",
"fullName": "R. G. Radwin",
"affiliation": "Dept. of Biomed. Eng., Univ. of Wisconsin, Madison, WI, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": null,
"surname": "Hyun Joon Shin",
"fullName": "Hyun Joon Shin",
"affiliation": "Div. of Digital Media, Ajou Univ., Suwon, South Korea",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2013-04-01 00:00:00",
"pubType": "trans",
"pages": "691-700",
"year": "2013",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2017/4822/0/07926707",
"title": "Automatic Calibration of a Multiple-Projector Spherical Fish Tank VR Display",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2017/07926707/12OmNAoDhTe",
"parentPublication": {
"id": "proceedings/wacv/2017/4822/0",
"title": "2017 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2008/2174/0/04761481",
"title": "Camera calibration for uneven terrains by observing pedestrians",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761481/12OmNC8dgoP",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2011/348/0/06011885",
"title": "Novel projector calibration approaches of multi-resolution display",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2011/06011885/12OmNCd2rEL",
"parentPublication": {
"id": "proceedings/icme/2011/348/0",
"title": "2011 IEEE International Conference on Multimedia and Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2014/2871/0/06802063",
"title": "Automated calibration of display characteristics (ACDC) for head-mounted displays and arbitrary surfaces",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2014/06802063/12OmNxwENpf",
"parentPublication": {
"id": "proceedings/vr/2014/2871/0",
"title": "2014 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/1993/3880/0/00341038",
"title": "Efficient and robust methods of accurate camera calibration",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/1993/00341038/12OmNyo1nQx",
"parentPublication": {
"id": "proceedings/cvpr/1993/3880/0",
"title": "Proceedings of IEEE Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2017/1032/0/1032c554",
"title": "Low-Dimensionality Calibration through Local Anisotropic Scaling for Robust Hand Model Personalization",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/1032c554/12OmNywfKHK",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2015/1727/0/07223434",
"title": "A multi-projector display system of arbitrary shape, size and resolution",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2015/07223434/12OmNzYNNiY",
"parentPublication": {
"id": "proceedings/vr/2015/1727/0",
"title": "2015 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2011/0063/0/06130255",
"title": "Calibration of radially symmetric distortion based on linearity in the calibrated image",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2011/06130255/12OmNzzxuyx",
"parentPublication": {
"id": "proceedings/iccvw/2011/0063/0",
"title": "2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/1991/04/i0370",
"title": "Camera Calibration by Vanishing Lines for 3-D Computer Vision",
"doi": null,
"abstractUrl": "/journal/tp/1991/04/i0370/13rRUwhpBEQ",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08798019",
"title": "Large-Scale Projection-Based Immersive Display: The Design and Implementation of LargeSpace",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798019/1cJ17trBZEQ",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttg2013040681",
"articleId": "13rRUILLkvr",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttg2013040701",
"articleId": "13rRUx0xPmZ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1MTOUEFAeT6",
"title": "June",
"year": "2023",
"issueNum": "06",
"idPrefix": "tp",
"pubType": "journal",
"volume": "45",
"label": "June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1j4mrhzYkw0",
"doi": "10.1109/TPAMI.2020.2986648",
"abstract": "Egocentric vision (a.k.a. first-person vision–FPV) applications have thrived over the past few years, thanks to the availability of affordable wearable cameras and large annotated datasets. The position of the wearable camera (usually mounted on the head) allows recording exactly what the camera wearers have in front of them, in particular hands and manipulated objects. This intrinsic advantage enables the study of the hands from multiple perspectives: localizing hands and their parts within the images; understanding what actions and activities the hands are involved in; and developing human-computer interfaces that rely on hand gestures. In this survey, we review the literature that focuses on the hands using egocentric vision, categorizing the existing approaches into: localization (where are the hands or parts of them?); interpretation (what are the hands doing?); and application (e.g., systems that used egocentric hand cues for solving a specific problem). Moreover, a list of the most prominent datasets with hand-based annotations is provided.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Egocentric vision (a.k.a. first-person vision–FPV) applications have thrived over the past few years, thanks to the availability of affordable wearable cameras and large annotated datasets. The position of the wearable camera (usually mounted on the head) allows recording exactly what the camera wearers have in front of them, in particular hands and manipulated objects. This intrinsic advantage enables the study of the hands from multiple perspectives: localizing hands and their parts within the images; understanding what actions and activities the hands are involved in; and developing human-computer interfaces that rely on hand gestures. In this survey, we review the literature that focuses on the hands using egocentric vision, categorizing the existing approaches into: localization (where are the hands or parts of them?); interpretation (what are the hands doing?); and application (e.g., systems that used egocentric hand cues for solving a specific problem). Moreover, a list of the most prominent datasets with hand-based annotations is provided.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Egocentric vision (a.k.a. first-person vision–FPV) applications have thrived over the past few years, thanks to the availability of affordable wearable cameras and large annotated datasets. The position of the wearable camera (usually mounted on the head) allows recording exactly what the camera wearers have in front of them, in particular hands and manipulated objects. This intrinsic advantage enables the study of the hands from multiple perspectives: localizing hands and their parts within the images; understanding what actions and activities the hands are involved in; and developing human-computer interfaces that rely on hand gestures. In this survey, we review the literature that focuses on the hands using egocentric vision, categorizing the existing approaches into: localization (where are the hands or parts of them?); interpretation (what are the hands doing?); and application (e.g., systems that used egocentric hand cues for solving a specific problem). Moreover, a list of the most prominent datasets with hand-based annotations is provided.",
"title": "Analysis of the Hands in Egocentric Vision: A Survey",
"normalizedTitle": "Analysis of the Hands in Egocentric Vision: A Survey",
"fno": "09064606",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Semantics",
"Cameras",
"Activity Recognition",
"Pose Estimation",
"Human Computer Interaction",
"Gesture Recognition",
"Taxonomy",
"Egocentric Vision",
"Computer Vision",
"Hand Detection",
"Hand Segmentation",
"Hand Pose Estimation",
"Hand Gesture Recognition",
"Grasp",
"Action Recognition",
"Activity Recognition",
"Human Computer Interaction"
],
"authors": [
{
"givenName": "Andrea",
"surname": "Bandini",
"fullName": "Andrea Bandini",
"affiliation": "KITE–Toronto Rehab–University Health Network, Toronto, ON, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "José",
"surname": "Zariffa",
"fullName": "José Zariffa",
"affiliation": "KITE–Toronto Rehab–University Health Network, Toronto, ON, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2023-06-01 00:00:00",
"pubType": "trans",
"pages": "6846-6866",
"year": "2023",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2015/8391/0/8391b949",
"title": "Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391b949/12OmNAm4TJU",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2009/3994/0/05204360",
"title": "Egocentric recognition of handled objects: Benchmark and analysis",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2009/05204360/12OmNzUxO8O",
"parentPublication": {
"id": "proceedings/cvprw/2009/3994/0",
"title": "2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000e710",
"title": "Analysis of Hand Segmentation in the Wild",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000e710/17D45W9KVIU",
"parentPublication": {
"id": "proceedings/cvpr/2018/6420/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200c300",
"title": "Anonymizing Egocentric Videos",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200c300/1BmHm8x3ZFC",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/percom-workshops/2022/1647/0/09767447",
"title": "Impacts of Image Obfuscation on Fine-grained Activity Recognition in Egocentric Video",
"doi": null,
"abstractUrl": "/proceedings-article/percom-workshops/2022/09767447/1Df8fOtqzks",
"parentPublication": {
"id": "proceedings/percom-workshops/2022/1647/0",
"title": "2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600d283",
"title": "Human Hands as Probes for Interactive Object Understanding",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600d283/1H1iDZIAPyU",
"parentPublication": {
"id": "proceedings/cvpr/2022/6946/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2018/8497/0/849700a040",
"title": "A Robust Method for Hands Gesture Recognition from Egocentric Depth Sensor",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2018/849700a040/1a3x7tWsXYI",
"parentPublication": {
"id": "proceedings/icvrv/2018/8497/0",
"title": "2018 International Conference on Virtual Reality and Visualization (ICVRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/06/09361177",
"title": "Multi-Dataset, Multitask Learning of Egocentric Vision Tasks",
"doi": null,
"abstractUrl": "/journal/tp/2023/06/09361177/1rsey0Ug7yE",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2021/0477/0/047700d398",
"title": "Whose hand is this? Person Identification from Egocentric Hand Gestures",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700d398/1uqGtwkoNuU",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/06/09591443",
"title": "Leveraging Hand-Object Interactions in Assistive Egocentric Vision",
"doi": null,
"abstractUrl": "/journal/tp/2023/06/09591443/1y2FeBkscta",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09562265",
"articleId": "1xtOoRYTrG0",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "10120667",
"articleId": "1MTPbTTYPKw",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1D80ZaZz94I",
"title": "June",
"year": "2022",
"issueNum": "06",
"idPrefix": "tp",
"pubType": "journal",
"volume": "44",
"label": "June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1qdT3YKBd5u",
"doi": "10.1109/TPAMI.2021.3050124",
"abstract": "Full projector compensation aims to modify a projector input image to compensate for both geometric and photometric disturbance of the projection surface. Traditional methods usually solve the two parts separately and may suffer from suboptimal solutions. In this paper, we propose the first end-to-end differentiable solution, named CompenNeSt++, to solve the two problems jointly. First, we propose a novel geometric correction subnet, named WarpingNet, which is designed with a cascaded coarse-to-fine structure to learn the sampling grid directly from sampling images. Second, we propose a novel photometric compensation subnet, named CompenNeSt, which is designed with a siamese architecture to capture the photometric interactions between the projection surface and the projected images, and to use such information to compensate the geometrically corrected images. By concatenating WarpingNet with CompenNeSt, CompenNeSt++ accomplishes full projector compensation and is end-to-end trainable. Third, to improve practicability, we propose a novel synthetic data-based pre-training strategy to significantly reduce the number of training images and training time. Moreover, we construct the first setup-independent full compensation benchmark to facilitate future studies. In thorough experiments, our method shows clear advantages over prior art with promising compensation quality and meanwhile being practically convenient.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Full projector compensation aims to modify a projector input image to compensate for both geometric and photometric disturbance of the projection surface. Traditional methods usually solve the two parts separately and may suffer from suboptimal solutions. In this paper, we propose the first end-to-end differentiable solution, named CompenNeSt++, to solve the two problems jointly. First, we propose a novel geometric correction subnet, named WarpingNet, which is designed with a cascaded coarse-to-fine structure to learn the sampling grid directly from sampling images. Second, we propose a novel photometric compensation subnet, named CompenNeSt, which is designed with a siamese architecture to capture the photometric interactions between the projection surface and the projected images, and to use such information to compensate the geometrically corrected images. By concatenating WarpingNet with CompenNeSt, CompenNeSt++ accomplishes full projector compensation and is end-to-end trainable. Third, to improve practicability, we propose a novel synthetic data-based pre-training strategy to significantly reduce the number of training images and training time. Moreover, we construct the first setup-independent full compensation benchmark to facilitate future studies. In thorough experiments, our method shows clear advantages over prior art with promising compensation quality and meanwhile being practically convenient.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Full projector compensation aims to modify a projector input image to compensate for both geometric and photometric disturbance of the projection surface. Traditional methods usually solve the two parts separately and may suffer from suboptimal solutions. In this paper, we propose the first end-to-end differentiable solution, named CompenNeSt++, to solve the two problems jointly. First, we propose a novel geometric correction subnet, named WarpingNet, which is designed with a cascaded coarse-to-fine structure to learn the sampling grid directly from sampling images. Second, we propose a novel photometric compensation subnet, named CompenNeSt, which is designed with a siamese architecture to capture the photometric interactions between the projection surface and the projected images, and to use such information to compensate the geometrically corrected images. By concatenating WarpingNet with CompenNeSt, CompenNeSt++ accomplishes full projector compensation and is end-to-end trainable. Third, to improve practicability, we propose a novel synthetic data-based pre-training strategy to significantly reduce the number of training images and training time. Moreover, we construct the first setup-independent full compensation benchmark to facilitate future studies. In thorough experiments, our method shows clear advantages over prior art with promising compensation quality and meanwhile being practically convenient.",
"title": "End-to-End Full Projector Compensation",
"normalizedTitle": "End-to-End Full Projector Compensation",
"fno": "09318552",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Computer Vision",
"Feature Extraction",
"Image Recognition",
"Image Reconstruction",
"Image Representation",
"Image Sampling",
"Image Sensors",
"Learning Artificial Intelligence",
"Neural Nets",
"Object Detection",
"Optical Projectors",
"Full Projector Compensation Aims",
"Projector Input Image",
"Geometric Disturbance",
"Photometric Disturbance",
"Projection Surface",
"Suboptimal Solutions",
"End To End Differentiable Solution",
"Named Compen Ne St",
"Geometric Correction Subnet",
"Named Warping Net",
"Coarse To Fine Structure",
"Sampling Grid",
"Photometric Compensation Subnet",
"Photometric Interactions",
"Projected Images",
"Geometrically",
"Accomplishes Full Projector Compensation",
"Novel Synthetic Data Based Pre Training Strategy",
"Training Images",
"Compensation Benchmark",
"Compensation Quality",
"Surface Texture",
"Cameras",
"Training",
"Benchmark Testing",
"Geometry",
"Task Analysis",
"Pipelines",
"Projector Compensation",
"Projector Camera Systems",
"Image Warping",
"Image Enhancement"
],
"authors": [
{
"givenName": "Bingyao",
"surname": "Huang",
"fullName": "Bingyao Huang",
"affiliation": "Department of Computer Science, Stony Brook University, Stony Brook, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tao",
"surname": "Sun",
"fullName": "Tao Sun",
"affiliation": "Department of Computer Science, Stony Brook University, Stony Brook, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haibin",
"surname": "Ling",
"fullName": "Haibin Ling",
"affiliation": "Department of Computer Science, Stony Brook University, Stony Brook, NY, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2022-06-01 00:00:00",
"pubType": "trans",
"pages": "2953-2967",
"year": "2022",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cvprw/2013/4990/0/4990a924",
"title": "Practical Non-linear Photometric Projector Compensation",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2013/4990a924/12OmNBQkwYN",
"parentPublication": {
"id": "proceedings/cvprw/2013/4990/0",
"title": "2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2008/2840/0/04637343",
"title": "A practical radiometric compensation method for projector-based augmentation",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2008/04637343/12OmNBp52JR",
"parentPublication": {
"id": "proceedings/ismar/2008/2840/0",
"title": "2008 7th IEEE/ACM International Symposium on Mixed and Augmented Reality",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2006/2646/0/26460006",
"title": "Robust Content-Dependent Photometric Projector Compensation",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2006/26460006/12OmNzYNN6k",
"parentPublication": {
"id": "proceedings/cvprw/2006/2646/0",
"title": "2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2008/10/ttp2008101831",
"title": "Robust and Accurate Visual Echo Cancelation in a Full-duplex Projector-Camera System",
"doi": null,
"abstractUrl": "/journal/tp/2008/10/ttp2008101831/13rRUxjQyip",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cost/2022/6248/0/624800a180",
"title": "Review of Photometric Compensation in Projection System",
"doi": null,
"abstractUrl": "/proceedings-article/cost/2022/624800a180/1H2pilDW8ww",
"parentPublication": {
"id": "proceedings/cost/2022/6248/0",
"title": "2022 International Conference on Culture-Oriented Science and Technology (CoST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2023/4815/0/481500a449",
"title": "Extended Depth-of-Field Projector using Learned Diffractive Optics",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2023/481500a449/1MNgNe272U0",
"parentPublication": {
"id": "proceedings/vr/2023/4815/0",
"title": "2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2023/4815/0/481500a135",
"title": "CompenHR: Efficient Full Compensation for High-resolution Projector",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2023/481500a135/1MNgmceltOU",
"parentPublication": {
"id": "proceedings/vr/2023/4815/0",
"title": "2023 IEEE Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2019/3293/0/329300g803",
"title": "End-To-End Projector Photometric Compensation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2019/329300g803/1gyraGpeGyY",
"parentPublication": {
"id": "proceedings/cvpr/2019/3293/0",
"title": "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300h164",
"title": "CompenNet++: End-to-End Full Projector Compensation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300h164/1hQqyKnlCEM",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/05/09382896",
"title": "DeProCams: Simultaneous Relighting, Compensation and Shape Reconstruction for Projector-Camera Systems",
"doi": null,
"abstractUrl": "/journal/tg/2021/05/09382896/1saZvVKgpFK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09328280",
"articleId": "1qutSSnI5HO",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09328198",
"articleId": "1qutR6kaNSU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNCbCrUN",
"title": "Dec.",
"year": "2013",
"issueNum": "12",
"idPrefix": "tg",
"pubType": "journal",
"volume": "19",
"label": "Dec.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwh80Hb",
"doi": "10.1109/TVCG.2013.137",
"abstract": "Domain-specific database applications tend to contain a sizable number of table-, form-, and report-style views that must each be designed and maintained by a software developer. A significant part of this job is the necessary tweaking of low-level presentation details such as label placements, text field dimensions, list or table styles, and so on. In this paper, we present a horizontally constrained layout management algorithm that automates the display of structured hierarchical data using the traditional visual idioms of hand-designed database UIs: tables, multi-column forms, and outline-style indented lists. We compare our system with pure outline and nested table layouts with respect to space efficiency and readability, the latter with an online user study on 27 subjects. Our layouts are 3.9 and 1.6 times more compact on average than outline layouts and horizontally unconstrained table layouts, respectively, and are as readable as table layouts even for large datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Domain-specific database applications tend to contain a sizable number of table-, form-, and report-style views that must each be designed and maintained by a software developer. A significant part of this job is the necessary tweaking of low-level presentation details such as label placements, text field dimensions, list or table styles, and so on. In this paper, we present a horizontally constrained layout management algorithm that automates the display of structured hierarchical data using the traditional visual idioms of hand-designed database UIs: tables, multi-column forms, and outline-style indented lists. We compare our system with pure outline and nested table layouts with respect to space efficiency and readability, the latter with an online user study on 27 subjects. Our layouts are 3.9 and 1.6 times more compact on average than outline layouts and horizontally unconstrained table layouts, respectively, and are as readable as table layouts even for large datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Domain-specific database applications tend to contain a sizable number of table-, form-, and report-style views that must each be designed and maintained by a software developer. A significant part of this job is the necessary tweaking of low-level presentation details such as label placements, text field dimensions, list or table styles, and so on. In this paper, we present a horizontally constrained layout management algorithm that automates the display of structured hierarchical data using the traditional visual idioms of hand-designed database UIs: tables, multi-column forms, and outline-style indented lists. We compare our system with pure outline and nested table layouts with respect to space efficiency and readability, the latter with an online user study on 27 subjects. Our layouts are 3.9 and 1.6 times more compact on average than outline layouts and horizontally unconstrained table layouts, respectively, and are as readable as table layouts even for large datasets.",
"title": "Automatic Layout of Structured Hierarchical Reports",
"normalizedTitle": "Automatic Layout of Structured Hierarchical Reports",
"fno": "ttg2013122586",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Layout",
"Data Visualization",
"XML",
"Nested Relations",
"Layout",
"Data Visualization",
"XML",
"Layout Management",
"Hierarchy Data",
"Tabular Data"
],
"authors": [
{
"givenName": "Eirik",
"surname": "Bakke",
"fullName": "Eirik Bakke",
"affiliation": "Comput. Sci. & Artificial Intell. Lab. (CSAIL), MIT, Cambridge, MA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "David R.",
"surname": "Karger",
"fullName": "David R. Karger",
"affiliation": "Comput. Sci. & Artificial Intell. Lab. (CSAIL), MIT, Cambridge, MA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Robert C.",
"surname": "Miller",
"fullName": "Robert C. Miller",
"affiliation": "Comput. Sci. & Artificial Intell. Lab. (CSAIL), MIT, Cambridge, MA, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "12",
"pubDate": "2013-12-01 00:00:00",
"pubType": "trans",
"pages": "2586-2595",
"year": "2013",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/edac/1990/2024/0/00136677",
"title": "Hierarchical layout verification for submicron designs",
"doi": null,
"abstractUrl": "/proceedings-article/edac/1990/00136677/12OmNqNos8Z",
"parentPublication": {
"id": "proceedings/edac/1990/2024/0",
"title": "Proceedings of the European Design Automation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2017/5738/0/08031595",
"title": "Visualizing the uncertainty induced by graph layout algorithms",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2017/08031595/12OmNs0C9DQ",
"parentPublication": {
"id": "proceedings/pacificvis/2017/5738/0",
"title": "2017 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cad-graphics/2015/8020/0/07450427",
"title": "Facade Layout Symmetrization",
"doi": null,
"abstractUrl": "/proceedings-article/cad-graphics/2015/07450427/12OmNviHKiH",
"parentPublication": {
"id": "proceedings/cad-graphics/2015/8020/0",
"title": "2015 14th International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2017/0831/0/0831a224",
"title": "Node Overlap Removal for 1D Graph Layout",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2017/0831a224/12OmNxuXczJ",
"parentPublication": {
"id": "proceedings/iv/2017/0831/0",
"title": "2017 21st International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/arvlsid/1995/7047/0/70470185",
"title": "HAL: heuristic algorithms for layout synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/arvlsid/1995/70470185/12OmNyRxFp4",
"parentPublication": {
"id": "proceedings/arvlsid/1995/7047/0",
"title": "Advanced Research in VLSI, Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dac/1995/725/0/01586714",
"title": "Automatic Layout Synthesis of Leaf Cells",
"doi": null,
"abstractUrl": "/proceedings-article/dac/1995/01586714/12OmNylKAXO",
"parentPublication": {
"id": "proceedings/dac/1995/725/0",
"title": "32nd Design Automation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vlhcc/2013/0369/0/06645264",
"title": "Framework for automatic generation of graphical layout compatible with multiple platforms",
"doi": null,
"abstractUrl": "/proceedings-article/vlhcc/2013/06645264/12OmNzV70N8",
"parentPublication": {
"id": "proceedings/vlhcc/2013/0369/0",
"title": "2013 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2011/01/ttg2011010101",
"title": "Automatic Metro Map Layout Using Multicriteria Optimization",
"doi": null,
"abstractUrl": "/journal/tg/2011/01/ttg2011010101/13rRUx0xPIA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08805452",
"title": "A Deep Generative Model for Graph Layout",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08805452/1cG4LsVN2zS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552233",
"title": "Automatic Polygon Layout for Primal-Dual Visualization of Hypergraphs",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552233/1xic56YNRyU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttg2013122576",
"articleId": "13rRUwjoNx3",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttg2013122596",
"articleId": "13rRUwjXZSf",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "17ShDTXnFtp",
"name": "ttg2013122586s.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg2013122586s.mp4",
"extension": "mp4",
"size": "47.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNAGepWJ",
"title": "Oct.",
"year": "2015",
"issueNum": "10",
"idPrefix": "tg",
"pubType": "journal",
"volume": "21",
"label": "Oct.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUEgs2M5",
"doi": "10.1109/TVCG.2015.2417572",
"abstract": "Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Computing distance fields is fundamental to many scientific and engineering applications. Distance fields can be used to direct analysis and reduce data. In this paper, we present a highly scalable method for computing 3D distance fields on massively parallel distributed-memory machines. A new distributed spatial data structure, named parallel distance tree, is introduced to manage the level sets of data and facilitate surface tracking over time, resulting in significantly reduced computation and communication costs for calculating the distance to the surface of interest from any spatial locations. Our method supports several data types and distance metrics from real-world applications. We demonstrate its efficiency and scalability on state-of-the-art supercomputers using both large-scale volume datasets and surface models. We also demonstrate in-situ distance field computation on dynamic turbulent flame surfaces for a petascale combustion simulation. Our work greatly extends the usability of distance fields for demanding applications.",
"title": "Scalable Parallel Distance Field Construction for Large-Scale Applications",
"normalizedTitle": "Scalable Parallel Distance Field Construction for Large-Scale Applications",
"fno": "07072474",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Program Processors",
"Octrees",
"Computational Modeling",
"Data Models",
"Three Dimensional Displays",
"Surface Treatment",
"Large Scale Scientific Data Analytics And Visualization",
"Distance Field",
"In Situ Processing",
"Parallel Algorithms",
"Scalability",
"Spatial Data Structures",
"Scientific Simulations",
"Geometric Modeling"
],
"authors": [
{
"givenName": "Hongfeng",
"surname": "Yu",
"fullName": "Hongfeng Yu",
"affiliation": ", University of Nebraska-Lincoln, Lincoln, NE, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jinrong",
"surname": "Xie",
"fullName": "Jinrong Xie",
"affiliation": ", University of California-Davis, Davis, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Kwan-Liu",
"surname": "Ma",
"fullName": "Kwan-Liu Ma",
"affiliation": ", University of California-Davis, Davis, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hemanth",
"surname": "Kolla",
"fullName": "Hemanth Kolla",
"affiliation": ", Sandia National Laboratories, Albuquerque, NM, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jacqueline H.",
"surname": "Chen",
"fullName": "Jacqueline H. Chen",
"affiliation": ", Sandia National Laboratories, Albuquerque, NM, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "10",
"pubDate": "2015-10-01 00:00:00",
"pubType": "trans",
"pages": "1187-1200",
"year": "2015",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/sibgrapi/2010/8420/0/05720356",
"title": "Geotextures: A Multi-source Geodesic Distance Field Approach for Procedural Texturing of Complex Meshes",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2010/05720356/12OmNBOUxso",
"parentPublication": {
"id": "proceedings/sibgrapi/2010/8420/0",
"title": "2010 23rd SIBGRAPI Conference on Graphics, Patterns and Images",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2015/9711/0/5720a157",
"title": "Incremental Division of Very Large Point Clouds for Scalable 3D Surface Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2015/5720a157/12OmNvT2p0I",
"parentPublication": {
"id": "proceedings/iccvw/2015/9711/0",
"title": "2015 IEEE International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2001/7200/0/7200huang",
"title": "A Complete Distance Field Representation",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2001/7200huang/12OmNxeutbu",
"parentPublication": {
"id": "proceedings/ieee-vis/2001/7200/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/2014/5500/0/5500b008",
"title": "Scalable Computation of Stream Surfaces on Large Scale Vector Fields",
"doi": null,
"abstractUrl": "/proceedings-article/sc/2014/5500b008/12OmNzXFoId",
"parentPublication": {
"id": "proceedings/sc/2014/5500/0",
"title": "SC14: International Conference for High Performance Computing, Networking, Storage and Analysis",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/08/07239614",
"title": "Multiphase Interface Tracking with Fast Semi-Lagrangian Contouring",
"doi": null,
"abstractUrl": "/journal/tg/2016/08/07239614/13rRUwInvfd",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/1992/01/mcg1992010065",
"title": "Distance Field Manipulation of Surface Models",
"doi": null,
"abstractUrl": "/magazine/cg/1992/01/mcg1992010065/13rRUwbaqNK",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09839681",
"title": "SSRNet: Scalable 3D Surface Reconstruction Network",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09839681/1FisL8u19du",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/candar/2022/7530/0/753000a019",
"title": "A Recurrence for the Surface Area of the (<tex>Z_$n, k$_Z</tex>)-Star Graph",
"doi": null,
"abstractUrl": "/proceedings-article/candar/2022/753000a019/1KBqN3Dj3y0",
"parentPublication": {
"id": "proceedings/candar/2022/7530/0",
"title": "2022 Tenth International Symposium on Computing and Networking (CANDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv-2/2019/2850/0/285000a160",
"title": "Hybrid Polygon-Point Rendering of Singular and Non-Manifold Implicit Surfaces",
"doi": null,
"abstractUrl": "/proceedings-article/iv-2/2019/285000a160/1cMEQnNfRXG",
"parentPublication": {
"id": "proceedings/iv-2/2019/2850/0",
"title": "2019 23rd International Conference in Information Visualization – Part II",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800a967",
"title": "SSRNet: Scalable 3D Surface Reconstruction Network",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800a967/1m3nKc80MlG",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07089294",
"articleId": "13rRUxjyX42",
"__typename": "AdjacentArticleType"
},
"next": null,
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1qLhZwxtEmA",
"title": "March",
"year": "2021",
"issueNum": "03",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "March",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1oCjmNa9g2c",
"doi": "10.1109/TVCG.2020.3036153",
"abstract": "Surface meshes associated with diffuse texture or color attributes are becoming popular multimedia contents. They provide a high degree of realism and allow six degrees of freedom (6DoF) interactions in immersive virtual reality environments. Just like other types of multimedia, 3D meshes are subject to a wide range of processing, e.g., simplification and compression, which result in a loss of quality of the final rendered scene. Thus, both subjective studies and objective metrics are needed to understand and predict this visual loss. In this work, we introduce a large dataset of 480 animated meshes with diffuse color information, and associated with perceived quality judgments. The stimuli were generated from 5 source models subjected to geometry and color distortions. Each stimulus was associated with 6 hypothetical rendering trajectories (HRTs): combinations of 3 viewpoints and 2 animations. A total of 11520 quality judgments (24 per stimulus) were acquired in a subjective experiment conducted in virtual reality. The results allowed us to explore the influence of source models, animations and viewpoints on both the quality scores and their confidence intervals. Based on these findings, we propose the first metric for quality assessment of 3D meshes with diffuse colors, which works entirely on the mesh domain. This metric incorporates perceptually-relevant curvature-based and color-based features. We evaluate its performance, as well as a number of Image Quality Metrics (IQMs), on two datasets: ours and a dataset of distorted textured meshes. Our metric demonstrates good results and a better stability than IQMs. Finally, we investigated how the knowledge of the viewpoint (i.e., the visible parts of the 3D model) may improve the results of objective metrics.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Surface meshes associated with diffuse texture or color attributes are becoming popular multimedia contents. They provide a high degree of realism and allow six degrees of freedom (6DoF) interactions in immersive virtual reality environments. Just like other types of multimedia, 3D meshes are subject to a wide range of processing, e.g., simplification and compression, which result in a loss of quality of the final rendered scene. Thus, both subjective studies and objective metrics are needed to understand and predict this visual loss. In this work, we introduce a large dataset of 480 animated meshes with diffuse color information, and associated with perceived quality judgments. The stimuli were generated from 5 source models subjected to geometry and color distortions. Each stimulus was associated with 6 hypothetical rendering trajectories (HRTs): combinations of 3 viewpoints and 2 animations. A total of 11520 quality judgments (24 per stimulus) were acquired in a subjective experiment conducted in virtual reality. The results allowed us to explore the influence of source models, animations and viewpoints on both the quality scores and their confidence intervals. Based on these findings, we propose the first metric for quality assessment of 3D meshes with diffuse colors, which works entirely on the mesh domain. This metric incorporates perceptually-relevant curvature-based and color-based features. We evaluate its performance, as well as a number of Image Quality Metrics (IQMs), on two datasets: ours and a dataset of distorted textured meshes. Our metric demonstrates good results and a better stability than IQMs. Finally, we investigated how the knowledge of the viewpoint (i.e., the visible parts of the 3D model) may improve the results of objective metrics.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Surface meshes associated with diffuse texture or color attributes are becoming popular multimedia contents. They provide a high degree of realism and allow six degrees of freedom (6DoF) interactions in immersive virtual reality environments. Just like other types of multimedia, 3D meshes are subject to a wide range of processing, e.g., simplification and compression, which result in a loss of quality of the final rendered scene. Thus, both subjective studies and objective metrics are needed to understand and predict this visual loss. In this work, we introduce a large dataset of 480 animated meshes with diffuse color information, and associated with perceived quality judgments. The stimuli were generated from 5 source models subjected to geometry and color distortions. Each stimulus was associated with 6 hypothetical rendering trajectories (HRTs): combinations of 3 viewpoints and 2 animations. A total of 11520 quality judgments (24 per stimulus) were acquired in a subjective experiment conducted in virtual reality. The results allowed us to explore the influence of source models, animations and viewpoints on both the quality scores and their confidence intervals. Based on these findings, we propose the first metric for quality assessment of 3D meshes with diffuse colors, which works entirely on the mesh domain. This metric incorporates perceptually-relevant curvature-based and color-based features. We evaluate its performance, as well as a number of Image Quality Metrics (IQMs), on two datasets: ours and a dataset of distorted textured meshes. Our metric demonstrates good results and a better stability than IQMs. Finally, we investigated how the knowledge of the viewpoint (i.e., the visible parts of the 3D model) may improve the results of objective metrics.",
"title": "Visual Quality of 3D Meshes With Diffuse Colors in Virtual Reality: Subjective and Objective Evaluation",
"normalizedTitle": "Visual Quality of 3D Meshes With Diffuse Colors in Virtual Reality: Subjective and Objective Evaluation",
"fno": "09252120",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computational Geometry",
"Computer Animation",
"Image Colour Analysis",
"Image Texture",
"Mesh Generation",
"Rendering Computer Graphics",
"Virtual Reality",
"Visual Quality",
"3 D Meshes",
"Diffuse Colors",
"Subjective Evaluation",
"Objective Evaluation",
"Surface Meshes",
"Diffuse Texture",
"Popular Multimedia Contents",
"6 Do F",
"Immersive Virtual Reality Environments",
"Compression",
"Rendered Scene",
"Objective Metrics",
"Animated Meshes",
"Color Information",
"Perceived Quality Judgments",
"Geometry",
"Color Distortions",
"Hypothetical Rendering Trajectories",
"Quality Judgments",
"Animations",
"Quality Scores",
"Quality Assessment",
"Mesh Domain",
"Image Quality Metrics",
"Distorted Textured Meshes",
"Perceptually Relevant Curvature",
"Three Dimensional Displays",
"Measurement",
"Image Color Analysis",
"Distortion",
"Solid Modeling",
"Quality Assessment",
"Geometry",
"Computer Graphics",
"Perception",
"Virtual Reality",
"Diffuse Color",
"3 D Mesh",
"Visual Quality Assessment",
"Subjective Quality Evaluation",
"Objective Quality Evaluation",
"Dataset",
"Perceptual Metric"
],
"authors": [
{
"givenName": "Yana",
"surname": "Nehmé",
"fullName": "Yana Nehmé",
"affiliation": "CNRS, LIRIS, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Florent",
"surname": "Dupont",
"fullName": "Florent Dupont",
"affiliation": "CNRS, LIRIS, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jean-Philippe",
"surname": "Farrugia",
"fullName": "Jean-Philippe Farrugia",
"affiliation": "CNRS, LIRIS, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Patrick",
"surname": "Le Callet",
"fullName": "Patrick Le Callet",
"affiliation": "CNRS, LS2N, France",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Guillaume",
"surname": "Lavoué",
"fullName": "Guillaume Lavoué",
"affiliation": "CNRS, LIRIS, France",
"__typename": "ArticleAuthorType"
}
],
"replicability": {
"isEnabled": true,
"codeDownloadUrl": "https://github.com/YanaNEHME/Visual_Quality_of_3D_Meshes_with_Diffuse_Colors_in_VR.git",
"codeRepositoryUrl": "https://github.com/YanaNEHME/Visual_Quality_of_3D_Meshes_with_Diffuse_Colors_in_VR",
"__typename": "ArticleReplicabilityType"
},
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "03",
"pubDate": "2021-03-01 00:00:00",
"pubType": "trans",
"pages": "2202-2219",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icme/2017/6067/0/08019470",
"title": "Learning-based objective evaluation of 3D human open meshes",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2017/08019470/12OmNviZlu5",
"parentPublication": {
"id": "proceedings/icme/2017/6067/0",
"title": "2017 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/nbis/2010/4167/0/4167a345",
"title": "Subjective Quality Assessments in Virtual Environments",
"doi": null,
"abstractUrl": "/proceedings-article/nbis/2010/4167a345/12OmNxTmHIg",
"parentPublication": {
"id": "proceedings/nbis/2010/4167/0",
"title": "2010 13th International Conference on Network-Based Information Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccp/2015/8667/0/07168375",
"title": "Single-Shot Reflectance Measurement from Polarized Color Gradient Illumination",
"doi": null,
"abstractUrl": "/proceedings-article/iccp/2015/07168375/12OmNxWLTsI",
"parentPublication": {
"id": "proceedings/iccp/2015/8667/0",
"title": "2015 IEEE International Conference on Computational Photography (ICCP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pbg/2005/20/0/01500326",
"title": "Conversion of point-sampled models to textured meshes",
"doi": null,
"abstractUrl": "/proceedings-article/pbg/2005/01500326/12OmNxzMnLl",
"parentPublication": {
"id": "proceedings/pbg/2005/20/0",
"title": "Point-Based Graphics 2005",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2017/6067/0/08019494",
"title": "A new combined PSNR for objective video quality assessment",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2017/08019494/12OmNyuy9PP",
"parentPublication": {
"id": "proceedings/icme/2017/6067/0",
"title": "2017 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2013/3022/0/3022a891",
"title": "Separating Specular and Diffuse Reflection Components in the HSI Color Space",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2013/3022a891/12OmNz6Apcw",
"parentPublication": {
"id": "proceedings/iccvw/2013/3022/0",
"title": "2013 IEEE International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2007/01/04015405",
"title": "Streaming Simplification of Tetrahedral Meshes",
"doi": null,
"abstractUrl": "/journal/tg/2007/01/04015405/13rRUyY28Yk",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600n3482",
"title": "Text2Mesh: Text-Driven Neural Stylization for Meshes",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600n3482/1H1hBnpgbAI",
"parentPublication": {
"id": "proceedings/cvpr/2022/6946/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2023/9346/0/934600c548",
"title": "Separating Partially-Polarized Diffuse and Specular Reflection Components under Unpolarized Light Sources",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600c548/1KxVkSYWbxC",
"parentPublication": {
"id": "proceedings/wacv/2023/9346/0",
"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmew/2021/4989/0/09455963",
"title": "A No-Reference Visual Quality Metric For 3D Color Meshes",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2021/09455963/1uCgrVwWrbq",
"parentPublication": {
"id": "proceedings/icmew/2021/4989/0",
"title": "2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08827957",
"articleId": "1ddbhyEXGWA",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08827956",
"articleId": "1ddbibDGunS",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1qLi0Agt3GM",
"name": "ttg202103-09252120s1-tvcg-3036153-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202103-09252120s1-tvcg-3036153-mm.zip",
"extension": "zip",
"size": "613 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzn38Js",
"title": "Oct.",
"year": "2020",
"issueNum": "10",
"idPrefix": "tp",
"pubType": "journal",
"volume": "42",
"label": "Oct.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1bIeDhBWhLW",
"doi": "10.1109/TPAMI.2019.2928296",
"abstract": "We propose DoubleFusion, a new real-time system that combines volumetric non-rigid reconstruction with data-driven template fitting to simultaneously reconstruct detailed surface geometry, large non-rigid motion and the optimized human body shape from a single depth camera. One of the key contributions of this method is a double-layer representation consisting of a complete parametric body model inside, and a gradually fused detailed surface outside. A pre-defined node graph on the body parameterizes the non-rigid deformations near the body, and a free-form dynamically changing graph parameterizes the outer surface layer far from the body, which allows more general reconstruction. We further propose a joint motion tracking method based on the double-layer representation to enable robust and fast motion tracking performance. Moreover, the inner parametric body is optimized online and forced to fit inside the outer surface layer as well as the live depth input. Overall, our method enables increasingly denoised, detailed and complete surface reconstructions, fast motion tracking performance and plausible inner body shape reconstruction in real-time. Experiments and comparisons show improved fast motion tracking and loop closure performance on more challenging scenarios. Two extended applications including body measurement and shape retargeting show the potential of our system in terms of practical use.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose DoubleFusion, a new real-time system that combines volumetric non-rigid reconstruction with data-driven template fitting to simultaneously reconstruct detailed surface geometry, large non-rigid motion and the optimized human body shape from a single depth camera. One of the key contributions of this method is a double-layer representation consisting of a complete parametric body model inside, and a gradually fused detailed surface outside. A pre-defined node graph on the body parameterizes the non-rigid deformations near the body, and a free-form dynamically changing graph parameterizes the outer surface layer far from the body, which allows more general reconstruction. We further propose a joint motion tracking method based on the double-layer representation to enable robust and fast motion tracking performance. Moreover, the inner parametric body is optimized online and forced to fit inside the outer surface layer as well as the live depth input. Overall, our method enables increasingly denoised, detailed and complete surface reconstructions, fast motion tracking performance and plausible inner body shape reconstruction in real-time. Experiments and comparisons show improved fast motion tracking and loop closure performance on more challenging scenarios. Two extended applications including body measurement and shape retargeting show the potential of our system in terms of practical use.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose DoubleFusion, a new real-time system that combines volumetric non-rigid reconstruction with data-driven template fitting to simultaneously reconstruct detailed surface geometry, large non-rigid motion and the optimized human body shape from a single depth camera. One of the key contributions of this method is a double-layer representation consisting of a complete parametric body model inside, and a gradually fused detailed surface outside. A pre-defined node graph on the body parameterizes the non-rigid deformations near the body, and a free-form dynamically changing graph parameterizes the outer surface layer far from the body, which allows more general reconstruction. We further propose a joint motion tracking method based on the double-layer representation to enable robust and fast motion tracking performance. Moreover, the inner parametric body is optimized online and forced to fit inside the outer surface layer as well as the live depth input. Overall, our method enables increasingly denoised, detailed and complete surface reconstructions, fast motion tracking performance and plausible inner body shape reconstruction in real-time. Experiments and comparisons show improved fast motion tracking and loop closure performance on more challenging scenarios. Two extended applications including body measurement and shape retargeting show the potential of our system in terms of practical use.",
"title": "DoubleFusion: Real-Time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor",
"normalizedTitle": "DoubleFusion: Real-Time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor",
"fno": "08762161",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Cameras",
"Geometry",
"Graph Theory",
"Image Motion Analysis",
"Image Reconstruction",
"Image Sequences",
"Medical Image Processing",
"Motion Estimation",
"Object Tracking",
"Pose Estimation",
"Solid Modelling",
"Video Signal Processing",
"Single Depth Camera",
"Key Contributions",
"Double Layer Representation",
"Complete Parametric Body Model",
"Gradually Fused Detailed Surface Outside",
"Pre Defined Node Graph",
"Nonrigid Deformations",
"Outer Surface Layer",
"General Reconstruction",
"Joint Motion",
"Fast Motion Tracking Performance",
"Inner Parametric Body",
"Live Depth Input",
"Complete Surface Reconstructions",
"Plausible Inner Body Shape Reconstruction",
"Loop Closure Performance",
"Extended Applications Including Body Measurement",
"Shape Retargeting",
"Optimized Human Body Shape",
"Nonrigid Motion",
"Detailed Surface Geometry",
"Nonrigid Reconstruction",
"Real Time System",
"Single Depth Sensor",
"Inner Body Shapes",
"Human Performances",
"Real Time Capture",
"Double Fusion",
"Shape",
"Surface Reconstruction",
"Real Time Systems",
"Tracking",
"Strain",
"Cameras",
"Skeleton",
"RGBD Sensor",
"Human Performance Capture",
"Human Shape Reconstruction",
"Real Time"
],
"authors": [
{
"givenName": "Tao",
"surname": "Yu",
"fullName": "Tao Yu",
"affiliation": "School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jianhui",
"surname": "Zhao",
"fullName": "Jianhui Zhao",
"affiliation": "School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zerong",
"surname": "Zheng",
"fullName": "Zerong Zheng",
"affiliation": "Department of Automation, Broadband Network & Digital Media Lab, Tsinghua University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Kaiwen",
"surname": "Guo",
"fullName": "Kaiwen Guo",
"affiliation": "Google Inc, San Francisco, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Qionghai",
"surname": "Dai",
"fullName": "Qionghai Dai",
"affiliation": "Department of Automation, Broadband Network & Digital Media Lab, Tsinghua University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hao",
"surname": "Li",
"fullName": "Hao Li",
"affiliation": "Institute for Creative Technologies, University of Southern California, Los Angeles, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gerard",
"surname": "Pons-Moll",
"fullName": "Gerard Pons-Moll",
"affiliation": "Max-Planck Institute for Informatics, Saarbrucken, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yebin",
"surname": "Liu",
"fullName": "Yebin Liu",
"affiliation": "Department of Automation, Broadband Network & Digital Media Lab, Tsinghua University, Beijing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "10",
"pubDate": "2020-10-01 00:00:00",
"pubType": "trans",
"pages": "2523-2539",
"year": "2020",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2015/8391/0/8391d083",
"title": "Robust Non-rigid Motion Tracking and Surface Reconstruction Using L0 Regularization",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391d083/12OmNB9KHwl",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2007/1016/0/04284846",
"title": "Model-Based Markerless Human Body Motion Capture using Multiple Cameras",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2007/04284846/12OmNvmXJ37",
"parentPublication": {
"id": "proceedings/icme/2007/1016/0",
"title": "2007 International Conference on Multimedia & Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2016/5407/0/5407a166",
"title": "Model-Based Outdoor Performance Capture",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2016/5407a166/12OmNwDSdg1",
"parentPublication": {
"id": "proceedings/3dv/2016/5407/0",
"title": "2016 Fourth International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2009/3992/0/05206755",
"title": "Motion capture using joint skeleton tracking and surface estimation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2009/05206755/12OmNwpoFGg",
"parentPublication": {
"id": "proceedings/cvpr/2009/3992/0",
"title": "2009 IEEE Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2017/1032/0/1032a910",
"title": "BodyFusion: Real-Time Capture of Human Motion and Surface Geometry Using a Single Depth Camera",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/1032a910/12OmNzT7Otl",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/05/07888591",
"title": "Robust Non-Rigid Motion Tracking and Surface Reconstruction Using Z_$L_0$_Z Regularization",
"doi": null,
"abstractUrl": "/journal/tg/2018/05/07888591/13rRUILtJqX",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/08/07983006",
"title": "FlyCap: Markerless Motion Capture Using Multiple Autonomous Flying Cameras",
"doi": null,
"abstractUrl": "/journal/tg/2018/08/07983006/13rRUxYrbUO",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000h287",
"title": "DoubleFusion: Real-Time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000h287/17D45VsBTWf",
"parentPublication": {
"id": "proceedings/cvpr/2018/6420/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2018/8425/0/842500a042",
"title": "Patch-Based Non-rigid 3D Reconstruction from a Single Depth Stream",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2018/842500a042/17D45WGGoME",
"parentPublication": {
"id": "proceedings/3dv/2018/8425/0",
"title": "2018 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093533",
"title": "Robust Template-Based Non-Rigid Motion Tracking Using Local Coordinate Regularization",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093533/1jPbs0rPdC0",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08708933",
"articleId": "19Q3hT6JyUg",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08732396",
"articleId": "1aDQpnTqak0",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1y2FkV9ZFKM",
"title": "Nov.",
"year": "2021",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1wpqlQWCIxy",
"doi": "10.1109/TVCG.2021.3106429",
"abstract": "We present a CPU-based real-time cloth animation method for dressing virtual humans of various shapes and poses. Our approach formulates the clothing deformation as a high-dimensional function of body shape parameters and pose parameters. In order to accelerate the computation, our formulation factorizes the clothing deformation into two independent components: the deformation introduced by body pose variation (Clothing Pose Model) and the deformation from body shape variation (Clothing Shape Model). Furthermore, we sample and cluster the poses spanning the entire pose space and use those clusters to efficiently calculate the anchoring points. We also introduce a sensitivity-based distance measurement to both find nearby anchoring points and evaluate their contributions to the final animation. Given a query shape and pose of the virtual agent, we synthesize the resulting clothing deformation by blending the Taylor expansion results of nearby anchoring points. Compared to previous methods, our approach is general and able to add the shape dimension to any clothing pose model. Furthermore, we can animate clothing represented with tens of thousands of vertices at 50+ FPS on a CPU. We also conduct a user evaluation and show that our method can improve a user's perception of dressed virtual agents in an immersive virtual environment (IVE) compared to a realtime linear blend skinning method.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a CPU-based real-time cloth animation method for dressing virtual humans of various shapes and poses. Our approach formulates the clothing deformation as a high-dimensional function of body shape parameters and pose parameters. In order to accelerate the computation, our formulation factorizes the clothing deformation into two independent components: the deformation introduced by body pose variation (Clothing Pose Model) and the deformation from body shape variation (Clothing Shape Model). Furthermore, we sample and cluster the poses spanning the entire pose space and use those clusters to efficiently calculate the anchoring points. We also introduce a sensitivity-based distance measurement to both find nearby anchoring points and evaluate their contributions to the final animation. Given a query shape and pose of the virtual agent, we synthesize the resulting clothing deformation by blending the Taylor expansion results of nearby anchoring points. Compared to previous methods, our approach is general and able to add the shape dimension to any clothing pose model. Furthermore, we can animate clothing represented with tens of thousands of vertices at 50+ FPS on a CPU. We also conduct a user evaluation and show that our method can improve a user's perception of dressed virtual agents in an immersive virtual environment (IVE) compared to a realtime linear blend skinning method.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a CPU-based real-time cloth animation method for dressing virtual humans of various shapes and poses. Our approach formulates the clothing deformation as a high-dimensional function of body shape parameters and pose parameters. In order to accelerate the computation, our formulation factorizes the clothing deformation into two independent components: the deformation introduced by body pose variation (Clothing Pose Model) and the deformation from body shape variation (Clothing Shape Model). Furthermore, we sample and cluster the poses spanning the entire pose space and use those clusters to efficiently calculate the anchoring points. We also introduce a sensitivity-based distance measurement to both find nearby anchoring points and evaluate their contributions to the final animation. Given a query shape and pose of the virtual agent, we synthesize the resulting clothing deformation by blending the Taylor expansion results of nearby anchoring points. Compared to previous methods, our approach is general and able to add the shape dimension to any clothing pose model. Furthermore, we can animate clothing represented with tens of thousands of vertices at 50+ FPS on a CPU. We also conduct a user evaluation and show that our method can improve a user's perception of dressed virtual agents in an immersive virtual environment (IVE) compared to a realtime linear blend skinning method.",
"title": "AgentDress: Realtime Clothing Synthesis for Virtual Agents using Plausible Deformations",
"normalizedTitle": "AgentDress: Realtime Clothing Synthesis for Virtual Agents using Plausible Deformations",
"fno": "09523843",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Clothing",
"Computer Animation",
"Pose Estimation",
"Solid Modelling",
"Virtual Reality",
"Realtime Clothing Synthesis",
"Virtual Agent",
"Plausible Deformations",
"CPU Based Real Time Cloth Animation Method",
"Virtual Humans",
"High Dimensional Function",
"Body Shape Parameters",
"Clothing Pose Model",
"Body Shape Variation",
"Clothing Shape Model",
"Sensitivity Based Distance Measurement",
"Nearby Anchoring Points",
"Query Shape",
"Resulting Clothing Deformation",
"Shape Dimension",
"Dressed Virtual Agents",
"Immersive Virtual Environment",
"Realtime Linear Blend Skinning Method",
"Clothing",
"Strain",
"Shape",
"Animation",
"Real Time Systems",
"Deformable Models",
"Computational Modeling",
"Clothing Animation",
"Virtual Agents",
"Social VR",
"Virtual Try On Clothing Shape Models"
],
"authors": [
{
"givenName": "Nannan",
"surname": "Wu",
"fullName": "Nannan Wu",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Qianwen",
"surname": "Chao",
"fullName": "Qianwen Chao",
"affiliation": "Department of Computer Science, Xidian University, Xi'an, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yanzhen",
"surname": "Chen",
"fullName": "Yanzhen Chen",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Weiwei",
"surname": "Xu",
"fullName": "Weiwei Xu",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chen",
"surname": "Liu",
"fullName": "Chen Liu",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Dinesh",
"surname": "Manocha",
"fullName": "Dinesh Manocha",
"affiliation": "Department of Computer Science, University of Maryland, College Park, MD, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wenxin",
"surname": "Sun",
"fullName": "Wenxin Sun",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yi",
"surname": "Han",
"fullName": "Yi Han",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xinran",
"surname": "Yao",
"fullName": "Xinran Yao",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiaogang",
"surname": "Jin",
"fullName": "Xiaogang Jin",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2021-11-01 00:00:00",
"pubType": "trans",
"pages": "4107-4118",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/2017/0457/0/0457f484",
"title": "Detailed, Accurate, Human Shape Estimation from Clothed 3D Scan Sequences",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2017/0457f484/12OmNCbCrYI",
"parentPublication": {
"id": "proceedings/cvpr/2017/0457/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2014/7000/1/7000a171",
"title": "A Layered Model of Human Body and Garment Deformation",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2014/7000a171/12OmNCf1DwE",
"parentPublication": {
"id": "proceedings/3dv/2014/7000/2",
"title": "2014 2nd International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2017/1032/0/1032a853",
"title": "A Generative Model of People in Clothing",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/1032a853/12OmNCwlakU",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08545658",
"title": "Representing a Partially Observed Non-Rigid 3D Human Using Eigen-Texture and Eigen-Deformation",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08545658/17D45XuDNE6",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200l1688",
"title": "Neural-GIF: Neural Generalized Implicit Functions for Animating People in Clothing",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200l1688/1BmLeBojAWs",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200k0954",
"title": "The Power of Points for Modeling Humans in Clothing",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200k0954/1BmLrmWbNuM",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2022/5670/0/567000a679",
"title": "Neural Point-based Shape Modeling of Humans in Challenging Clothing",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2022/567000a679/1KYsvi8qLS0",
"parentPublication": {
"id": "proceedings/3dv/2022/5670/0",
"title": "2022 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800h363",
"title": "TailorNet: Predicting Clothing in 3D as a Function of Human Pose, Shape and Garment Style",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800h363/1m3nnD97pZu",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800g468",
"title": "Learning to Dress 3D People in Generative Clothing",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800g468/1m3nwUHFD68",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2020/8128/0/812800a322",
"title": "MonoClothCap: Towards Temporally Coherent Clothing Capture from Monocular RGB Video",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2020/812800a322/1qyxk1bcV5S",
"parentPublication": {
"id": "proceedings/3dv/2020/8128/0",
"title": "2020 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09523888",
"articleId": "1wpqxgia3Vm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09523841",
"articleId": "1wpqtpOgOqI",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1y2FnK0CcmI",
"name": "ttg202111-09523843s1-supp1-3106429.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202111-09523843s1-supp1-3106429.pdf",
"extension": "pdf",
"size": "5.03 MB",
"__typename": "WebExtraType"
},
{
"id": "1y2FnE32t0I",
"name": "ttg202111-09523843s1-supp3-3106429.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202111-09523843s1-supp3-3106429.mp4",
"extension": "mp4",
"size": "6.22 MB",
"__typename": "WebExtraType"
},
{
"id": "1y2FnplS5tC",
"name": "ttg202111-09523843s1-supp2-3106429.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202111-09523843s1-supp2-3106429.mp4",
"extension": "mp4",
"size": "31 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNBTJIKa",
"title": "July",
"year": "2015",
"issueNum": "07",
"idPrefix": "ts",
"pubType": "journal",
"volume": "41",
"label": "July",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUx0xPoL",
"doi": "10.1109/TSE.2015.2389225",
"abstract": "Lazy Initialization (LI) allows symbolic execution to effectively deal with heap-allocated data structures, thanks to a significant reduction in spurious and redundant symbolic structures. Bounded lazy initialization (BLI) improves on LI by taking advantage of precomputed relational bounds on the interpretation of class fields in order to reduce the number of spurious structures even further. In this paper we present bounded lazy initialization with SAT support (BLISS), a novel technique that refines the search for valid structures during the symbolic execution process. BLISS builds upon BLI, extending it with field bound refinement and satisfiability checks. Field bounds are refined while a symbolic structure is concretized, avoiding cases that, due to the concrete part of the heap and the field bounds, can be deemed redundant. Satisfiability checks on refined symbolic heaps allow us to prune these heaps as soon as they are identified as infeasible, i.e., as soon as it can be confirmed that they cannot be extended to any valid concrete heap. Compared to LI and BLI, BLISS reduces the time required by LI by up to four orders of magnitude for the most complex data structures. Moreover, the number of partially symbolic structures obtained by exploring program paths is reduced by BLISS by over 50 percent, with reductions of over 90 percent in some cases (compared to LI). BLISS uses less memory than LI and BLI, which enables the exploration of states unreachable by previous techniques.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Lazy Initialization (LI) allows symbolic execution to effectively deal with heap-allocated data structures, thanks to a significant reduction in spurious and redundant symbolic structures. Bounded lazy initialization (BLI) improves on LI by taking advantage of precomputed relational bounds on the interpretation of class fields in order to reduce the number of spurious structures even further. In this paper we present bounded lazy initialization with SAT support (BLISS), a novel technique that refines the search for valid structures during the symbolic execution process. BLISS builds upon BLI, extending it with field bound refinement and satisfiability checks. Field bounds are refined while a symbolic structure is concretized, avoiding cases that, due to the concrete part of the heap and the field bounds, can be deemed redundant. Satisfiability checks on refined symbolic heaps allow us to prune these heaps as soon as they are identified as infeasible, i.e., as soon as it can be confirmed that they cannot be extended to any valid concrete heap. Compared to LI and BLI, BLISS reduces the time required by LI by up to four orders of magnitude for the most complex data structures. Moreover, the number of partially symbolic structures obtained by exploring program paths is reduced by BLISS by over 50 percent, with reductions of over 90 percent in some cases (compared to LI). BLISS uses less memory than LI and BLI, which enables the exploration of states unreachable by previous techniques.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Lazy Initialization (LI) allows symbolic execution to effectively deal with heap-allocated data structures, thanks to a significant reduction in spurious and redundant symbolic structures. Bounded lazy initialization (BLI) improves on LI by taking advantage of precomputed relational bounds on the interpretation of class fields in order to reduce the number of spurious structures even further. In this paper we present bounded lazy initialization with SAT support (BLISS), a novel technique that refines the search for valid structures during the symbolic execution process. BLISS builds upon BLI, extending it with field bound refinement and satisfiability checks. Field bounds are refined while a symbolic structure is concretized, avoiding cases that, due to the concrete part of the heap and the field bounds, can be deemed redundant. Satisfiability checks on refined symbolic heaps allow us to prune these heaps as soon as they are identified as infeasible, i.e., as soon as it can be confirmed that they cannot be extended to any valid concrete heap. Compared to LI and BLI, BLISS reduces the time required by LI by up to four orders of magnitude for the most complex data structures. Moreover, the number of partially symbolic structures obtained by exploring program paths is reduced by BLISS by over 50 percent, with reductions of over 90 percent in some cases (compared to LI). BLISS uses less memory than LI and BLI, which enables the exploration of states unreachable by previous techniques.",
"title": "BLISS: Improved Symbolic Execution by Bounded Lazy Initialization with SAT Support",
"normalizedTitle": "BLISS: Improved Symbolic Execution by Bounded Lazy Initialization with SAT Support",
"fno": "07004061",
"hasPdf": true,
"idPrefix": "ts",
"keywords": [
"Concrete",
"Binary Trees",
"Java",
"Periodic Structures",
"Software"
],
"authors": [
{
"givenName": "Nicolas",
"surname": "Rosner",
"fullName": "Nicolas Rosner",
"affiliation": "Department of Computer Science, FCEyN, Universidad de Buenos Aires, Buenos Aires, Argentina",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jaco",
"surname": "Geldenhuys",
"fullName": "Jaco Geldenhuys",
"affiliation": "Department of Computer Science, University of Stellenbosch, Stellenbosch, South Africa",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nazareno M.",
"surname": "Aguirre",
"fullName": "Nazareno M. Aguirre",
"affiliation": "Department of Computer Science, FCEFQyN, Universidad Nacional de Rio Cuarto, and CONICET, Río Cuarto, Argentina",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Willem",
"surname": "Visser",
"fullName": "Willem Visser",
"affiliation": "Department of Computer Science, University of Stellenbosch, Stellenbosch, South Africa",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Marcelo F.",
"surname": "Frias",
"fullName": "Marcelo F. Frias",
"affiliation": "Department of Software Engineering, Instituto Tecnológico de Buenos Aires, and CONICET, Buenos Aires, Argentina",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "07",
"pubDate": "2015-07-01 00:00:00",
"pubType": "trans",
"pages": "639-660",
"year": "2015",
"issn": "0098-5589",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ast/2009/3711/0/05069044",
"title": "Lazy symbolic evaluation and its path constraints solution",
"doi": null,
"abstractUrl": "/proceedings-article/ast/2009/05069044/12OmNAsBFGh",
"parentPublication": {
"id": "proceedings/ast/2009/3711/0",
"title": "2009 ICSE Workshop on Automation of Software Test (AST 2009)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sefm/2007/2884/0/04343944",
"title": "Towards A Case-Optimal Symbolic Execution Algorithm for Analyzing Strong Properties of Object-Oriented Programs",
"doi": null,
"abstractUrl": "/proceedings-article/sefm/2007/04343944/12OmNCgrD3k",
"parentPublication": {
"id": "proceedings/sefm/2007/2884/0",
"title": "2007 IEEE International Conference on Software Engineering and Formal Methods",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icse/2008/4486/0/04814209",
"title": "Juzi",
"doi": null,
"abstractUrl": "/proceedings-article/icse/2008/04814209/12OmNCmGNWO",
"parentPublication": {
"id": "proceedings/icse/2008/4486/0",
"title": "2008 ACM/IEEE 30th International Conference on Software Engineering. ICSE'08",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icse/2015/1934/1/1934a632",
"title": "Compositional Symbolic Execution with Memoized Replay",
"doi": null,
"abstractUrl": "/proceedings-article/icse/2015/1934a632/12OmNvAAttZ",
"parentPublication": {
"id": "proceedings/icse/2015/1934/2",
"title": "2015 IEEE/ACM 37th IEEE International Conference on Software Engineering (ICSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csf/2016/2607/0/2607a387",
"title": "Multi-run Side-Channel Analysis Using Symbolic Execution and Max-SMT",
"doi": null,
"abstractUrl": "/proceedings-article/csf/2016/2607a387/12OmNvAS4pD",
"parentPublication": {
"id": "proceedings/csf/2016/2607/0",
"title": "2016 IEEE 29th Computer Security Foundations Symposium (CSF)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icst/2015/7125/0/07102587",
"title": "Evaluating Symbolic Execution-Based Test Tools",
"doi": null,
"abstractUrl": "/proceedings-article/icst/2015/07102587/12OmNz4Bdr6",
"parentPublication": {
"id": "proceedings/icst/2015/7125/0",
"title": "2015 IEEE 8th International Conference on Software Testing, Verification and Validation (ICST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ast/2012/1821/0/06228982",
"title": "All-values symbolic execution",
"doi": null,
"abstractUrl": "/proceedings-article/ast/2012/06228982/12OmNzlD9nO",
"parentPublication": {
"id": "proceedings/ast/2012/1821/0",
"title": "Automation of Software Test, Second International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icse-companion/2018/5663/0/566301a268",
"title": "Poster: Testing Heap-Based Programs with Java StarFinder",
"doi": null,
"abstractUrl": "/proceedings-article/icse-companion/2018/566301a268/13bd1gzWkQ2",
"parentPublication": {
"id": "proceedings/icse-companion/2018/5663/0",
"title": "2018 IEEE/ACM 40th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2001/05/t0432",
"title": "Symbolic Analysis of Bounded Petri Nets",
"doi": null,
"abstractUrl": "/journal/tc/2001/05/t0432/13rRUxASu02",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/issre/2022/5132/0/513200a494",
"title": "Learning to Prune Infeasible Paths in Generalized Symbolic Execution",
"doi": null,
"abstractUrl": "/proceedings-article/issre/2022/513200a494/1JhTHq1toHe",
"parentPublication": {
"id": "proceedings/issre/2022/5132/0",
"title": "2022 IEEE 33rd International Symposium on Software Reliability Engineering (ISSRE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07029714",
"articleId": "13rRUzphDzy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07042284",
"articleId": "13rRUxZ0nXJ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNyKJisL",
"title": "Jan.-Feb.",
"year": "2020",
"issueNum": "01",
"idPrefix": "cg",
"pubType": "magazine",
"volume": "40",
"label": "Jan.-Feb.",
"downloadables": {
"hasCover": true,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "19TwKhiEDxC",
"doi": "10.1109/MCG.2019.2915215",
"abstract": "Simulation ensembles such as the ones simulating deep water asteroid impacts have many facets. Their analysis in terms of detecting spatiotemporal patterns, comparing multiple runs, and analyzing the influence of simulation parameters requires aggregation at multiple levels. We propose respective visual encodings embedded in an interactive visual analysis tool.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Simulation ensembles such as the ones simulating deep water asteroid impacts have many facets. Their analysis in terms of detecting spatiotemporal patterns, comparing multiple runs, and analyzing the influence of simulation parameters requires aggregation at multiple levels. We propose respective visual encodings embedded in an interactive visual analysis tool.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Simulation ensembles such as the ones simulating deep water asteroid impacts have many facets. Their analysis in terms of detecting spatiotemporal patterns, comparing multiple runs, and analyzing the influence of simulation parameters requires aggregation at multiple levels. We propose respective visual encodings embedded in an interactive visual analysis tool.",
"title": "Aggregated Ensemble Views for Deep Water Asteroid Impact Simulations",
"normalizedTitle": "Aggregated Ensemble Views for Deep Water Asteroid Impact Simulations",
"fno": "08709800",
"hasPdf": true,
"idPrefix": "cg",
"keywords": [
"Asteroids",
"Data Visualisation",
"Geophysics Computing",
"Interactive Systems",
"Spatiotemporal Phenomena",
"Aggregated Ensemble Views",
"Deep Water Asteroid Impact",
"Spatiotemporal Pattern Detection",
"Interactive Visual Analysis Tool",
"Simulation Run Visualizations",
"Analytical Models",
"Visualization",
"Solar System",
"Data Models",
"Computational Modeling",
"Encoding",
"Isosurfaces"
],
"authors": [
{
"givenName": "Simon",
"surname": "Leistikow",
"fullName": "Simon Leistikow",
"affiliation": "Westfälische Wilhelms-Universität Münster, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Karim",
"surname": "Huesmann",
"fullName": "Karim Huesmann",
"affiliation": "Westfälische Wilhelms-Universität Münster, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alexey",
"surname": "Fofonov",
"fullName": "Alexey Fofonov",
"affiliation": "Jacobs University, Bremen, Germany",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lars",
"surname": "Linsen",
"fullName": "Lars Linsen",
"affiliation": "Westfälische Wilhelms-Universität Münster, Germany",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2020-01-01 00:00:00",
"pubType": "mags",
"pages": "72-81",
"year": "2020",
"issn": "0272-1716",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icpp/2016/2823/0/2823a458",
"title": "Ensemble Toolkit: Scalable and Flexible Execution of Ensembles of Tasks",
"doi": null,
"abstractUrl": "/proceedings-article/icpp/2016/2823a458/12OmNvw2TcP",
"parentPublication": {
"id": "proceedings/icpp/2016/2823/0",
"title": "2016 45th International Conference on Parallel Processing (ICPP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/01/07539323",
"title": "Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots",
"doi": null,
"abstractUrl": "/journal/tg/2017/01/07539323/13rRUxNEqPZ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2014/03/mcg2014030008",
"title": "Future challenges for ensemble visualization",
"doi": null,
"abstractUrl": "/magazine/cg/2014/03/mcg2014030008/13rRUxNmPLh",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/08/07321821",
"title": "Visual Analysis of Multi-Run Spatio-Temporal Simulations Using Isocontour Similarity for Projected Views",
"doi": null,
"abstractUrl": "/journal/tg/2016/08/07321821/13rRUyYjKak",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2021/03/08502125",
"title": "Integrating Data and Model Space in Ensemble Learning by Visual Analytics",
"doi": null,
"abstractUrl": "/journal/bd/2021/03/08502125/14ArjyliufC",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2018/5520/0/552000b144",
"title": "M2TD: Multi-Task Tensor Decomposition for Sparse Ensemble Simulations",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2018/552000b144/14Fq10gOWL9",
"parentPublication": {
"id": "proceedings/icde/2018/5520/0",
"title": "2018 IEEE 34th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vds/2017/3185/0/08573444",
"title": "Visual Integration of Data and Model Space in Ensemble Learning",
"doi": null,
"abstractUrl": "/proceedings-article/vds/2017/08573444/17D45XreC6k",
"parentPublication": {
"id": "proceedings/vds/2017/3185/0",
"title": "2017 IEEE Visualization in Data Science (VDS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scivis/2018/6882/0/08823612",
"title": "Visualizing Deep Water Asteroid Impacts: Interactive Visual Analysis of Multi-run Spatio-temporal Simulations",
"doi": null,
"abstractUrl": "/proceedings-article/scivis/2018/08823612/1d5kxZq5oTS",
"parentPublication": {
"id": "proceedings/scivis/2018/6882/0",
"title": "2018 IEEE Scientific Visualization Conference (SciVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222295",
"title": "Modeling the Influence of Visual Density on Cluster Perception in Scatterplots Using Topology",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222295/1nTqtC45a12",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wcmeim/2020/4109/0/410900a556",
"title": "Design optimization and simulation analysis of grab sampling head",
"doi": null,
"abstractUrl": "/proceedings-article/wcmeim/2020/410900a556/1t2mAS9Glhe",
"parentPublication": {
"id": "proceedings/wcmeim/2020/4109/0",
"title": "2020 3rd World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08951771",
"articleId": "1goL8muq0lq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08951768",
"articleId": "1goLauG6eWc",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzZ5oam",
"title": "July/August",
"year": "2008",
"issueNum": "04",
"idPrefix": "tg",
"pubType": "journal",
"volume": "14",
"label": "July/August",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxASuGa",
"doi": "10.1109/TVCG.2008.38",
"abstract": "A curve skeleton is a compact representation of 3D objects and has numerous applications. It can be used to describe an object??s geometry and topology. In this paper, we introduce a novel approach for computing curve skeletons for volumetric representations of the input models. Our algorithm consists of three major steps: 1) using iterative least squares optimization to shrink models and, at the same time, preserving their geometries and topologies; 2) extracting curve skeletons through the thinning algorithm; and 3) pruning unnecessary branches based on shrinking ratios. The proposed method is less sensitive to noise on the surface of models and can generate smoother skeletons. In addition, our shrinking algorithm requires little computation, since the optimization system can be factorized and stored in the pre-computational step. We demonstrate several extracted skeletons that help evaluate our algorithm. We also experimentally compare the proposed method with other well-known methods. Experimental results show advantages when using our method over other techniques.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A curve skeleton is a compact representation of 3D objects and has numerous applications. It can be used to describe an object??s geometry and topology. In this paper, we introduce a novel approach for computing curve skeletons for volumetric representations of the input models. Our algorithm consists of three major steps: 1) using iterative least squares optimization to shrink models and, at the same time, preserving their geometries and topologies; 2) extracting curve skeletons through the thinning algorithm; and 3) pruning unnecessary branches based on shrinking ratios. The proposed method is less sensitive to noise on the surface of models and can generate smoother skeletons. In addition, our shrinking algorithm requires little computation, since the optimization system can be factorized and stored in the pre-computational step. We demonstrate several extracted skeletons that help evaluate our algorithm. We also experimentally compare the proposed method with other well-known methods. Experimental results show advantages when using our method over other techniques.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A curve skeleton is a compact representation of 3D objects and has numerous applications. It can be used to describe an object??s geometry and topology. In this paper, we introduce a novel approach for computing curve skeletons for volumetric representations of the input models. Our algorithm consists of three major steps: 1) using iterative least squares optimization to shrink models and, at the same time, preserving their geometries and topologies; 2) extracting curve skeletons through the thinning algorithm; and 3) pruning unnecessary branches based on shrinking ratios. The proposed method is less sensitive to noise on the surface of models and can generate smoother skeletons. In addition, our shrinking algorithm requires little computation, since the optimization system can be factorized and stored in the pre-computational step. We demonstrate several extracted skeletons that help evaluate our algorithm. We also experimentally compare the proposed method with other well-known methods. Experimental results show advantages when using our method over other techniques.",
"title": "Curve-Skeleton Extraction Using Iterative Least Squares Optimization",
"normalizedTitle": "Curve-Skeleton Extraction Using Iterative Least Squares Optimization",
"fno": "ttg2008040926",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computer Graphics",
"Skeleton"
],
"authors": [
{
"givenName": "Yu-Shuen",
"surname": "Wang",
"fullName": "Yu-Shuen Wang",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tong-Yee",
"surname": "Lee",
"fullName": "Tong-Yee Lee",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2008-07-01 00:00:00",
"pubType": "trans",
"pages": "926-936",
"year": "2008",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ieee-vis/2005/2766/0/01532783",
"title": "Curve-skeleton applications",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/01532783/12OmNAle6mg",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgiv/2008/3359/0/3359a132",
"title": "Skeleton Based 3D Model Morphing Using Barycentric Map",
"doi": null,
"abstractUrl": "/proceedings-article/cgiv/2008/3359a132/12OmNB9t6qf",
"parentPublication": {
"id": "proceedings/cgiv/2008/3359/0",
"title": "2008 Fifth International Conference on Computer Graphics, Imaging and Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccet/2009/3521/1/3521a326",
"title": "3D Mesh Skeleton Extraction Based on Feature Points",
"doi": null,
"abstractUrl": "/proceedings-article/iccet/2009/3521a326/12OmNvAAtk8",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2005/2766/0/27660013",
"title": "Curve-Skeleton Applications",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2005/27660013/12OmNyQ7G1I",
"parentPublication": {
"id": "proceedings/ieee-vis/2005/2766/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icapr/2009/3520/0/04782819",
"title": "Discrete Curve Evolution Based Skeleton Pruning for Character Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/icapr/2009/04782819/12OmNyjtNIb",
"parentPublication": {
"id": "proceedings/icapr/2009/3520/0",
"title": "Advances in Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2007/03/v0530",
"title": "Curve-Skeleton Properties, Applications, and Algorithms",
"doi": null,
"abstractUrl": "/journal/tg/2007/03/v0530/13rRUwbaqUK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2007/03/i0449",
"title": "Skeleton Pruning by Contour Partitioning with Discrete Curve Evolution",
"doi": null,
"abstractUrl": "/journal/tp/2007/03/i0449/13rRUxDqS57",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2013/06/ttp2013061495",
"title": "Surface and Curve Skeletonization of Large 3D Models on the GPU",
"doi": null,
"abstractUrl": "/journal/tp/2013/06/ttp2013061495/13rRUyYSWmb",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/09/08664178",
"title": "Mass-Driven Topology-Aware Curve Skeleton Extraction from Incomplete Point Clouds",
"doi": null,
"abstractUrl": "/journal/tg/2020/09/08664178/1lRhomN6HMk",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/03/09173765",
"title": "A Simple and Stable Centeredness Measure for 3D Curve Skeleton Extraction",
"doi": null,
"abstractUrl": "/journal/tg/2022/03/09173765/1mts9gNKec0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttg2008040914",
"articleId": "13rRUxBJhmM",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttg2008040937",
"articleId": "13rRUzpzeAY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvqEvRo",
"title": "PrePrints",
"year": "5555",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": null,
"label": "PrePrints",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1C0jdavrcC4",
"doi": "10.1109/TVCG.2022.3161962",
"abstract": "Extracting concise 3D curve skeletons with existing methods is still a serious challenge as these methods require tedious parameter adjustment to suppress the influence of shape boundary perturbations to avoid spurious branches. In this paper, we address this challenge by enhancing the capture of prominent features and using them for skeleton extraction, motivated by the observation that the shape is mainly represented by prominent features. Our method takes the medial mesh of the shape as input, which can maintain the shape topology well. We develop a series of novel measures for simplifying and contracting the medial mesh to capture prominent features and represent them concisely, by which means the influences of shape boundary perturbations on skeleton extraction are suppressed and the quantity of data needed for skeleton extraction is significantly reduced. As a result, we can robustly and concisely extract the curve skeleton based on prominent features, avoiding the trouble of tuning parameters and saving computations, as shown by experimental results.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Extracting concise 3D curve skeletons with existing methods is still a serious challenge as these methods require tedious parameter adjustment to suppress the influence of shape boundary perturbations to avoid spurious branches. In this paper, we address this challenge by enhancing the capture of prominent features and using them for skeleton extraction, motivated by the observation that the shape is mainly represented by prominent features. Our method takes the medial mesh of the shape as input, which can maintain the shape topology well. We develop a series of novel measures for simplifying and contracting the medial mesh to capture prominent features and represent them concisely, by which means the influences of shape boundary perturbations on skeleton extraction are suppressed and the quantity of data needed for skeleton extraction is significantly reduced. As a result, we can robustly and concisely extract the curve skeleton based on prominent features, avoiding the trouble of tuning parameters and saving computations, as shown by experimental results.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Extracting concise 3D curve skeletons with existing methods is still a serious challenge as these methods require tedious parameter adjustment to suppress the influence of shape boundary perturbations to avoid spurious branches. In this paper, we address this challenge by enhancing the capture of prominent features and using them for skeleton extraction, motivated by the observation that the shape is mainly represented by prominent features. Our method takes the medial mesh of the shape as input, which can maintain the shape topology well. We develop a series of novel measures for simplifying and contracting the medial mesh to capture prominent features and represent them concisely, by which means the influences of shape boundary perturbations on skeleton extraction are suppressed and the quantity of data needed for skeleton extraction is significantly reduced. As a result, we can robustly and concisely extract the curve skeleton based on prominent features, avoiding the trouble of tuning parameters and saving computations, as shown by experimental results.",
"title": "Robustly Extracting Concise 3D Curve Skeletons by Enhancing the Capture of Prominent Features",
"normalizedTitle": "Robustly Extracting Concise 3D Curve Skeletons by Enhancing the Capture of Prominent Features",
"fno": "09741325",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Skeleton",
"Shape",
"Feature Extraction",
"Topology",
"Perturbation Methods",
"Three Dimensional Displays",
"Surface Treatment",
"Curve Skeleton",
"Medial Surface",
"Set Cover",
"Edge Contraction"
],
"authors": [
{
"givenName": "Yiyao",
"surname": "Chu",
"fullName": "Yiyao Chu",
"affiliation": "institute of software, Chinese Academy of Sciences, 12381 Beijing, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wencheng",
"surname": "Wang",
"fullName": "Wencheng Wang",
"affiliation": "Institute of Software, State Key Laboratory of Computer Science, Beijing, Beijing, China, 100190",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lei",
"surname": "Li",
"fullName": "Lei Li",
"affiliation": "institute of software, Chinese Academy of Sciences, 12381, Beijing, China, 100190",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-03-01 00:00:00",
"pubType": "trans",
"pages": "1-1",
"year": "5555",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2007/1630/0/04409112",
"title": "On the Extraction of Curve Skeletons using Gradient Vector Flow",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2007/04409112/12OmNC1oT5B",
"parentPublication": {
"id": "proceedings/iccv/2007/1630/0",
"title": "2007 11th IEEE International Conference on Computer Vision",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dimpvt/2012/4873/0/4873a371",
"title": "An Adaptive Hierarchical Approach to the Extraction of High Resolution Medial Surfaces",
"doi": null,
"abstractUrl": "/proceedings-article/3dimpvt/2012/4873a371/12OmNqAU6yz",
"parentPublication": {
"id": "proceedings/3dimpvt/2012/4873/0",
"title": "2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/1992/2920/0/00202026",
"title": "Interval skeletons",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/1992/00202026/12OmNqBKTLd",
"parentPublication": {
"id": "proceedings/icpr/1992/2920/0",
"title": "11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2000/0750/1/00905486",
"title": "Object representation and comparison inferred from its medial axis",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2000/00905486/12OmNvkpljB",
"parentPublication": {
"id": "proceedings/icpr/2000/0750/1",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/1992/2855/0/00223226",
"title": "Voronoi skeletons: theory and applications",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/1992/00223226/12OmNxH9Xdu",
"parentPublication": {
"id": "proceedings/cvpr/1992/2855/0",
"title": "Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2010/7029/0/05543279",
"title": "Straight skeletons for binary shapes",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2010/05543279/12OmNyUnEJa",
"parentPublication": {
"id": "proceedings/cvprw/2010/7029/0",
"title": "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2012/11/ttg2012111891",
"title": "Reconstructing the Curve-Skeletons of 3D Shapes Using the Visual Hull",
"doi": null,
"abstractUrl": "/journal/tg/2012/11/ttg2012111891/13rRUwIF6dP",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2016/01/07066924",
"title": "An Unified Multiscale Framework for Planar, Surface, and Curve Skeletonization",
"doi": null,
"abstractUrl": "/journal/tp/2016/01/07066924/13rRUxASuNO",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/03/09173765",
"title": "A Simple and Stable Centeredness Measure for 3D Curve Skeleton Extraction",
"doi": null,
"abstractUrl": "/journal/tg/2022/03/09173765/1mts9gNKec0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/019100c142",
"title": "SkeletonNetV2: A Dense Channel Attention Blocks for Skeleton Extraction",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100c142/1yNi2zrB80U",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09737429",
"articleId": "1BQidPzNjBS",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09744472",
"articleId": "1C8BFCieD2U",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1C1Y0HPzFf2",
"name": "ttg555501-09741325s1-supp1-3161962.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg555501-09741325s1-supp1-3161962.pdf",
"extension": "pdf",
"size": "3.68 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1qL5hsvvVkc",
"title": "Feb.",
"year": "2021",
"issueNum": "02",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Feb.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1nTquHN7hbq",
"doi": "10.1109/TVCG.2020.3030420",
"abstract": "Investigating relationships between variables in multi-dimensional data sets is a common task for data analysts and engineers. More specifically, it is often valuable to understand which ranges of which input variables lead to particular values of a given target variable. Unfortunately, with an increasing number of independent variables, this process may become cumbersome and time-consuming due to the many possible combinations that have to be explored. In this paper, we propose a novel approach to visualize correlations between input variables and a target output variable that scales to hundreds of variables. We developed a visual model based on neural networks that can be explored in a guided way to help analysts find and understand such correlations. First, we train a neural network to predict the target from the input variables. Then, we visualize the inner workings of the resulting model to help understand relations within the data set. We further introduce a new regularization term for the backpropagation algorithm that encourages the neural network to learn representations that are easier to interpret visually. We apply our method to artificial and real-world data sets to show its utility.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Investigating relationships between variables in multi-dimensional data sets is a common task for data analysts and engineers. More specifically, it is often valuable to understand which ranges of which input variables lead to particular values of a given target variable. Unfortunately, with an increasing number of independent variables, this process may become cumbersome and time-consuming due to the many possible combinations that have to be explored. In this paper, we propose a novel approach to visualize correlations between input variables and a target output variable that scales to hundreds of variables. We developed a visual model based on neural networks that can be explored in a guided way to help analysts find and understand such correlations. First, we train a neural network to predict the target from the input variables. Then, we visualize the inner workings of the resulting model to help understand relations within the data set. We further introduce a new regularization term for the backpropagation algorithm that encourages the neural network to learn representations that are easier to interpret visually. We apply our method to artificial and real-world data sets to show its utility.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Investigating relationships between variables in multi-dimensional data sets is a common task for data analysts and engineers. More specifically, it is often valuable to understand which ranges of which input variables lead to particular values of a given target variable. Unfortunately, with an increasing number of independent variables, this process may become cumbersome and time-consuming due to the many possible combinations that have to be explored. In this paper, we propose a novel approach to visualize correlations between input variables and a target output variable that scales to hundreds of variables. We developed a visual model based on neural networks that can be explored in a guided way to help analysts find and understand such correlations. First, we train a neural network to predict the target from the input variables. Then, we visualize the inner workings of the resulting model to help understand relations within the data set. We further introduce a new regularization term for the backpropagation algorithm that encourages the neural network to learn representations that are easier to interpret visually. We apply our method to artificial and real-world data sets to show its utility.",
"title": "Visual Neural Decomposition to Explain Multivariate Data Sets",
"normalizedTitle": "Visual Neural Decomposition to Explain Multivariate Data Sets",
"fno": "09222060",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Backpropagation",
"Data Analysis",
"Data Visualisation",
"Neural Nets",
"Backpropagation Algorithm",
"Visual Model",
"Data Analysts",
"Multidimensional Data Sets",
"Multivariate Data Sets",
"Visual Neural Decomposition",
"Neural Network",
"Data Visualization",
"Visualization",
"Correlation",
"Analytical Models",
"Input Variables",
"Neural Networks",
"Semiconductor Device Measurement",
"Visual Analytics",
"Multivariate Data Analysis",
"Machine Learning"
],
"authors": [
{
"givenName": "Johannes",
"surname": "Knittel",
"fullName": "Johannes Knittel",
"affiliation": "University of Stuttgart",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Andres",
"surname": "Lalama",
"fullName": "Andres Lalama",
"affiliation": "University of Stuttgart",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Steffen",
"surname": "Koch",
"fullName": "Steffen Koch",
"affiliation": "University of Stuttgart",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Thomas",
"surname": "Ertl",
"fullName": "Thomas Ertl",
"affiliation": "University of Stuttgart",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2021-02-01 00:00:00",
"pubType": "trans",
"pages": "1374-1384",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vast/2014/6227/0/07042515",
"title": "Visualizing the effects of scale and geography in multivariate comparison",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2014/07042515/12OmNvEhfZc",
"parentPublication": {
"id": "proceedings/vast/2014/6227/0",
"title": "2014 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2011/0868/0/06004012",
"title": "Nugget Browser: Visual Subgroup Mining and Statistical Significance Discovery in Multivariate Datasets",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2011/06004012/12OmNyO8tLh",
"parentPublication": {
"id": "proceedings/iv/2011/0868/0",
"title": "2011 15th International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/2002/7614/2/01166413",
"title": "Simulation based cause and effect analysis of cycle time and WIP in semiconductor wafer fabrication",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/2002/01166413/12OmNywxlM8",
"parentPublication": {
"id": "proceedings/wsc/2002/7614/2",
"title": "Proceedings of the 2002 Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192697",
"title": "Association Analysis for Visual Exploration of Multivariate Scientific Data Sets",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192697/13rRUNvgz9S",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875963",
"title": "Decomposition and Simplification of Multivariate Data using Pareto Sets",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875963/13rRUwj7cpc",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/12/ttg2013122606",
"title": "GPLOM: The Generalized Plot Matrix for Visualizing Multidimensional Multivariate Data",
"doi": null,
"abstractUrl": "/journal/tg/2013/12/ttg2013122606/13rRUxAAT0S",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a012",
"title": "Visualization Techniques Representing Effects of Coordination of Vessels' Movements",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a012/17D45XH89pX",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/03/09174891",
"title": "ChartSeer: Interactive Steering Exploratory Visual Analysis With Machine Intelligence",
"doi": null,
"abstractUrl": "/journal/tg/2022/03/09174891/1myqQNpVVTy",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09230431",
"title": "V2V: A Deep Learning Approach to Variable-to-Variable Selection and Translation for Multivariate Time-Varying Data",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09230431/1o3nDz76NBC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/03/09626557",
"title": "SimuExplorer: Visual Exploration of Game Simulation in Table Tennis",
"doi": null,
"abstractUrl": "/journal/tg/2023/03/09626557/1yNd5vlQLrG",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09222510",
"articleId": "1nTrIuXAPRe",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09219240",
"articleId": "1nMMmribStW",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1qLaQYXviHm",
"name": "ttg202102-09222060s1-supp1-3030420.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202102-09222060s1-supp1-3030420.pdf",
"extension": "pdf",
"size": "3.6 MB",
"__typename": "WebExtraType"
},
{
"id": "1qLaNaBT7OM",
"name": "ttg202102-09222060s1-supp2-3030420.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202102-09222060s1-supp2-3030420.mp4",
"extension": "mp4",
"size": "20.3 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1JP1e1gAvYY",
"title": "Feb.",
"year": "2023",
"issueNum": "02",
"idPrefix": "tk",
"pubType": "journal",
"volume": "35",
"label": "Feb.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1uUtsAHpq2Q",
"doi": "10.1109/TKDE.2021.3094236",
"abstract": "Patterns in charts refer to interesting visual features or forms. Identifying patterns not only helps analysts understand the ‘shape’ of the data but also supports better and faster decision-making. Existing solutions for identifying patterns in charts require a large number of labeled data instances, making it intractable without user supervision. In this paper, we propose ChartNavigator, an interactive pattern identification and annotation framework for unlabeled visualization charts. ChartNavigator leverages a novel chart-sensitive deep factor model to map patterns into a low-dimensional factor representation space, and facilitates rich analysis with the derived representations. We design and implement a visual interface to support efficient identification and annotation of potential patterns in charts. Evaluations with multiple datasets show that our approach outperforms the baseline models in identifying and annotating patterns.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Patterns in charts refer to interesting visual features or forms. Identifying patterns not only helps analysts understand the ‘shape’ of the data but also supports better and faster decision-making. Existing solutions for identifying patterns in charts require a large number of labeled data instances, making it intractable without user supervision. In this paper, we propose ChartNavigator, an interactive pattern identification and annotation framework for unlabeled visualization charts. ChartNavigator leverages a novel chart-sensitive deep factor model to map patterns into a low-dimensional factor representation space, and facilitates rich analysis with the derived representations. We design and implement a visual interface to support efficient identification and annotation of potential patterns in charts. Evaluations with multiple datasets show that our approach outperforms the baseline models in identifying and annotating patterns.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Patterns in charts refer to interesting visual features or forms. Identifying patterns not only helps analysts understand the ‘shape’ of the data but also supports better and faster decision-making. Existing solutions for identifying patterns in charts require a large number of labeled data instances, making it intractable without user supervision. In this paper, we propose ChartNavigator, an interactive pattern identification and annotation framework for unlabeled visualization charts. ChartNavigator leverages a novel chart-sensitive deep factor model to map patterns into a low-dimensional factor representation space, and facilitates rich analysis with the derived representations. We design and implement a visual interface to support efficient identification and annotation of potential patterns in charts. Evaluations with multiple datasets show that our approach outperforms the baseline models in identifying and annotating patterns.",
"title": "ChartNavigator: An Interactive Pattern Identification and Annotation Framework for Charts",
"normalizedTitle": "ChartNavigator: An Interactive Pattern Identification and Annotation Framework for Charts",
"fno": "09472937",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Control Charts",
"Data Visualisation",
"Decision Making",
"Graphical User Interfaces",
"Learning Artificial Intelligence",
"Pattern Classification",
"Annotation Framework",
"Chart Navigator Leverages",
"Efficient Identification",
"Faster Decision Making",
"Identifying Annotating Patterns",
"Identifying Patterns",
"Interactive Pattern Identification",
"Interesting Visual Features",
"Labeled Data Instances",
"Low Dimensional Factor Representation Space",
"Map Patterns",
"Novel Chart Sensitive Deep Factor Model",
"Potential Patterns",
"Unlabeled Visualization Charts",
"Visual Interface",
"Visualization",
"Data Models",
"Annotations",
"Data Visualization",
"Solid Modeling",
"Inference Algorithms",
"Estimation",
"Pattern Identification",
"Chart",
"Variational Autoencoder",
"User Interaction",
"Visual Analysis"
],
"authors": [
{
"givenName": "Tianye",
"surname": "Zhang",
"fullName": "Tianye Zhang",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haozhe",
"surname": "Feng",
"fullName": "Haozhe Feng",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wei",
"surname": "Chen",
"fullName": "Wei Chen",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zexian",
"surname": "Chen",
"fullName": "Zexian Chen",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wenting",
"surname": "Zheng",
"fullName": "Wenting Zheng",
"affiliation": "State Key Lab of CAD & CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiaonan",
"surname": "Luo",
"fullName": "Xiaonan Luo",
"affiliation": "Guilin University of Electronic Technology, Guilin, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wenqi",
"surname": "Huang",
"fullName": "Wenqi Huang",
"affiliation": "Digital Grid Research Institute, China Southern Power Grid, Guangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Anthony",
"surname": "Tung",
"fullName": "Anthony Tung",
"affiliation": "Department of Computer Science, National University of Singapore, Singapore, Singapore",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2023-02-01 00:00:00",
"pubType": "trans",
"pages": "1258-1269",
"year": "2023",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iv/2017/0831/0/0831a096",
"title": "Microtext Line Charts",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2017/0831a096/12OmNAqkSCW",
"parentPublication": {
"id": "proceedings/iv/2017/0831/0",
"title": "2017 21st International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2017/5738/0/08031599",
"title": "ChartAccent: Annotation for data-driven storytelling",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2017/08031599/12OmNxEjY7F",
"parentPublication": {
"id": "proceedings/pacificvis/2017/5738/0",
"title": "2017 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2002/03/v0255",
"title": "Hierarchical Pixel Bar Charts",
"doi": null,
"abstractUrl": "/journal/tg/2002/03/v0255/13rRUyuegh1",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09904452",
"title": "Striking a Balance: Reader Takeaways and Preferences when Integrating Text and Charts",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09904452/1H1gordOnfy",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08807238",
"title": "A Comparison of Radial and Linear Charts for Visualizing Daily Patterns",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08807238/1cG66qf6MKs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dasc-picom-cbdcom-cyberscitech/2020/6609/0/660900a201",
"title": "Research on Data Quality Control of Crowdsourcing Annotation: A Survey",
"doi": null,
"abstractUrl": "/proceedings-article/dasc-picom-cbdcom-cyberscitech/2020/660900a201/1oFGQGSDUxW",
"parentPublication": {
"id": "proceedings/dasc-picom-cbdcom-cyberscitech/2020/6609/0",
"title": "2020 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ase/2020/6768/0/676800a175",
"title": "UNCHARTIT: An Interactive Framework for Program Recovery from Charts",
"doi": null,
"abstractUrl": "/proceedings-article/ase/2020/676800a175/1pP3KLMHunK",
"parentPublication": {
"id": "proceedings/ase/2020/6768/0",
"title": "2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/02/09547737",
"title": "ChartStory: Automated Partitioning, Layout, and Captioning of Charts into Comic-Style Narratives",
"doi": null,
"abstractUrl": "/journal/tg/2023/02/09547737/1x9TL0bvSlq",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552240",
"title": "Kineticharts: Augmenting Affective Expressiveness of Charts in Data Stories with Animation Design",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552240/1xic12y0QJG",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09552930",
"title": "Kori: Interactive Synthesis of Text and Charts in Data Documents",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09552930/1xic4JnxG2k",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09511228",
"articleId": "1vXcMwbYWKA",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09511218",
"articleId": "1vXcMYNMizK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1JP1ijhhMBy",
"name": "ttk202302-09472937s1-supp2-3094236.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttk202302-09472937s1-supp2-3094236.mp4",
"extension": "mp4",
"size": "35.9 MB",
"__typename": "WebExtraType"
},
{
"id": "1JP1iv2vhLi",
"name": "ttk202302-09472937s1-supp1-3094236.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttk202302-09472937s1-supp1-3094236.pdf",
"extension": "pdf",
"size": "16.3 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1z98erbYoUw",
"title": "Jan.",
"year": "2022",
"issueNum": "01",
"idPrefix": "tp",
"pubType": "journal",
"volume": "44",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1l3uajhdTP2",
"doi": "10.1109/TPAMI.2020.3005393",
"abstract": "In this work, we introduce the <italic>average top-<inline-formula><tex-math notation=\"LaTeX\">Z_$k$_Z</tex-math></inline-formula></italic> (<inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathrm {AT}_k$_Z</tex-math></inline-formula>) loss, which is the average over the <inline-formula><tex-math notation=\"LaTeX\">Z_$k$_Z</tex-math></inline-formula> largest individual losses over a training data, as a new aggregate loss for supervised learning. We show that the <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathrm {AT}_k$_Z</tex-math></inline-formula> loss is a natural generalization of the two widely used aggregate losses, namely the average loss and the maximum loss. Yet, the <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathrm {AT}_k$_Z</tex-math></inline-formula> loss can better adapt to different data distributions because of the extra flexibility provided by the different choices of <inline-formula><tex-math notation=\"LaTeX\">Z_$k$_Z</tex-math></inline-formula>. Furthermore, it remains a convex function over all individual losses and can be combined with different types of individual loss without significant increase in computation. We then provide interpretations of the <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathrm {AT}_k$_Z</tex-math></inline-formula> loss from the perspective of the modification of individual loss and robustness to training data distributions. We further study the classification calibration of the <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathrm {AT}_k$_Z</tex-math></inline-formula> loss and the error bounds of <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathrm {AT}_k$_Z</tex-math></inline-formula>-SVM model. We demonstrate the applicability of minimum average top-<inline-formula><tex-math notation=\"LaTeX\">Z_$k$_Z</tex-math></inline-formula> learning for supervised learning problems including binary/multi-class classification and regression, using experiments on both synthetic and real datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this work, we introduce the <italic>average top-<inline-formula><tex-math notation=\"LaTeX\">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href=\"fan-ieq1-3005393.gif\"/></alternatives></inline-formula></italic> (<inline-formula><tex-math notation=\"LaTeX\">$\\mathrm {AT}_k$</tex-math><alternatives><mml:math><mml:msub><mml:mi> AT </mml:mi><mml:mi mathvariant=\"normal\">k</mml:mi></mml:msub></mml:math><inline-graphic xlink:href=\"fan-ieq2-3005393.gif\"/></alternatives></inline-formula>) loss, which is the average over the <inline-formula><tex-math notation=\"LaTeX\">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href=\"fan-ieq3-3005393.gif\"/></alternatives></inline-formula> largest individual losses over a training data, as a new aggregate loss for supervised learning. We show that the <inline-formula><tex-math notation=\"LaTeX\">$\\mathrm {AT}_k$</tex-math><alternatives><mml:math><mml:msub><mml:mi> AT </mml:mi><mml:mi mathvariant=\"normal\">k</mml:mi></mml:msub></mml:math><inline-graphic xlink:href=\"fan-ieq4-3005393.gif\"/></alternatives></inline-formula> loss is a natural generalization of the two widely used aggregate losses, namely the average loss and the maximum loss. Yet, the <inline-formula><tex-math notation=\"LaTeX\">$\\mathrm {AT}_k$</tex-math><alternatives><mml:math><mml:msub><mml:mi> AT </mml:mi><mml:mi mathvariant=\"normal\">k</mml:mi></mml:msub></mml:math><inline-graphic xlink:href=\"fan-ieq5-3005393.gif\"/></alternatives></inline-formula> loss can better adapt to different data distributions because of the extra flexibility provided by the different choices of <inline-formula><tex-math notation=\"LaTeX\">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href=\"fan-ieq6-3005393.gif\"/></alternatives></inline-formula>. Furthermore, it remains a convex function over all individual losses and can be combined with different types of individual loss without significant increase in computation. We then provide interpretations of the <inline-formula><tex-math notation=\"LaTeX\">$\\mathrm {AT}_k$</tex-math><alternatives><mml:math><mml:msub><mml:mi> AT </mml:mi><mml:mi mathvariant=\"normal\">k</mml:mi></mml:msub></mml:math><inline-graphic xlink:href=\"fan-ieq7-3005393.gif\"/></alternatives></inline-formula> loss from the perspective of the modification of individual loss and robustness to training data distributions. We further study the classification calibration of the <inline-formula><tex-math notation=\"LaTeX\">$\\mathrm {AT}_k$</tex-math><alternatives><mml:math><mml:msub><mml:mi> AT </mml:mi><mml:mi mathvariant=\"normal\">k</mml:mi></mml:msub></mml:math><inline-graphic xlink:href=\"fan-ieq8-3005393.gif\"/></alternatives></inline-formula> loss and the error bounds of <inline-formula><tex-math notation=\"LaTeX\">$\\mathrm {AT}_k$</tex-math><alternatives><mml:math><mml:msub><mml:mi> AT </mml:mi><mml:mi mathvariant=\"normal\">k</mml:mi></mml:msub></mml:math><inline-graphic xlink:href=\"fan-ieq9-3005393.gif\"/></alternatives></inline-formula>-SVM model. We demonstrate the applicability of minimum average top-<inline-formula><tex-math notation=\"LaTeX\">$k$</tex-math><alternatives><mml:math><mml:mi>k</mml:mi></mml:math><inline-graphic xlink:href=\"fan-ieq10-3005393.gif\"/></alternatives></inline-formula> learning for supervised learning problems including binary/multi-class classification and regression, using experiments on both synthetic and real datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this work, we introduce the average top-- (-) loss, which is the average over the - largest individual losses over a training data, as a new aggregate loss for supervised learning. We show that the - loss is a natural generalization of the two widely used aggregate losses, namely the average loss and the maximum loss. Yet, the - loss can better adapt to different data distributions because of the extra flexibility provided by the different choices of -. Furthermore, it remains a convex function over all individual losses and can be combined with different types of individual loss without significant increase in computation. We then provide interpretations of the - loss from the perspective of the modification of individual loss and robustness to training data distributions. We further study the classification calibration of the - loss and the error bounds of --SVM model. We demonstrate the applicability of minimum average top-- learning for supervised learning problems including binary/multi-class classification and regression, using experiments on both synthetic and real datasets.",
"title": "Average Top-k Aggregate Loss for Supervised Learning",
"normalizedTitle": "Average Top-k Aggregate Loss for Supervised Learning",
"fno": "09127807",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Pattern Classification",
"Regression Analysis",
"Supervised Learning",
"Training Data Distributions",
"Supervised Learning",
"Top K Aggregate Loss",
"Convex Function",
"Binary Multi Class Classification",
"Regression",
"Aggregates",
"Training",
"Training Data",
"Supervised Learning",
"Data Models",
"Loss Measurement",
"Task Analysis",
"Aggregate Loss",
"average top-<inline-formula xmlns:ali=\"http://www.niso.org/schemas/ali/1.0/\" xmlns:mml=\"http://www.w3.org/1998/Math/MathML\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xmlns:xsi=\"http://www.w3.org/2001/XMLSchema-instance\"> <tex-math notation=\"LaTeX\">Z_$k$_Z</tex-math> </inline-formula> loss",
"Supervised Learning",
"Learning Theory"
],
"authors": [
{
"givenName": "Siwei",
"surname": "Lyu",
"fullName": "Siwei Lyu",
"affiliation": "Department of Computer Science, University at Albany, State University of New York, Albany, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yanbo",
"surname": "Fan",
"fullName": "Yanbo Fan",
"affiliation": "Tencent AI Lab, Shenzhen, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yiming",
"surname": "Ying",
"fullName": "Yiming Ying",
"affiliation": "Department of Mathematics and Statistics, University at Albany, State University of New York, Albany, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Bao-Gang",
"surname": "Hu",
"fullName": "Bao-Gang Hu",
"affiliation": "National Laboratory of Pattern Recognition, CASIA, University of Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-01-01 00:00:00",
"pubType": "trans",
"pages": "76-86",
"year": "2022",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tq/2019/02/07898418",
"title": "Privacy-Preserving Multi-Keyword Top-k Similarity Search Over Encrypted Data",
"doi": null,
"abstractUrl": "/journal/tq/2019/02/07898418/13rRUzpzeCt",
"parentPublication": {
"id": "trans/tq",
"title": "IEEE Transactions on Dependable and Secure Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/04/09861690",
"title": "Optimizing Partial Area Under the Top-k Curve: Theory and Practice",
"doi": null,
"abstractUrl": "/journal/tp/2023/04/09861690/1FWhV30RnNe",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2021/12/09007415",
"title": "Flexible Aggregate Nearest Neighbor Queries and its Keyword-Aware Variant on Road Networks",
"doi": null,
"abstractUrl": "/journal/tk/2021/12/09007415/1hJKhc0u1So",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/09/09253703",
"title": "Effective and Efficient Discovery of Top-k Meta Paths in Heterogeneous Information Networks",
"doi": null,
"abstractUrl": "/journal/tk/2022/09/09253703/1oDXxbwvBoQ",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/11/09319529",
"title": "Density-Based Top-K Spatial Textual Clusters Retrieval",
"doi": null,
"abstractUrl": "/journal/tk/2022/11/09319529/1qiRBPJJPLa",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/01/09444852",
"title": "Edge Manipulation Approaches for K-Core Minimization: Metrics and Analytics",
"doi": null,
"abstractUrl": "/journal/tk/2023/01/09444852/1u51rOHi1MY",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2022/07/09585362",
"title": "A Fast <inline-formula><tex-math notation=\"LaTeX\">Z_$f(r,k+1)/k$_Z</tex-math></inline-formula>-Diagnosis for Interconnection Networks Under MM* Model",
"doi": null,
"abstractUrl": "/journal/td/2022/07/09585362/1y11LlQdiGk",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/04/09599395",
"title": "Efficient Top-<italic>k</italic> Matching for Publish/Subscribe Ride Hitching",
"doi": null,
"abstractUrl": "/journal/tk/2023/04/09599395/1yeC79w0z3q",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2022/07/09609537",
"title": "Hamiltonian Paths of <inline-formula><tex-math notation=\"LaTeX\">Z_$k$_Z</tex-math></inline-formula>-ary <inline-formula><tex-math notation=\"LaTeX\">Z_$n$_Z</tex-math></inline-formula>-cubes Avoiding Faulty Links and Passing Through Prescribed Linear Forests",
"doi": null,
"abstractUrl": "/journal/td/2022/07/09609537/1yoxLa2YFO0",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/04/09643014",
"title": "k-Pleased Querying",
"doi": null,
"abstractUrl": "/journal/tk/2023/04/09643014/1zarWNa1c5y",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09146781",
"articleId": "1lHjLvQETQI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09139397",
"articleId": "1ls8X1ZoJj2",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1GBRc2WeeKQ",
"title": "Oct.",
"year": "2022",
"issueNum": "10",
"idPrefix": "tk",
"pubType": "journal",
"volume": "34",
"label": "Oct.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1qaz6yaHjji",
"doi": "10.1109/TKDE.2021.3049624",
"abstract": "Given a dataset <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathcal S$_Z</tex-math></inline-formula> composed of <inline-formula><tex-math notation=\"LaTeX\">Z_$g$_Z</tex-math></inline-formula> subsets with each data item belonging to one of them, <italic>multiset membership lookup</italic> takes an item <inline-formula><tex-math notation=\"LaTeX\">Z_$e$_Z</tex-math></inline-formula> as input and outputs a binary answer whether <inline-formula><tex-math notation=\"LaTeX\">Z_$e\\in {\\mathcal S}$_Z</tex-math></inline-formula> and, in case of yes, the ID of the subset to which <inline-formula><tex-math notation=\"LaTeX\">Z_$e$_Z</tex-math></inline-formula> belongs. Overlaid upon while more sophisticated than the canonical membership lookup, multiset membership lookup emerges as a pivotal functionality in many computing and networking paradigms. The quest to achieve high-speed, high-accuracy lookup with limited memory cost makes lookup algorithm design a challenging task, particularly when the data items arrive as a stream. In this paper, we devise compact data structures and lookup algorithms that are amendable for hardware implementation, while guaranteeing high lookup accuracy and supporting interactive query processing. We first propose <italic>multi-hash color table</italic>, a variant of Bloom filter, to encode subset IDs compactly and map the ID of an item to its subset ID. We further construct a more balanced data structure called <italic>balanced multi-hash color table</italic> to improve the compactness by integrating the state-of-the-art load balancing technique. We complete our work by addressing the case of <italic>batch arrivals</italic> and design a batched recording algorithm optimizing the memory efficiency. We give both theoretical and empirical analysis to characterize and evaluate the performance of the proposed algorithms in terms of lookup accuracy, memory and access efficiency.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Given a dataset <inline-formula><tex-math notation=\"LaTeX\">$\\mathcal S$</tex-math><alternatives><mml:math><mml:mi mathvariant=\"script\">S</mml:mi></mml:math><inline-graphic xlink:href=\"chen-ieq1-3049624.gif\"/></alternatives></inline-formula> composed of <inline-formula><tex-math notation=\"LaTeX\">$g$</tex-math><alternatives><mml:math><mml:mi>g</mml:mi></mml:math><inline-graphic xlink:href=\"chen-ieq2-3049624.gif\"/></alternatives></inline-formula> subsets with each data item belonging to one of them, <italic>multiset membership lookup</italic> takes an item <inline-formula><tex-math notation=\"LaTeX\">$e$</tex-math><alternatives><mml:math><mml:mi>e</mml:mi></mml:math><inline-graphic xlink:href=\"chen-ieq3-3049624.gif\"/></alternatives></inline-formula> as input and outputs a binary answer whether <inline-formula><tex-math notation=\"LaTeX\">$e\\in {\\mathcal S}$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>e</mml:mi><mml:mo>∈</mml:mo><mml:mi mathvariant=\"script\">S</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href=\"chen-ieq4-3049624.gif\"/></alternatives></inline-formula> and, in case of yes, the ID of the subset to which <inline-formula><tex-math notation=\"LaTeX\">$e$</tex-math><alternatives><mml:math><mml:mi>e</mml:mi></mml:math><inline-graphic xlink:href=\"chen-ieq5-3049624.gif\"/></alternatives></inline-formula> belongs. Overlaid upon while more sophisticated than the canonical membership lookup, multiset membership lookup emerges as a pivotal functionality in many computing and networking paradigms. The quest to achieve high-speed, high-accuracy lookup with limited memory cost makes lookup algorithm design a challenging task, particularly when the data items arrive as a stream. In this paper, we devise compact data structures and lookup algorithms that are amendable for hardware implementation, while guaranteeing high lookup accuracy and supporting interactive query processing. We first propose <italic>multi-hash color table</italic>, a variant of Bloom filter, to encode subset IDs compactly and map the ID of an item to its subset ID. We further construct a more balanced data structure called <italic>balanced multi-hash color table</italic> to improve the compactness by integrating the state-of-the-art load balancing technique. We complete our work by addressing the case of <italic>batch arrivals</italic> and design a batched recording algorithm optimizing the memory efficiency. We give both theoretical and empirical analysis to characterize and evaluate the performance of the proposed algorithms in terms of lookup accuracy, memory and access efficiency.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Given a dataset - composed of - subsets with each data item belonging to one of them, multiset membership lookup takes an item - as input and outputs a binary answer whether - and, in case of yes, the ID of the subset to which - belongs. Overlaid upon while more sophisticated than the canonical membership lookup, multiset membership lookup emerges as a pivotal functionality in many computing and networking paradigms. The quest to achieve high-speed, high-accuracy lookup with limited memory cost makes lookup algorithm design a challenging task, particularly when the data items arrive as a stream. In this paper, we devise compact data structures and lookup algorithms that are amendable for hardware implementation, while guaranteeing high lookup accuracy and supporting interactive query processing. We first propose multi-hash color table, a variant of Bloom filter, to encode subset IDs compactly and map the ID of an item to its subset ID. We further construct a more balanced data structure called balanced multi-hash color table to improve the compactness by integrating the state-of-the-art load balancing technique. We complete our work by addressing the case of batch arrivals and design a batched recording algorithm optimizing the memory efficiency. We give both theoretical and empirical analysis to characterize and evaluate the performance of the proposed algorithms in terms of lookup accuracy, memory and access efficiency.",
"title": "Multiset Membership Lookup in Large Datasets",
"normalizedTitle": "Multiset Membership Lookup in Large Datasets",
"fno": "09314921",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Computational Complexity",
"Data Structures",
"Optimisation",
"Query Processing",
"Resource Allocation",
"Table Lookup",
"Multiset Membership Lookup",
"Data Item",
"Canonical Membership Lookup",
"High Accuracy Lookup",
"Lookup Algorithm Design",
"Compact Data Structures",
"Lookup Algorithms",
"High Lookup Accuracy",
"Supporting Interactive Query Processing",
"Subset ID",
"Balanced Data Structure",
"Image Color Analysis",
"Data Structures",
"Hash Functions",
"Memory Management",
"Data Mining",
"Query Processing",
"Color",
"Multiset Membership Lookup",
"Data Stream Mining"
],
"authors": [
{
"givenName": "Lin",
"surname": "Chen",
"fullName": "Lin Chen",
"affiliation": "School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, Guangdong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jihong",
"surname": "Yu",
"fullName": "Jihong Yu",
"affiliation": "School of Information and Electronics, Beijing Institute of Technology, Beijing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "10",
"pubDate": "2022-10-01 00:00:00",
"pubType": "trans",
"pages": "4947-4958",
"year": "2022",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tk/2023/05/09712197",
"title": "Fast LDP-MST: An Efficient Density-Peak-Based Clustering Method for Large-Size Datasets",
"doi": null,
"abstractUrl": "/journal/tk/2023/05/09712197/1AUkecqbRok",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2023/06/09920009",
"title": "A Unified Cryptoprocessor for Lattice-Based Signature and Key-Exchange",
"doi": null,
"abstractUrl": "/journal/tc/2023/06/09920009/1HxSozW28Qo",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/sc/2022/01/08826379",
"title": "Achieving One-Round Password-Based Authenticated Key Exchange over Lattices",
"doi": null,
"abstractUrl": "/journal/sc/2022/01/08826379/1d6xzconoJO",
"parentPublication": {
"id": "trans/sc",
"title": "IEEE Transactions on Services Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2021/12/09007415",
"title": "Flexible Aggregate Nearest Neighbor Queries and its Keyword-Aware Variant on Road Networks",
"doi": null,
"abstractUrl": "/journal/tk/2021/12/09007415/1hJKhc0u1So",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/01/09039684",
"title": "HyperMinHash: MinHash in LogLog Space",
"doi": null,
"abstractUrl": "/journal/tk/2022/01/09039684/1igS2G8DNfi",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2021/12/09110776",
"title": "Accelerated Variance Reduction Stochastic ADMM for Large-Scale Machine Learning",
"doi": null,
"abstractUrl": "/journal/tp/2021/12/09110776/1kuDlRSAfuw",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/07/09186333",
"title": "<italic>LShape</italic> Partitioning: Parallel Skyline Query Processing Using <inline-formula><tex-math notation=\"LaTeX\">Z_$MapReduce$_Z</tex-math></inline-formula>",
"doi": null,
"abstractUrl": "/journal/tk/2022/07/09186333/1mP21G1r2QE",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/07/09199134",
"title": "Computing K-Cores in Large Uncertain Graphs: An Index-Based Optimal Approach",
"doi": null,
"abstractUrl": "/journal/tk/2022/07/09199134/1naBq7vTUIw",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2022/05/09423579",
"title": "Constructing Completely Independent Spanning Trees in a Family of Line-Graph-Based Data Center Networks",
"doi": null,
"abstractUrl": "/journal/tc/2022/05/09423579/1tkyeT8TOwg",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/03/09525250",
"title": "Fast Reachability Queries Answering Based on <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathsf{RCN}$_Z</tex-math></inline-formula> Reduction",
"doi": null,
"abstractUrl": "/journal/tk/2023/03/09525250/1wuoOp439OU",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09298881",
"articleId": "1pF1NKMV76U",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09314916",
"articleId": "1qaz7rC9EuA",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1GBRdeHFguk",
"name": "ttk202210-09314921s1-supp1-3049624.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttk202210-09314921s1-supp1-3049624.pdf",
"extension": "pdf",
"size": "250 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1GF6jMpqNjy",
"title": "Oct.",
"year": "2022",
"issueNum": "10",
"idPrefix": "tp",
"pubType": "journal",
"volume": "44",
"label": "Oct.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1vmGPn3Y96U",
"doi": "10.1109/TPAMI.2021.3097804",
"abstract": "This paper presents a comprehensive underwater visual reconstruction paradigm that comprises three procedures, i.e., the E-procedure, the R-procedure, and the H-procedure. The E-procedure <inline-formula><tex-math notation=\"LaTeX\">Z_$enhance$_Z</tex-math></inline-formula>s original underwater images based on color compensation balance and weighted image fusion, yielding restored color, sharpened edges, and global contrast. The R-procedure <inline-formula><tex-math notation=\"LaTeX\">Z_$register$_Z</tex-math></inline-formula>s multiple enhanced underwater images by exploiting global similarity and local deformation. The H-procedure <inline-formula><tex-math notation=\"LaTeX\">Z_$homogenize$_Z</tex-math></inline-formula>s the registered underwater images by multi-scale composition strategy, which eliminates the inhomogeneous transition and brightness difference across overlapping regions, resulting in a reconstructed wide-field underwater image with comfortable and natural visibility. The three procedures operate in a cascade where the former procedure processes underwater images in a way that facilitates the latter one. We refer to the overall three procedures as the Enhancement-Registration-Homogenization (ERH) paradigm. Comprehensive qualitative and quantitative empirical evaluations reveal that our ERH paradigm outperforms state-of-the-art visual reconstruction methods, including the AutoStitch, APAP, SPHP, APNAP, and REW.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents a comprehensive underwater visual reconstruction paradigm that comprises three procedures, i.e., the E-procedure, the R-procedure, and the H-procedure. The E-procedure <inline-formula><tex-math notation=\"LaTeX\">$enhance$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mi>h</mml:mi><mml:mi>a</mml:mi><mml:mi>n</mml:mi><mml:mi>c</mml:mi><mml:mi>e</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href=\"chang-ieq1-3097804.gif\"/></alternatives></inline-formula>s original underwater images based on color compensation balance and weighted image fusion, yielding restored color, sharpened edges, and global contrast. The R-procedure <inline-formula><tex-math notation=\"LaTeX\">$register$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>r</mml:mi><mml:mi>e</mml:mi><mml:mi>g</mml:mi><mml:mi>i</mml:mi><mml:mi>s</mml:mi><mml:mi>t</mml:mi><mml:mi>e</mml:mi><mml:mi>r</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href=\"chang-ieq2-3097804.gif\"/></alternatives></inline-formula>s multiple enhanced underwater images by exploiting global similarity and local deformation. The H-procedure <inline-formula><tex-math notation=\"LaTeX\">$homogenize$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>h</mml:mi><mml:mi>o</mml:mi><mml:mi>m</mml:mi><mml:mi>o</mml:mi><mml:mi>g</mml:mi><mml:mi>e</mml:mi><mml:mi>n</mml:mi><mml:mi>i</mml:mi><mml:mi>z</mml:mi><mml:mi>e</mml:mi></mml:mrow></mml:math><inline-graphic xlink:href=\"chang-ieq3-3097804.gif\"/></alternatives></inline-formula>s the registered underwater images by multi-scale composition strategy, which eliminates the inhomogeneous transition and brightness difference across overlapping regions, resulting in a reconstructed wide-field underwater image with comfortable and natural visibility. The three procedures operate in a cascade where the former procedure processes underwater images in a way that facilitates the latter one. We refer to the overall three procedures as the Enhancement-Registration-Homogenization (ERH) paradigm. Comprehensive qualitative and quantitative empirical evaluations reveal that our ERH paradigm outperforms state-of-the-art visual reconstruction methods, including the AutoStitch, APAP, SPHP, APNAP, and REW.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents a comprehensive underwater visual reconstruction paradigm that comprises three procedures, i.e., the E-procedure, the R-procedure, and the H-procedure. The E-procedure -s original underwater images based on color compensation balance and weighted image fusion, yielding restored color, sharpened edges, and global contrast. The R-procedure -s multiple enhanced underwater images by exploiting global similarity and local deformation. The H-procedure -s the registered underwater images by multi-scale composition strategy, which eliminates the inhomogeneous transition and brightness difference across overlapping regions, resulting in a reconstructed wide-field underwater image with comfortable and natural visibility. The three procedures operate in a cascade where the former procedure processes underwater images in a way that facilitates the latter one. We refer to the overall three procedures as the Enhancement-Registration-Homogenization (ERH) paradigm. Comprehensive qualitative and quantitative empirical evaluations reveal that our ERH paradigm outperforms state-of-the-art visual reconstruction methods, including the AutoStitch, APAP, SPHP, APNAP, and REW.",
"title": "Enhancement-Registration-Homogenization (ERH): A Comprehensive Underwater Visual Reconstruction Paradigm",
"normalizedTitle": "Enhancement-Registration-Homogenization (ERH): A Comprehensive Underwater Visual Reconstruction Paradigm",
"fno": "09490352",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Edge Detection",
"Feature Extraction",
"Image Colour Analysis",
"Image Denoising",
"Image Enhancement",
"Image Fusion",
"Image Matching",
"Image Reconstruction",
"Image Registration",
"Image Restoration",
"Image Segmentation",
"Image Sensors",
"Registered Underwater Images",
"Wide Field Underwater Image",
"Enhancement Registration Homogenization Paradigm",
"Quantitative Empirical Evaluations",
"ERH Paradigm",
"State Of The Art Visual Reconstruction Methods",
"Comprehensive Underwater Visual Reconstruction Paradigm",
"E Procedure",
"R Procedure",
"H Procedure",
"Original Underwater Images",
"Color Compensation Balance",
"Weighted Image Fusion",
"Multiple Enhanced Underwater Images",
"Global Similarity",
"Local Deformation",
"Image Color Analysis",
"Image Reconstruction",
"Visualization",
"Nonhomogeneous Media",
"Image Restoration",
"Image Fusion",
"Image Edge Detection",
"Image Registration",
"Multi Scale Composition",
"Underwater Image Reconstruction"
],
"authors": [
{
"givenName": "Huajun",
"surname": "Song",
"fullName": "Huajun Song",
"affiliation": "College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, Shandong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Laibin",
"surname": "Chang",
"fullName": "Laibin Chang",
"affiliation": "College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, Shandong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ziwei",
"surname": "Chen",
"fullName": "Ziwei Chen",
"affiliation": "College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, Shandong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peng",
"surname": "Ren",
"fullName": "Peng Ren",
"affiliation": "College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, Shandong, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "10",
"pubDate": "2022-10-01 00:00:00",
"pubType": "trans",
"pages": "6953-6967",
"year": "2022",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/sc/2021/06/08705372",
"title": "Scheduling Real-Time Security Aware Tasks in Fog Networks",
"doi": null,
"abstractUrl": "/journal/sc/2021/06/08705372/19JpNnOBEY0",
"parentPublication": {
"id": "trans/sc",
"title": "IEEE Transactions on Services Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2021/06/08964488",
"title": "Efficient Compression and Indexing for Highly Repetitive DNA Sequence Collections",
"doi": null,
"abstractUrl": "/journal/tb/2021/06/08964488/1gLZGsjhZkc",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/01/09037115",
"title": "Aligning Points to Lines: Provable Approximations",
"doi": null,
"abstractUrl": "/journal/tk/2022/01/09037115/1igMO6tI3Is",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ec/2022/01/09188026",
"title": "Design of Unsigned Approximate Hybrid Dividers Based on Restoring Array and Logarithmic Dividers",
"doi": null,
"abstractUrl": "/journal/ec/2022/01/09188026/1mXkkeEoISY",
"parentPublication": {
"id": "trans/ec",
"title": "IEEE Transactions on Emerging Topics in Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/06/09294112",
"title": "Geometry-Aware Generation of Adversarial Point Clouds",
"doi": null,
"abstractUrl": "/journal/tp/2022/06/09294112/1pA8gc6H8dO",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/08/09369083",
"title": "Robust Low-Tubal-Rank Tensor Recovery From Binary Measurements",
"doi": null,
"abstractUrl": "/journal/tp/2022/08/09369083/1rFvS23KDAI",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/03/09525250",
"title": "Fast Reachability Queries Answering Based on <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathsf{RCN}$_Z</tex-math></inline-formula> Reduction",
"doi": null,
"abstractUrl": "/journal/tk/2023/03/09525250/1wuoOp439OU",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2022/07/09585362",
"title": "A Fast <inline-formula><tex-math notation=\"LaTeX\">Z_$f(r,k+1)/k$_Z</tex-math></inline-formula>-Diagnosis for Interconnection Networks Under MM* Model",
"doi": null,
"abstractUrl": "/journal/td/2022/07/09585362/1y11LlQdiGk",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tq/2023/01/09615013",
"title": "Privacy-Preserving Proof-of-Location With Security Against Geo-Tampering",
"doi": null,
"abstractUrl": "/journal/tq/2023/01/09615013/1yyhBtMPBss",
"parentPublication": {
"id": "trans/tq",
"title": "IEEE Transactions on Dependable and Secure Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2022/10/09662259",
"title": "CoPA: Cold Page Awakening to Overcome Retention Failures in STT-MRAM Based I/O Buffers",
"doi": null,
"abstractUrl": "/journal/td/2022/10/09662259/1zzlhhawmCQ",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09446583",
"articleId": "1u8ltrH1neU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09448409",
"articleId": "1ugE4OYu2Xu",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1IWfo7586pG",
"title": "Nov.-Dec.",
"year": "2022",
"issueNum": "06",
"idPrefix": "tb",
"pubType": "journal",
"volume": "19",
"label": "Nov.-Dec.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1yA73pVevu0",
"doi": "10.1109/TCBB.2021.3128381",
"abstract": "Suppose we aim to build a phylogeny for a set of taxa <inline-formula><tex-math notation=\"LaTeX\">Z_$X$_Z</tex-math></inline-formula> using information from a collection of loci, where each locus offers information for only a fraction of the taxa. The question is whether, based solely on the pattern of data availability, called a <italic>taxon coverage pattern</italic>, one can determine if the data suffices to construct a reliable phylogeny. The problem can be expressed combinatorially as follows. Let us call a taxon coverage pattern <italic>decisive</italic> if, for any binary phylogenetic tree <inline-formula><tex-math notation=\"LaTeX\">Z_$T$_Z</tex-math></inline-formula> for <inline-formula><tex-math notation=\"LaTeX\">Z_$X$_Z</tex-math></inline-formula>, the collection of phylogenetic trees obtained by restricting <inline-formula><tex-math notation=\"LaTeX\">Z_$T$_Z</tex-math></inline-formula> to the subset of <inline-formula><tex-math notation=\"LaTeX\">Z_$X$_Z</tex-math></inline-formula> covered by each locus uniquely determines <inline-formula><tex-math notation=\"LaTeX\">Z_$T$_Z</tex-math></inline-formula>. Here we relate the problem of checking whether a taxon coverage pattern is decisive to a hypergraph coloring problem. Using this connection, we (1) show that checking decisiveness is co-NP complete; (2) obtain lower bounds on the amount of coverage needed to achieve decisiveness; (3) devise an exact algorithm for decisiveness; (4) develop problem reduction rules, and use them to obtain efficient algorithms for inputs with few loci; and (5) devise Boolean satisfiability (SAT) and integer linear programming formulations (ILP) of decisiveness that allow us to analyze data sets that arise in practice. For data sets that are not decisive, we use our SAT and ILP formulations to obtain decisive subsets of the data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Suppose we aim to build a phylogeny for a set of taxa <inline-formula><tex-math notation=\"LaTeX\">$X$</tex-math><alternatives><mml:math><mml:mi>X</mml:mi></mml:math><inline-graphic xlink:href=\"fernandezbaca-ieq1-3128381.gif\"/></alternatives></inline-formula> using information from a collection of loci, where each locus offers information for only a fraction of the taxa. The question is whether, based solely on the pattern of data availability, called a <italic>taxon coverage pattern</italic>, one can determine if the data suffices to construct a reliable phylogeny. The problem can be expressed combinatorially as follows. Let us call a taxon coverage pattern <italic>decisive</italic> if, for any binary phylogenetic tree <inline-formula><tex-math notation=\"LaTeX\">$T$</tex-math><alternatives><mml:math><mml:mi>T</mml:mi></mml:math><inline-graphic xlink:href=\"fernandezbaca-ieq2-3128381.gif\"/></alternatives></inline-formula> for <inline-formula><tex-math notation=\"LaTeX\">$X$</tex-math><alternatives><mml:math><mml:mi>X</mml:mi></mml:math><inline-graphic xlink:href=\"fernandezbaca-ieq3-3128381.gif\"/></alternatives></inline-formula>, the collection of phylogenetic trees obtained by restricting <inline-formula><tex-math notation=\"LaTeX\">$T$</tex-math><alternatives><mml:math><mml:mi>T</mml:mi></mml:math><inline-graphic xlink:href=\"fernandezbaca-ieq4-3128381.gif\"/></alternatives></inline-formula> to the subset of <inline-formula><tex-math notation=\"LaTeX\">$X$</tex-math><alternatives><mml:math><mml:mi>X</mml:mi></mml:math><inline-graphic xlink:href=\"fernandezbaca-ieq5-3128381.gif\"/></alternatives></inline-formula> covered by each locus uniquely determines <inline-formula><tex-math notation=\"LaTeX\">$T$</tex-math><alternatives><mml:math><mml:mi>T</mml:mi></mml:math><inline-graphic xlink:href=\"fernandezbaca-ieq6-3128381.gif\"/></alternatives></inline-formula>. Here we relate the problem of checking whether a taxon coverage pattern is decisive to a hypergraph coloring problem. Using this connection, we (1) show that checking decisiveness is co-NP complete; (2) obtain lower bounds on the amount of coverage needed to achieve decisiveness; (3) devise an exact algorithm for decisiveness; (4) develop problem reduction rules, and use them to obtain efficient algorithms for inputs with few loci; and (5) devise Boolean satisfiability (SAT) and integer linear programming formulations (ILP) of decisiveness that allow us to analyze data sets that arise in practice. For data sets that are not decisive, we use our SAT and ILP formulations to obtain decisive subsets of the data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Suppose we aim to build a phylogeny for a set of taxa - using information from a collection of loci, where each locus offers information for only a fraction of the taxa. The question is whether, based solely on the pattern of data availability, called a taxon coverage pattern, one can determine if the data suffices to construct a reliable phylogeny. The problem can be expressed combinatorially as follows. Let us call a taxon coverage pattern decisive if, for any binary phylogenetic tree - for -, the collection of phylogenetic trees obtained by restricting - to the subset of - covered by each locus uniquely determines -. Here we relate the problem of checking whether a taxon coverage pattern is decisive to a hypergraph coloring problem. Using this connection, we (1) show that checking decisiveness is co-NP complete; (2) obtain lower bounds on the amount of coverage needed to achieve decisiveness; (3) devise an exact algorithm for decisiveness; (4) develop problem reduction rules, and use them to obtain efficient algorithms for inputs with few loci; and (5) devise Boolean satisfiability (SAT) and integer linear programming formulations (ILP) of decisiveness that allow us to analyze data sets that arise in practice. For data sets that are not decisive, we use our SAT and ILP formulations to obtain decisive subsets of the data.",
"title": "Checking Phylogenetics Decisiveness in Theory and in Practice",
"normalizedTitle": "Checking Phylogenetics Decisiveness in Theory and in Practice",
"fno": "09616390",
"hasPdf": true,
"idPrefix": "tb",
"keywords": [
"Biology Computing",
"Boolean Functions",
"Computability",
"Computational Complexity",
"Data Analysis",
"Evolution Biological",
"Genetics",
"Graph Colouring",
"Integer Programming",
"Linear Programming",
"Set Theory",
"Trees Mathematics",
"Binary Phylogenetic Tree",
"Boolean Satisfiability",
"Co NP Complete",
"Data Availability",
"Data Set Analysis",
"Decisive Subsets",
"Hypergraph Coloring Problem",
"ILP",
"Integer Linear Programming",
"Phylogenetic Decisiveness",
"Phylogeny",
"Problem Reduction Rules",
"SAT",
"Taxon Coverage Pattern",
"Phylogeny",
"Partitioning Algorithms",
"Color",
"Terminology",
"Steel",
"Software",
"Reliability",
"Phylogenetic Tree",
"Taxon Coverage",
"Algorithms",
"No Rainbow Hypergraph Coloring",
"Integer Linear Programming",
"Satisfiability"
],
"authors": [
{
"givenName": "Ghazaleh",
"surname": "Parvini",
"fullName": "Ghazaleh Parvini",
"affiliation": "College of Information & Computer Sciences, University of Massachusetts Amherst, Amherst, MA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Katherine",
"surname": "Braught",
"fullName": "Katherine Braught",
"affiliation": "Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "David",
"surname": "Fernańdez-Baca",
"fullName": "David Fernańdez-Baca",
"affiliation": "Department of Computer Science, Iowa State University, Ames, IA, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2022-11-01 00:00:00",
"pubType": "trans",
"pages": "3307-3316",
"year": "2022",
"issn": "1545-5963",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tp/2023/04/09861690",
"title": "Optimizing Partial Area Under the Top-k Curve: Theory and Practice",
"doi": null,
"abstractUrl": "/journal/tp/2023/04/09861690/1FWhV30RnNe",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2023/01/09930647",
"title": "The High Faulty Tolerant Capability of the Alternating Group Graphs",
"doi": null,
"abstractUrl": "/journal/td/2023/01/09930647/1HMP3UkhGus",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/07/09186333",
"title": "<italic>LShape</italic> Partitioning: Parallel Skyline Query Processing Using <inline-formula><tex-math notation=\"LaTeX\">Z_$MapReduce$_Z</tex-math></inline-formula>",
"doi": null,
"abstractUrl": "/journal/tk/2022/07/09186333/1mP21G1r2QE",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/08/09244575",
"title": "Distributed Density Peaks Clustering Revisited",
"doi": null,
"abstractUrl": "/journal/tk/2022/08/09244575/1ojYk1yEY1i",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/09/09250607",
"title": "Enumerating Maximum Cliques in Massive Graphs",
"doi": null,
"abstractUrl": "/journal/tk/2022/09/09250607/1oxjS6MBaA8",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/04/09354552",
"title": "An Asymmetric Alignment Algorithm for Estimating Ancestor-Descendant Edit Distance for Tandem Repeats",
"doi": null,
"abstractUrl": "/journal/tb/2022/04/09354552/1reXbdTv8QM",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2022/05/09423579",
"title": "Constructing Completely Independent Spanning Trees in a Family of Line-Graph-Based Data Center Networks",
"doi": null,
"abstractUrl": "/journal/tc/2022/05/09423579/1tkyeT8TOwg",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/06/09535228",
"title": "Improved Fixed-Parameter Algorithm for the Tree Containment Problem on Unrooted Phylogenetic Network",
"doi": null,
"abstractUrl": "/journal/tb/2022/06/09535228/1wMEIAs9pni",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/03/09580703",
"title": "Efficient and Optimal Algorithms for Tree Summarization With Weighted Terminologies",
"doi": null,
"abstractUrl": "/journal/tk/2023/03/09580703/1xPnZzu3u9O",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2022/10/09665221",
"title": "An Efficient Index-Based Approach to Distributed Set Reachability on Small-World Graphs",
"doi": null,
"abstractUrl": "/journal/td/2022/10/09665221/1zJiQNKABEs",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09527082",
"articleId": "1wzrIdwmvhS",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09594710",
"articleId": "1y5Z15USITe",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNAnuTvo",
"title": "Nov.",
"year": "2016",
"issueNum": "11",
"idPrefix": "tg",
"pubType": "journal",
"volume": "22",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUzp02ot",
"doi": "10.1109/TVCG.2016.2593780",
"abstract": "In augmented reality (AR) applications, a virtual avatar serves as a useful medium to represent a human in a different place. This paper deals with the problem of retargeting a human motion to an avatar. In particular, we present a novel method that retargets a human motion with respect to an object to that of an avatar with respect to a different object of a similar shape. To achieve this, we developed a spatial map that defines the correspondences between any points in the 3D spaces around the respective objects. The key advantage of the spatial map is that it identifies the desired locations of the avatar's body parts for any input motion of a human. Once the spatial map is created offline, the motion retargeting can be performed in real-time. The retargeted motion preserves important features of the original motion such as the human pose and the spatial relation with the object. We report the results of a number of experiments that demonstrate the effectiveness of the proposed method.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In augmented reality (AR) applications, a virtual avatar serves as a useful medium to represent a human in a different place. This paper deals with the problem of retargeting a human motion to an avatar. In particular, we present a novel method that retargets a human motion with respect to an object to that of an avatar with respect to a different object of a similar shape. To achieve this, we developed a spatial map that defines the correspondences between any points in the 3D spaces around the respective objects. The key advantage of the spatial map is that it identifies the desired locations of the avatar's body parts for any input motion of a human. Once the spatial map is created offline, the motion retargeting can be performed in real-time. The retargeted motion preserves important features of the original motion such as the human pose and the spatial relation with the object. We report the results of a number of experiments that demonstrate the effectiveness of the proposed method.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In augmented reality (AR) applications, a virtual avatar serves as a useful medium to represent a human in a different place. This paper deals with the problem of retargeting a human motion to an avatar. In particular, we present a novel method that retargets a human motion with respect to an object to that of an avatar with respect to a different object of a similar shape. To achieve this, we developed a spatial map that defines the correspondences between any points in the 3D spaces around the respective objects. The key advantage of the spatial map is that it identifies the desired locations of the avatar's body parts for any input motion of a human. Once the spatial map is created offline, the motion retargeting can be performed in real-time. The retargeted motion preserves important features of the original motion such as the human pose and the spatial relation with the object. We report the results of a number of experiments that demonstrate the effectiveness of the proposed method.",
"title": "Retargeting Human-Object Interaction to Virtual Avatars",
"normalizedTitle": "Retargeting Human-Object Interaction to Virtual Avatars",
"fno": "07523447",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Avatars",
"Shape",
"Three Dimensional Displays",
"Trajectory",
"Mesh Generation",
"Real Time Systems",
"Geometry",
"Avatar Animation",
"Motion Retargeting",
"Human Object Interaction",
"Augmented Reality",
"Telepresence"
],
"authors": [
{
"givenName": "Yeonjoon",
"surname": "Kim",
"fullName": "Yeonjoon Kim",
"affiliation": "Korea Advanced Institute of Science and Technology (KAIST)",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hangil",
"surname": "Park",
"fullName": "Hangil Park",
"affiliation": "Korea Advanced Institute of Science and Technology (KAIST)",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Seungbae",
"surname": "Bang",
"fullName": "Seungbae Bang",
"affiliation": "Korea Advanced Institute of Science and Technology (KAIST)",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sung-Hee",
"surname": "Lee",
"fullName": "Sung-Hee Lee",
"affiliation": "Korea Advanced Institute of Science and Technology (KAIST)",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2016-11-01 00:00:00",
"pubType": "trans",
"pages": "2405-2412",
"year": "2016",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/2010/6984/0/05540162",
"title": "Hybrid shift map for video retargeting",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2010/05540162/12OmNx0RIXh",
"parentPublication": {
"id": "proceedings/cvpr/2010/6984/0",
"title": "2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2007/1016/0/04284819",
"title": "Real-Time Humanoid Avatar for Multimodal Human-Machine Interaction",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2007/04284819/12OmNzkMlMm",
"parentPublication": {
"id": "proceedings/icme/2007/1016/0",
"title": "2007 International Conference on Multimedia & Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08446152",
"title": "Simulating Movement Interactions Between Avatars & Agents in Virtual Worlds Using Human Motion Constraints",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08446152/13bd1tMztYH",
"parentPublication": {
"id": "proceedings/vr/2018/3365/0",
"title": "2018 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2013/04/ttg2013040583",
"title": "Human Tails: Ownership and Control of Extended Humanoid Avatars",
"doi": null,
"abstractUrl": "/journal/tg/2013/04/ttg2013040583/13rRUxYrbUF",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdh/2018/9497/0/949700a329",
"title": "A Motion Retargeting Method with Footstep Constraints",
"doi": null,
"abstractUrl": "/proceedings-article/icdh/2018/949700a329/17D45WK5Akh",
"parentPublication": {
"id": "proceedings/icdh/2018/9497/0",
"title": "2018 7th International Conference on Digital Home (ICDH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200j700",
"title": "Contact-Aware Retargeting of Skinned Motion",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200j700/1BmIsrlulzO",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2022/5670/0/567000a197",
"title": "HVTR: Hybrid Volumetric-Textural Rendering for Human Avatars",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2022/567000a197/1KYsovTRTC8",
"parentPublication": {
"id": "proceedings/3dv/2022/5670/0",
"title": "2022 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2020/6532/0/09090443",
"title": "MotionNote: A Novel Human Pose Representation",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2020/09090443/1jIxlFindEk",
"parentPublication": {
"id": "proceedings/vrw/2020/6532/0",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/02/09157962",
"title": "Facial Expression Retargeting From Human to Avatar Made Easy",
"doi": null,
"abstractUrl": "/journal/tg/2022/02/09157962/1m1eKuAoOoE",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/03/09173828",
"title": "Placement Retargeting of Virtual Avatars to Dissimilar Indoor Environments",
"doi": null,
"abstractUrl": "/journal/tg/2022/03/09173828/1mtsbpUceNG",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07523388",
"articleId": "13rRUxBJhvy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07523400",
"articleId": "13rRUy0HYRu",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1MNboCLDDZC",
"title": "June",
"year": "2023",
"issueNum": "06",
"idPrefix": "tk",
"pubType": "journal",
"volume": "35",
"label": "June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1DQLK4ory9y",
"doi": "10.1109/TKDE.2022.3175814",
"abstract": "Given a source node <inline-formula><tex-math notation=\"LaTeX\">Z_$s$_Z</tex-math></inline-formula> and a target node <inline-formula><tex-math notation=\"LaTeX\">Z_$t$_Z</tex-math></inline-formula> in a graph <inline-formula><tex-math notation=\"LaTeX\">Z_$G$_Z</tex-math></inline-formula>, the Personalized PageRank (PPR) from <inline-formula><tex-math notation=\"LaTeX\">Z_$s$_Z</tex-math></inline-formula> to <inline-formula><tex-math notation=\"LaTeX\">Z_$t$_Z</tex-math></inline-formula> is the probability of a random walk starting from <inline-formula><tex-math notation=\"LaTeX\">Z_$s$_Z</tex-math></inline-formula> terminates at <inline-formula><tex-math notation=\"LaTeX\">Z_$t$_Z</tex-math></inline-formula>. PPR is a classic measure of the relevance between two nodes in a graph. It has been applied in numerous real-world systems. However, existing techniques for PPR queries are not robust to dynamic real-world graphs, which typically have different evolving speeds. Their performance is significantly degraded either at a lower graph evolving rate (e.g., much more queries than updates) or a higher rate. To address the above deficiencies, we propose <italic>Agenda</italic> to efficiently process, with strong approximation guarantees, the single-source PPR (SSPPR) queries on dynamically evolving graphs with various evolving speeds. Compared with previous methods, <italic>Agenda</italic> has significantly better workload robustness, while ensuring the same result accuracy. <italic>Agenda</italic> also has theoretically-guaranteed small query and update costs. Experiments on up to billion-edge scale graphs show that <italic>Agenda</italic> significantly outperforms state-of-the-art methods for various query/update workloads, while maintaining better or comparable approximation accuracies.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Given a source node <inline-formula><tex-math notation=\"LaTeX\">$s$</tex-math><alternatives><mml:math><mml:mi>s</mml:mi></mml:math><inline-graphic xlink:href=\"mo-ieq1-3175814.gif\"/></alternatives></inline-formula> and a target node <inline-formula><tex-math notation=\"LaTeX\">$t$</tex-math><alternatives><mml:math><mml:mi>t</mml:mi></mml:math><inline-graphic xlink:href=\"mo-ieq2-3175814.gif\"/></alternatives></inline-formula> in a graph <inline-formula><tex-math notation=\"LaTeX\">$G$</tex-math><alternatives><mml:math><mml:mi>G</mml:mi></mml:math><inline-graphic xlink:href=\"mo-ieq3-3175814.gif\"/></alternatives></inline-formula>, the Personalized PageRank (PPR) from <inline-formula><tex-math notation=\"LaTeX\">$s$</tex-math><alternatives><mml:math><mml:mi>s</mml:mi></mml:math><inline-graphic xlink:href=\"mo-ieq4-3175814.gif\"/></alternatives></inline-formula> to <inline-formula><tex-math notation=\"LaTeX\">$t$</tex-math><alternatives><mml:math><mml:mi>t</mml:mi></mml:math><inline-graphic xlink:href=\"mo-ieq5-3175814.gif\"/></alternatives></inline-formula> is the probability of a random walk starting from <inline-formula><tex-math notation=\"LaTeX\">$s$</tex-math><alternatives><mml:math><mml:mi>s</mml:mi></mml:math><inline-graphic xlink:href=\"mo-ieq6-3175814.gif\"/></alternatives></inline-formula> terminates at <inline-formula><tex-math notation=\"LaTeX\">$t$</tex-math><alternatives><mml:math><mml:mi>t</mml:mi></mml:math><inline-graphic xlink:href=\"mo-ieq7-3175814.gif\"/></alternatives></inline-formula>. PPR is a classic measure of the relevance between two nodes in a graph. It has been applied in numerous real-world systems. However, existing techniques for PPR queries are not robust to dynamic real-world graphs, which typically have different evolving speeds. Their performance is significantly degraded either at a lower graph evolving rate (e.g., much more queries than updates) or a higher rate. To address the above deficiencies, we propose <italic>Agenda</italic> to efficiently process, with strong approximation guarantees, the single-source PPR (SSPPR) queries on dynamically evolving graphs with various evolving speeds. Compared with previous methods, <italic>Agenda</italic> has significantly better workload robustness, while ensuring the same result accuracy. <italic>Agenda</italic> also has theoretically-guaranteed small query and update costs. Experiments on up to billion-edge scale graphs show that <italic>Agenda</italic> significantly outperforms state-of-the-art methods for various query/update workloads, while maintaining better or comparable approximation accuracies.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Given a source node - and a target node - in a graph -, the Personalized PageRank (PPR) from - to - is the probability of a random walk starting from - terminates at -. PPR is a classic measure of the relevance between two nodes in a graph. It has been applied in numerous real-world systems. However, existing techniques for PPR queries are not robust to dynamic real-world graphs, which typically have different evolving speeds. Their performance is significantly degraded either at a lower graph evolving rate (e.g., much more queries than updates) or a higher rate. To address the above deficiencies, we propose Agenda to efficiently process, with strong approximation guarantees, the single-source PPR (SSPPR) queries on dynamically evolving graphs with various evolving speeds. Compared with previous methods, Agenda has significantly better workload robustness, while ensuring the same result accuracy. Agenda also has theoretically-guaranteed small query and update costs. Experiments on up to billion-edge scale graphs show that Agenda significantly outperforms state-of-the-art methods for various query/update workloads, while maintaining better or comparable approximation accuracies.",
"title": "Single-Source Personalized PageRanks With Workload Robustness",
"normalizedTitle": "Single-Source Personalized PageRanks With Workload Robustness",
"fno": "09785611",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Social Networking Online",
"Indexes",
"Blogs",
"Costs",
"Robustness",
"Heuristic Algorithms",
"Query Processing",
"Graphs Algorithms",
"Personalized Pageranks",
"Query Processing"
],
"authors": [
{
"givenName": "Dingheng",
"surname": "Mo",
"fullName": "Dingheng Mo",
"affiliation": "School of Computer Science and Engineering, Nanyang Technological University, Singapore",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Siqiang",
"surname": "Luo",
"fullName": "Siqiang Luo",
"affiliation": "School of Computer Science and Engineering, Nanyang Technological University, Singapore",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2023-06-01 00:00:00",
"pubType": "trans",
"pages": "6320-6334",
"year": "2023",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/sc/2022/02/08966480",
"title": "Reverse Nearest Neighbor Search in Semantic Trajectories for Location-Based Services",
"doi": null,
"abstractUrl": "/journal/sc/2022/02/08966480/1gNEzYzsFAk",
"parentPublication": {
"id": "trans/sc",
"title": "IEEE Transactions on Services Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/07/09199134",
"title": "Computing K-Cores in Large Uncertain Graphs: An Index-Based Optimal Approach",
"doi": null,
"abstractUrl": "/journal/tk/2022/07/09199134/1naBq7vTUIw",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/09/09250607",
"title": "Enumerating Maximum Cliques in Massive Graphs",
"doi": null,
"abstractUrl": "/journal/tk/2022/09/09250607/1oxjS6MBaA8",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/09/09269479",
"title": "Efficient Radius-Bounded Community Search in Geo-Social Networks",
"doi": null,
"abstractUrl": "/journal/tk/2022/09/09269479/1p1c8tla0DK",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/01/09444852",
"title": "Edge Manipulation Approaches for K-Core Minimization: Metrics and Analytics",
"doi": null,
"abstractUrl": "/journal/tk/2023/01/09444852/1u51rOHi1MY",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/02/09511141",
"title": "Partition-Aware Graph Pattern Based Node Matching With Updates",
"doi": null,
"abstractUrl": "/journal/tk/2023/02/09511141/1vXcMOXd7MY",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/02/09492838",
"title": "Maximum Signed <inline-formula><tex-math notation=\"LaTeX\">Z_$\\theta$_Z</tex-math></inline-formula>-Clique Identification in Large Signed Graphs",
"doi": null,
"abstractUrl": "/journal/tk/2023/02/09492838/1vq0EU6lrAA",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/03/09525250",
"title": "Fast Reachability Queries Answering Based on <inline-formula><tex-math notation=\"LaTeX\">Z_$\\mathsf{RCN}$_Z</tex-math></inline-formula> Reduction",
"doi": null,
"abstractUrl": "/journal/tk/2023/03/09525250/1wuoOp439OU",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/03/09546728",
"title": "Skyline Group Queries in Large Road-Social Networks Revisited",
"doi": null,
"abstractUrl": "/journal/tk/2023/03/09546728/1x6zArmoz72",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2022/10/09672729",
"title": "Spatial-Keyword Skyline Publish/Subscribe Query Processing Over Distributed Sliding Window Streaming Data",
"doi": null,
"abstractUrl": "/journal/tc/2022/10/09672729/1zWzLpjhFDy",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09767633",
"articleId": "1D4HcolUgMg",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09761762",
"articleId": "1CKMjMIWCE8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwCsdFw",
"title": "PrePrints",
"year": "5555",
"issueNum": "01",
"idPrefix": "tk",
"pubType": "journal",
"volume": null,
"label": "PrePrints",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1HYqASRP8Vq",
"doi": "10.1109/TKDE.2022.3218844",
"abstract": "<italic>Geo-social group</italic> queries, which return a social cohesive user group with a spatial constraint, have receive significant research interests due to their promising applications for group-based activity planning and scheduling in location-based social networks (LBSNs). However, existing studies on geo-social group queries mostly assume the users are stationary whereas in realistic LBSN application scenarios all users may continuously move over time. Thus, in this paper, we investigate the problem of <italic><underline>c</underline>ontinuous <underline>g</underline>eo-<underline>s</underline>ocial <underline>g</underline>roups <underline>m</underline>onitoring</italic> (<italic>CGSGM</italic>) over moving users. A challenge in answering CGSGM queries over moving users is how to efficiently update geo-social groups when users are continuously moving. To address the CGSGM problem, we first propose a baseline algorithm, namely <italic>Baseline-BB</italic>, which recomputes the new geo-social groups from scratch at each time instance by utilizing a branch and bound (BB) strategy. To improve the inefficiency of BB, we explore a new strategy, called common neighbor or neighbor expanding (CNNE), which expands the common neighbors of edges or the neighbors of users in intermediate groups to quickly produce the valid group combinations. Accordingly, another baseline algorithm, namely <italic>Baseline-CNNE</italic>, is proposed. As these baseline algorithms do not maintain intermediate results to facilitate further query processing, we develop an incremental algorithm, called <italic>incremental monitoring algorithm (IMA)</italic>, which maintains the support, common neighbors and the neighbors of current users when exploring possible user groups for further updates and query processing. Since IMA requires many times of truss decomposition when processing mutiple-users updates, we propose an improved incremental algorithm, called <italic>improved incremental monitoring algorithm (IIMA)</italic>, which performs truss decompostion only once. Moreover, we design algorithms for handling the social changes that result in insertion/deletion of some edges in the social network. Owing to the challenge in setting, an appropriate monitoring distance, we further study the top <inline-formula><tex-math notation=\"LaTeX\">Z_$N$_Z</tex-math></inline-formula> CGSGM problem, which finds top <inline-formula><tex-math notation=\"LaTeX\">Z_$N$_Z</tex-math></inline-formula> result groups at each time instance. Finally, we conduct extensive experiments using four real datasets to validate our ideas and evaluate the proposed algorithms.",
"abstracts": [
{
"abstractType": "Regular",
"content": "<italic>Geo-social group</italic> queries, which return a social cohesive user group with a spatial constraint, have receive significant research interests due to their promising applications for group-based activity planning and scheduling in location-based social networks (LBSNs). However, existing studies on geo-social group queries mostly assume the users are stationary whereas in realistic LBSN application scenarios all users may continuously move over time. Thus, in this paper, we investigate the problem of <italic><underline>c</underline>ontinuous <underline>g</underline>eo-<underline>s</underline>ocial <underline>g</underline>roups <underline>m</underline>onitoring</italic> (<italic>CGSGM</italic>) over moving users. A challenge in answering CGSGM queries over moving users is how to efficiently update geo-social groups when users are continuously moving. To address the CGSGM problem, we first propose a baseline algorithm, namely <italic>Baseline-BB</italic>, which recomputes the new geo-social groups from scratch at each time instance by utilizing a branch and bound (BB) strategy. To improve the inefficiency of BB, we explore a new strategy, called common neighbor or neighbor expanding (CNNE), which expands the common neighbors of edges or the neighbors of users in intermediate groups to quickly produce the valid group combinations. Accordingly, another baseline algorithm, namely <italic>Baseline-CNNE</italic>, is proposed. As these baseline algorithms do not maintain intermediate results to facilitate further query processing, we develop an incremental algorithm, called <italic>incremental monitoring algorithm (IMA)</italic>, which maintains the support, common neighbors and the neighbors of current users when exploring possible user groups for further updates and query processing. Since IMA requires many times of truss decomposition when processing mutiple-users updates, we propose an improved incremental algorithm, called <italic>improved incremental monitoring algorithm (IIMA)</italic>, which performs truss decompostion only once. Moreover, we design algorithms for handling the social changes that result in insertion/deletion of some edges in the social network. Owing to the challenge in setting, an appropriate monitoring distance, we further study the top <inline-formula><tex-math notation=\"LaTeX\">$N$</tex-math></inline-formula> CGSGM problem, which finds top <inline-formula><tex-math notation=\"LaTeX\">$N$</tex-math></inline-formula> result groups at each time instance. Finally, we conduct extensive experiments using four real datasets to validate our ideas and evaluate the proposed algorithms.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Geo-social group queries, which return a social cohesive user group with a spatial constraint, have receive significant research interests due to their promising applications for group-based activity planning and scheduling in location-based social networks (LBSNs). However, existing studies on geo-social group queries mostly assume the users are stationary whereas in realistic LBSN application scenarios all users may continuously move over time. Thus, in this paper, we investigate the problem of continuous geo-social groups monitoring (CGSGM) over moving users. A challenge in answering CGSGM queries over moving users is how to efficiently update geo-social groups when users are continuously moving. To address the CGSGM problem, we first propose a baseline algorithm, namely Baseline-BB, which recomputes the new geo-social groups from scratch at each time instance by utilizing a branch and bound (BB) strategy. To improve the inefficiency of BB, we explore a new strategy, called common neighbor or neighbor expanding (CNNE), which expands the common neighbors of edges or the neighbors of users in intermediate groups to quickly produce the valid group combinations. Accordingly, another baseline algorithm, namely Baseline-CNNE, is proposed. As these baseline algorithms do not maintain intermediate results to facilitate further query processing, we develop an incremental algorithm, called incremental monitoring algorithm (IMA), which maintains the support, common neighbors and the neighbors of current users when exploring possible user groups for further updates and query processing. Since IMA requires many times of truss decomposition when processing mutiple-users updates, we propose an improved incremental algorithm, called improved incremental monitoring algorithm (IIMA), which performs truss decompostion only once. Moreover, we design algorithms for handling the social changes that result in insertion/deletion of some edges in the social network. Owing to the challenge in setting, an appropriate monitoring distance, we further study the top - CGSGM problem, which finds top - result groups at each time instance. Finally, we conduct extensive experiments using four real datasets to validate our ideas and evaluate the proposed algorithms.",
"title": "Continuous Geo-Social Group Monitoring in Dynamic LBSNs",
"normalizedTitle": "Continuous Geo-Social Group Monitoring in Dynamic LBSNs",
"fno": "09935277",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Monitoring",
"Social Networking Online",
"Query Processing",
"Servers",
"Dynamic Scheduling",
"Spatial Databases",
"Planning",
"Continuous Queries",
"Geo Social Group Query",
"Location Based Services",
"Monitoring",
"Nearest Neighbor"
],
"authors": [
{
"givenName": "Huaijie",
"surname": "Zhu",
"fullName": "Huaijie Zhu",
"affiliation": "Sun Yat-Sen University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wei",
"surname": "Liu",
"fullName": "Wei Liu",
"affiliation": "Sun Yat-Sen University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jian",
"surname": "Yin",
"fullName": "Jian Yin",
"affiliation": "Sun Yat-Sen University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Libin",
"surname": "Zheng",
"fullName": "Libin Zheng",
"affiliation": "Sun Yat-Sen University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xin",
"surname": "Huang",
"fullName": "Xin Huang",
"affiliation": "Hong Kong Baptist University, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jianliang",
"surname": "Xu",
"fullName": "Jianliang Xu",
"affiliation": "Hong Kong Baptist University, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wang-Chien",
"surname": "Lee",
"fullName": "Wang-Chien Lee",
"affiliation": "Computer Science and Engineering, Penn State University, PA, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-11-01 00:00:00",
"pubType": "trans",
"pages": "1-14",
"year": "5555",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icde/2016/2020/0/07498399",
"title": "Geo-Social K-Cover Group queries for collaborative spatial computing",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2016/07498399/12OmNxu6p82",
"parentPublication": {
"id": "proceedings/icde/2016/2020/0",
"title": "2016 IEEE 32nd International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ic/2011/03/mic2011030020",
"title": "Location-Related Privacy in Geo-Social Networks",
"doi": null,
"abstractUrl": "/magazine/ic/2011/03/mic2011030020/13rRUB6SpTS",
"parentPublication": {
"id": "mags/ic",
"title": "IEEE Internet Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2018/05/08186182",
"title": "Density-Based Place Clustering Using Geo-Social Network Data",
"doi": null,
"abstractUrl": "/journal/tk/2018/05/08186182/13rRUy0HYS3",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/05/09713727",
"title": "Top-<italic>k</italic> Socio-Spatial Co-Engaged Location Selection for Social Users",
"doi": null,
"abstractUrl": "/journal/tk/2023/05/09713727/1AZKZ1MkncY",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300a312",
"title": "Continuous Geo-Social Group Monitoring over Moving Users",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300a312/1FwFboYjmOA",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09894074",
"title": "Willingness Maximization for Ego Network Data Extraction in Multiple Online Social Networks",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09894074/1GIq734SFLa",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ispa-bdcloud-socialcom-sustaincom/2022/6497/0/649700a443",
"title": "Learning to Process Topic Aware Queries on Geo-Textual Streaming Data",
"doi": null,
"abstractUrl": "/proceedings-article/ispa-bdcloud-socialcom-sustaincom/2022/649700a443/1LKwr4HoQsU",
"parentPublication": {
"id": "proceedings/ispa-bdcloud-socialcom-sustaincom/2022/6497/0",
"title": "2022 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mdm/2019/3363/0/336300a391",
"title": "Towards Usability on Reverse Top-k Geo-Social Keyword Query Results",
"doi": null,
"abstractUrl": "/proceedings-article/mdm/2019/336300a391/1ckrNUXqReE",
"parentPublication": {
"id": "proceedings/mdm/2019/3363/0",
"title": "2019 20th IEEE International Conference on Mobile Data Management (MDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/05/09122565",
"title": "Efficient Processing of Group Planning Queries Over Spatial-Social Networks",
"doi": null,
"abstractUrl": "/journal/tk/2022/05/09122565/1kRRvDuoYPS",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/sc/2023/01/09547836",
"title": "Towards Keyword-Based Geo-Social Group Query Services",
"doi": null,
"abstractUrl": "/journal/sc/2023/01/09547836/1x9Tqdy2x0c",
"parentPublication": {
"id": "trans/sc",
"title": "IEEE Transactions on Services Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09935292",
"articleId": "1HYqAJIGB2w",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09935307",
"articleId": "1HYqBaTlU1q",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1I05u9y2Ry0",
"name": "ttk555501-09935277s1-supp1-3218844.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttk555501-09935277s1-supp1-3218844.pdf",
"extension": "pdf",
"size": "76.6 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1CdACzpvTPi",
"title": "May",
"year": "2022",
"issueNum": "05",
"idPrefix": "tk",
"pubType": "journal",
"volume": "34",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1kRRvDuoYPS",
"doi": "10.1109/TKDE.2020.3004153",
"abstract": "Recently, location-based social networks, that involve both social and spatial information, have received much attention in many real-world applications such as location-based services (LBS), map utilities, business planning, and so on. In this paper, we seamlessly integrate both social networks and spatial road networks, resulting in a so-called <italic>spatial-social network</italic>, and study an important and novel query type, named <italic>group planning query over spatial-social networks</italic> (GP-SSN), which is very useful for applications such as trip recommendations. In particular, a GP-SSN query retrieves a group of friends with common interests on social networks and a number of spatially close <italic>points of interest</italic> (POIs) on spatial road networks that best match group’s preferences and have the smallest traveling distances to the group. In order to tackle the GP-SSN problem, we design effective pruning methods, matching score pruning, user pruning, and distance pruning, to rule out false alarms of GP-SSN query answers and reduce the problem search space. We also propose effective indexing mechanisms to facilitate the GP-SSN query processing, and develop efficient GP-SSN query answering algorithms via index traversals. Extensive experiments have been conducted to evaluate the efficiency and effectiveness of our proposed GP-SSN query processing approaches.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recently, location-based social networks, that involve both social and spatial information, have received much attention in many real-world applications such as location-based services (LBS), map utilities, business planning, and so on. In this paper, we seamlessly integrate both social networks and spatial road networks, resulting in a so-called <italic>spatial-social network</italic>, and study an important and novel query type, named <italic>group planning query over spatial-social networks</italic> (GP-SSN), which is very useful for applications such as trip recommendations. In particular, a GP-SSN query retrieves a group of friends with common interests on social networks and a number of spatially close <italic>points of interest</italic> (POIs) on spatial road networks that best match group’s preferences and have the smallest traveling distances to the group. In order to tackle the GP-SSN problem, we design effective pruning methods, matching score pruning, user pruning, and distance pruning, to rule out false alarms of GP-SSN query answers and reduce the problem search space. We also propose effective indexing mechanisms to facilitate the GP-SSN query processing, and develop efficient GP-SSN query answering algorithms via index traversals. Extensive experiments have been conducted to evaluate the efficiency and effectiveness of our proposed GP-SSN query processing approaches.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recently, location-based social networks, that involve both social and spatial information, have received much attention in many real-world applications such as location-based services (LBS), map utilities, business planning, and so on. In this paper, we seamlessly integrate both social networks and spatial road networks, resulting in a so-called spatial-social network, and study an important and novel query type, named group planning query over spatial-social networks (GP-SSN), which is very useful for applications such as trip recommendations. In particular, a GP-SSN query retrieves a group of friends with common interests on social networks and a number of spatially close points of interest (POIs) on spatial road networks that best match group’s preferences and have the smallest traveling distances to the group. In order to tackle the GP-SSN problem, we design effective pruning methods, matching score pruning, user pruning, and distance pruning, to rule out false alarms of GP-SSN query answers and reduce the problem search space. We also propose effective indexing mechanisms to facilitate the GP-SSN query processing, and develop efficient GP-SSN query answering algorithms via index traversals. Extensive experiments have been conducted to evaluate the efficiency and effectiveness of our proposed GP-SSN query processing approaches.",
"title": "Efficient Processing of Group Planning Queries Over Spatial-Social Networks",
"normalizedTitle": "Efficient Processing of Group Planning Queries Over Spatial-Social Networks",
"fno": "09122565",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Social Networking Online",
"Roads",
"Planning",
"Search Problems",
"Indexing",
"Query Processing",
"Spatial Social Network",
"Group Planning Query Over Spatial Social Networks",
"GP SSN"
],
"authors": [
{
"givenName": "Ahmed",
"surname": "Al-Baghdadi",
"fullName": "Ahmed Al-Baghdadi",
"affiliation": "Department of Computer Science, Kent State University, Kent, OH, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gokarna",
"surname": "Sharma",
"fullName": "Gokarna Sharma",
"affiliation": "Department of Computer Science, Kent State University, Kent, OH, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiang",
"surname": "Lian",
"fullName": "Xiang Lian",
"affiliation": "Department of Computer Science, Kent State University, Kent, OH, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2022-05-01 00:00:00",
"pubType": "trans",
"pages": "2135-2147",
"year": "2022",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/mdm/2016/0883/1/0883a232",
"title": "K-Closest Pairs Queries in Road Networks",
"doi": null,
"abstractUrl": "/proceedings-article/mdm/2016/0883a232/12OmNrJROUF",
"parentPublication": {
"id": "proceedings/mdm/2016/0883/1",
"title": "2016 17th IEEE International Conference on Mobile Data Management (MDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2016/2020/0/07498399",
"title": "Geo-Social K-Cover Group queries for collaborative spatial computing",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2016/07498399/12OmNxu6p82",
"parentPublication": {
"id": "proceedings/icde/2016/2020/0",
"title": "2016 IEEE 32nd International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2018/04/08125132",
"title": "Towards Why-Not Spatial Keyword Top-Z_$k$_Z Queries: A Direction-Aware Approach",
"doi": null,
"abstractUrl": "/journal/tk/2018/04/08125132/13rRUwfZC0H",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2008/06/ttk2008060809",
"title": "Probabilistic Group Nearest Neighbor Queries in Uncertain Databases",
"doi": null,
"abstractUrl": "/journal/tk/2008/06/ttk2008060809/13rRUxBa5xy",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2015/05/06940263",
"title": "Efficient Reverse Top-k Boolean Spatial Keyword Queries on Road Networks",
"doi": null,
"abstractUrl": "/journal/tk/2015/05/06940263/13rRUxC0Swj",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2017/11/08014478",
"title": "Time-Aware Boolean Spatial Keyword Queries",
"doi": null,
"abstractUrl": "/journal/tk/2017/11/08014478/13rRUynHujB",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2009/03/ttk2009030351",
"title": "Efficient Processing of Metric Skyline Queries",
"doi": null,
"abstractUrl": "/journal/tk/2009/03/ttk2009030351/13rRUyueghx",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2019/12/08493329",
"title": "On Efficient Processing of Group and Subsequent Queries for Social Activity Planning",
"doi": null,
"abstractUrl": "/journal/tk/2019/12/08493329/14qdcRKegee",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mdm/2022/5176/0/517600a041",
"title": "Advanced Conjunctive Boolean Streaming Spatial Keyword Processing",
"doi": null,
"abstractUrl": "/proceedings-article/mdm/2022/517600a041/1G89F74ycUM",
"parentPublication": {
"id": "proceedings/mdm/2022/5176/0",
"title": "2022 23rd IEEE International Conference on Mobile Data Management (MDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2019/7474/0/747400a434",
"title": "Cohesive Group Nearest Neighbor Queries Over Road-Social Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2019/747400a434/1aDT0fYz36U",
"parentPublication": {
"id": "proceedings/icde/2019/7474/0",
"title": "2019 IEEE 35th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09133279",
"articleId": "1la7EFn5FrG",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09124657",
"articleId": "1kVbASKntM4",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1CdAMLgjQje",
"name": "ttk202205-09122565s1-supp1-3004153.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttk202205-09122565s1-supp1-3004153.pdf",
"extension": "pdf",
"size": "622 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1CdAifRDMY0",
"title": "March-April",
"year": "2022",
"issueNum": "02",
"idPrefix": "tb",
"pubType": "journal",
"volume": "19",
"label": "March-April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1w7abbNXM6Q",
"doi": "10.1109/TCBB.2021.3105001",
"abstract": "<italic>Motivation:</italic> In bioinformatics, complex cellular modeling and behavior simulation to identify significant molecular interactions is considered a relevant problem. Traditional methods model such complex systems using single and binary network. However, this model is inadequate to represent biological networks as different sets of interactions can simultaneously take place for different interaction constraints (such as transcription regulation and protein interaction). Furthermore, biological systems may exhibit varying interaction topologies even for the same interaction type under different developmental stages or stress conditions. Therefore, models which consider biological systems as solitary interactions are inaccurate as they fail to capture the complex behavior of cellular interactions within organisms. Identification and counting of recurrent motifs within a network is one of the fundamental problems in biological network analysis. Existing methods for motif counting on single network topologies are inadequate to capture patterns of molecular interactions that have significant changes in biological expression when identified across different organisms that are similar, or even time-varying networks within the same organism. That is, they fail to identify recurrent interactions as they consider a single snapshot of a network among a set of multiple networks. Therefore, we need methods geared towards studying multiple network topologies and the pattern conservation among them. <italic>Contributions:</italic> In this paper, we consider the problem of counting the number of instances of a user supplied motif topology in a given multilayer network. We model interactions among a set of entities (e.g., genes)describing various conditions or temporal variation as multilayer networks. Thus a separate network as each layer shows the connectivity of the nodes under a unique network state. Existing motif counting and identification methods are limited to single network topologies, and thus cannot be directly applied on multilayer networks. We apply our model and algorithm to study frequent patterns in cellular networks that are common in varying cellular states under different stress conditions, where the cellular network topology under each stress condition describes a unique network layer. <italic>Results:</italic> We develop a methodology and corresponding algorithm based on the proposed model for motif counting in multilayer networks. We performed experiments on both real and synthetic datasets. We modeled the synthetic datasets under a wide spectrum of parameters, such as network size, density, motif frequency. Results on synthetic datasets demonstrate that our algorithm finds motif embeddings with very high accuracy compared to existing state-of-the-art methods such as G-tries, ESU (FANMODE)and mfinder. Furthermore, we observe that our method runs from several times to several orders of magnitude faster than existing methods. For experiments on real dataset, we consider Escherichia coli (<italic>E. coli</italic>)transcription regulatory network under different experimental conditions. We observe that the genes selected by our method conserves functional characteristics under various stress conditions with very low false discovery rates. Moreover, the method is scalable to real networks in terms of both network size and number of layers.",
"abstracts": [
{
"abstractType": "Regular",
"content": "<italic>Motivation:</italic> In bioinformatics, complex cellular modeling and behavior simulation to identify significant molecular interactions is considered a relevant problem. Traditional methods model such complex systems using single and binary network. However, this model is inadequate to represent biological networks as different sets of interactions can simultaneously take place for different interaction constraints (such as transcription regulation and protein interaction). Furthermore, biological systems may exhibit varying interaction topologies even for the same interaction type under different developmental stages or stress conditions. Therefore, models which consider biological systems as solitary interactions are inaccurate as they fail to capture the complex behavior of cellular interactions within organisms. Identification and counting of recurrent motifs within a network is one of the fundamental problems in biological network analysis. Existing methods for motif counting on single network topologies are inadequate to capture patterns of molecular interactions that have significant changes in biological expression when identified across different organisms that are similar, or even time-varying networks within the same organism. That is, they fail to identify recurrent interactions as they consider a single snapshot of a network among a set of multiple networks. Therefore, we need methods geared towards studying multiple network topologies and the pattern conservation among them. <italic>Contributions:</italic> In this paper, we consider the problem of counting the number of instances of a user supplied motif topology in a given multilayer network. We model interactions among a set of entities (e.g., genes)describing various conditions or temporal variation as multilayer networks. Thus a separate network as each layer shows the connectivity of the nodes under a unique network state. Existing motif counting and identification methods are limited to single network topologies, and thus cannot be directly applied on multilayer networks. We apply our model and algorithm to study frequent patterns in cellular networks that are common in varying cellular states under different stress conditions, where the cellular network topology under each stress condition describes a unique network layer. <italic>Results:</italic> We develop a methodology and corresponding algorithm based on the proposed model for motif counting in multilayer networks. We performed experiments on both real and synthetic datasets. We modeled the synthetic datasets under a wide spectrum of parameters, such as network size, density, motif frequency. Results on synthetic datasets demonstrate that our algorithm finds motif embeddings with very high accuracy compared to existing state-of-the-art methods such as G-tries, ESU (FANMODE)and mfinder. Furthermore, we observe that our method runs from several times to several orders of magnitude faster than existing methods. For experiments on real dataset, we consider Escherichia coli (<italic>E. coli</italic>)transcription regulatory network under different experimental conditions. We observe that the genes selected by our method conserves functional characteristics under various stress conditions with very low false discovery rates. Moreover, the method is scalable to real networks in terms of both network size and number of layers.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Motivation: In bioinformatics, complex cellular modeling and behavior simulation to identify significant molecular interactions is considered a relevant problem. Traditional methods model such complex systems using single and binary network. However, this model is inadequate to represent biological networks as different sets of interactions can simultaneously take place for different interaction constraints (such as transcription regulation and protein interaction). Furthermore, biological systems may exhibit varying interaction topologies even for the same interaction type under different developmental stages or stress conditions. Therefore, models which consider biological systems as solitary interactions are inaccurate as they fail to capture the complex behavior of cellular interactions within organisms. Identification and counting of recurrent motifs within a network is one of the fundamental problems in biological network analysis. Existing methods for motif counting on single network topologies are inadequate to capture patterns of molecular interactions that have significant changes in biological expression when identified across different organisms that are similar, or even time-varying networks within the same organism. That is, they fail to identify recurrent interactions as they consider a single snapshot of a network among a set of multiple networks. Therefore, we need methods geared towards studying multiple network topologies and the pattern conservation among them. Contributions: In this paper, we consider the problem of counting the number of instances of a user supplied motif topology in a given multilayer network. We model interactions among a set of entities (e.g., genes)describing various conditions or temporal variation as multilayer networks. Thus a separate network as each layer shows the connectivity of the nodes under a unique network state. Existing motif counting and identification methods are limited to single network topologies, and thus cannot be directly applied on multilayer networks. We apply our model and algorithm to study frequent patterns in cellular networks that are common in varying cellular states under different stress conditions, where the cellular network topology under each stress condition describes a unique network layer. Results: We develop a methodology and corresponding algorithm based on the proposed model for motif counting in multilayer networks. We performed experiments on both real and synthetic datasets. We modeled the synthetic datasets under a wide spectrum of parameters, such as network size, density, motif frequency. Results on synthetic datasets demonstrate that our algorithm finds motif embeddings with very high accuracy compared to existing state-of-the-art methods such as G-tries, ESU (FANMODE)and mfinder. Furthermore, we observe that our method runs from several times to several orders of magnitude faster than existing methods. For experiments on real dataset, we consider Escherichia coli (E. coli)transcription regulatory network under different experimental conditions. We observe that the genes selected by our method conserves functional characteristics under various stress conditions with very low false discovery rates. Moreover, the method is scalable to real networks in terms of both network size and number of layers.",
"title": "Pattern Discovery in Multilayer Networks",
"normalizedTitle": "Pattern Discovery in Multilayer Networks",
"fno": "09514471",
"hasPdf": true,
"idPrefix": "tb",
"keywords": [
"Bioinformatics",
"Cellular Radio",
"Telecommunication Network Topology",
"Synthetic Datasets",
"Bioinformatics",
"Pattern Discovery",
"Transcription Regulation",
"Interaction Constraints",
"Binary Network",
"Molecular Interactions",
"Behavior Simulation",
"Complex Cellular Modeling",
"Cellular Network Topology",
"Unique Network State",
"Multilayer Networks",
"Motif Topology",
"Time Varying Networks",
"Motif Counting",
"Biological Network Analysis",
"Cellular Interactions",
"Solitary Interactions",
"Stress Condition",
"Interaction Topologies",
"Biological Systems",
"Nonhomogeneous Media",
"Biology",
"Network Topology",
"Topology",
"Biological System Modeling",
"Proteins",
"Stress",
"Multilayer Networks",
"Motif Finding",
"Biological Networks"
],
"authors": [
{
"givenName": "Yuanfang",
"surname": "Ren",
"fullName": "Yuanfang Ren",
"affiliation": "Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Aisharjya",
"surname": "Sarkar",
"fullName": "Aisharjya Sarkar",
"affiliation": "Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Pierangelo",
"surname": "Veltri",
"fullName": "Pierangelo Veltri",
"affiliation": "Department of Surgical and Medical Science, University Magna Graecia of Catanzaro, Catanzaro, Italy",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ahmet",
"surname": "Ay",
"fullName": "Ahmet Ay",
"affiliation": "Departments of Biology and Mathematics, Colgate University, Hamilton, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alin",
"surname": "Dobra",
"fullName": "Alin Dobra",
"affiliation": "Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tamer",
"surname": "Kahveci",
"fullName": "Tamer Kahveci",
"affiliation": "Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2022-03-01 00:00:00",
"pubType": "trans",
"pages": "741-752",
"year": "2022",
"issn": "1545-5963",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/eisic/2015/8657/0/8657a037",
"title": "Understanding the Dynamic of Covert Organization with Multilayer Networks Model",
"doi": null,
"abstractUrl": "/proceedings-article/eisic/2015/8657a037/12OmNBBzohv",
"parentPublication": {
"id": "proceedings/eisic/2015/8657/0",
"title": "2015 European Intelligence and Security Informatics Conference (EISIC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2017/3800/0/3800a134",
"title": "Principled Multilayer Network Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2017/3800a134/12OmNro0I2O",
"parentPublication": {
"id": "proceedings/icdmw/2017/3800/0",
"title": "2017 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2017/3050/0/08217920",
"title": "ParaMODA: Improving motif-centric subgraph pattern search in PPI networks",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217920/12OmNvDqsDE",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2019/04/08329217",
"title": "A New Algorithm for Counting Independent Motifs in Probabilistic Networks",
"doi": null,
"abstractUrl": "/journal/tb/2019/04/08329217/13rRUwIF6jy",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2018/04/07936619",
"title": "Construction of Signaling Pathways with RNAi Data and Multiple Reference Networks",
"doi": null,
"abstractUrl": "/journal/tb/2018/04/07936619/13rRUwbs1Zj",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2018/9159/0/08594909",
"title": "Fast Rectangle Counting on Massive Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2018/08594909/17D45Wuc3b6",
"parentPublication": {
"id": "proceedings/icdm/2018/9159/0",
"title": "2018 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2019/01/08288571",
"title": "A Comparative Study of Network Motifs in the Integrated Transcriptional Regulation and Protein Interaction Networks of <italic>Shewanella</italic>",
"doi": null,
"abstractUrl": "/journal/tb/2019/01/08288571/17D45XvMcfb",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2023/02/09804726",
"title": "Diffusion Alignment Coefficient (DAC): A Novel Similarity Metric for Protein-Protein Interaction Network",
"doi": null,
"abstractUrl": "/journal/tb/2023/02/09804726/1Erlfm1AQbm",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2023/02/09900440",
"title": "Exploring Scalable Parallelization for Edit Distance-Based Motif Search",
"doi": null,
"abstractUrl": "/journal/tb/2023/02/09900440/1GU2oUBjccM",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/03/09317770",
"title": "DPCMNE: Detecting Protein Complexes From Protein-Protein Interaction Networks Via Multi-Level Network Embedding",
"doi": null,
"abstractUrl": "/journal/tb/2022/03/09317770/1qdSNUe4iUE",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09425591",
"articleId": "1tpwQt5yJYA",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09134909",
"articleId": "1lgLhSW7h1m",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1KxPG2bPMTm",
"title": "Jan.-Feb.",
"year": "2023",
"issueNum": "01",
"idPrefix": "sc",
"pubType": "journal",
"volume": "16",
"label": "Jan.-Feb.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1x9Tqdy2x0c",
"doi": "10.1109/TSC.2021.3115132",
"abstract": "In this article, we study a novel variant of geo-social group queries, namely, <italic><underline>k</underline>eyword-based <underline>g</underline>eo-<underline>s</underline>ocial <underline>g</underline>roup</italic> (<italic>KGSG</italic>) queries. Motivated by group-based activity planning, KGSG ensures that the attendees have a <italic>good social relationship</italic>, are <italic>close enough to the activity location</italic>, and are <italic>interested in</italic> the activity. Efficient processing of the KGSG query is very challenging as the problem is NP-hard. To address the challenge, we first propose two R-tree based algorithms, namely <italic>Distance Ordering based</italic> (Baseline) and <italic>Breadth Distance Ordering with Neighbor Expanding</italic> (BDONE). To further improve these two R-tree based algorithms, we propose a new keyword-aware social spatial index, called <italic>SIR-tree</italic>, which incorporates spatial, social, and keyword information into an R-tree. The novelty of SIR-tree lies in the idea of <italic>projecting the social relationships of an LBSN on the spatial layer which also maintains the users’ keyword information</italic>, to facilitate efficient KGSG query processing. Accordingly, we develop an efficient algorithm, called <italic>KGSG by SIR-tree Acceleration</italic> (KGSG-SIR), which exploits SIR-tree to accelerate query processing of KGSG. We conduct an extensive performance evaluation using four real datasets to validate our ideas and the proposed algorithms. The experimental result shows that the KGSG-SIR algorithm outperforms the two algorithms significantly.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this article, we study a novel variant of geo-social group queries, namely, <italic><underline>k</underline>eyword-based <underline>g</underline>eo-<underline>s</underline>ocial <underline>g</underline>roup</italic> (<italic>KGSG</italic>) queries. Motivated by group-based activity planning, KGSG ensures that the attendees have a <italic>good social relationship</italic>, are <italic>close enough to the activity location</italic>, and are <italic>interested in</italic> the activity. Efficient processing of the KGSG query is very challenging as the problem is NP-hard. To address the challenge, we first propose two R-tree based algorithms, namely <italic>Distance Ordering based</italic> (Baseline) and <italic>Breadth Distance Ordering with Neighbor Expanding</italic> (BDONE). To further improve these two R-tree based algorithms, we propose a new keyword-aware social spatial index, called <italic>SIR-tree</italic>, which incorporates spatial, social, and keyword information into an R-tree. The novelty of SIR-tree lies in the idea of <italic>projecting the social relationships of an LBSN on the spatial layer which also maintains the users’ keyword information</italic>, to facilitate efficient KGSG query processing. Accordingly, we develop an efficient algorithm, called <italic>KGSG by SIR-tree Acceleration</italic> (KGSG-SIR), which exploits SIR-tree to accelerate query processing of KGSG. We conduct an extensive performance evaluation using four real datasets to validate our ideas and the proposed algorithms. The experimental result shows that the KGSG-SIR algorithm outperforms the two algorithms significantly.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this article, we study a novel variant of geo-social group queries, namely, keyword-based geo-social group (KGSG) queries. Motivated by group-based activity planning, KGSG ensures that the attendees have a good social relationship, are close enough to the activity location, and are interested in the activity. Efficient processing of the KGSG query is very challenging as the problem is NP-hard. To address the challenge, we first propose two R-tree based algorithms, namely Distance Ordering based (Baseline) and Breadth Distance Ordering with Neighbor Expanding (BDONE). To further improve these two R-tree based algorithms, we propose a new keyword-aware social spatial index, called SIR-tree, which incorporates spatial, social, and keyword information into an R-tree. The novelty of SIR-tree lies in the idea of projecting the social relationships of an LBSN on the spatial layer which also maintains the users’ keyword information, to facilitate efficient KGSG query processing. Accordingly, we develop an efficient algorithm, called KGSG by SIR-tree Acceleration (KGSG-SIR), which exploits SIR-tree to accelerate query processing of KGSG. We conduct an extensive performance evaluation using four real datasets to validate our ideas and the proposed algorithms. The experimental result shows that the KGSG-SIR algorithm outperforms the two algorithms significantly.",
"title": "Towards Keyword-Based Geo-Social Group Query Services",
"normalizedTitle": "Towards Keyword-Based Geo-Social Group Query Services",
"fno": "09547836",
"hasPdf": true,
"idPrefix": "sc",
"keywords": [
"Location Based Services",
"Query Processing",
"Social Networking Online",
"Trees Mathematics",
"Activity Location",
"Agood Social Relationship",
"Called SIR Tree",
"Efficient KGSG Query Processing",
"Group Based Activity Planning",
"Inthe Activity",
"Keyword Aware Social Spatial Index",
"KGSG SIR Algorithm",
"R Tree Based Algorithms",
"SIR Tree Acceleration",
"Social Relationships",
"Social Keyword Information",
"Spatial Keyword Information",
"Towards Keyword Based Geo Social Group Query Services",
"Users",
"Query Processing",
"Indexes",
"Social Networking Online",
"Peer To Peer Computing",
"Planning",
"Spatial Databases",
"TV",
"Location Based Services",
"Geo Social Group Query",
"Nearest Neighbor",
"Keywords Matching"
],
"authors": [
{
"givenName": "Huaijie",
"surname": "Zhu",
"fullName": "Huaijie Zhu",
"affiliation": "Sun Yat-Sen University, Guangzhou, Guangdong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wei",
"surname": "Liu",
"fullName": "Wei Liu",
"affiliation": "Sun Yat-Sen University, Guangzhou, Guangdong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jian",
"surname": "Yin",
"fullName": "Jian Yin",
"affiliation": "Sun Yat-Sen University, Guangzhou, Guangdong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jianliang",
"surname": "Xu",
"fullName": "Jianliang Xu",
"affiliation": "Hong Kong Baptist University, Kowloon, Tong, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wang-Chien",
"surname": "Lee",
"fullName": "Wang-Chien Lee",
"affiliation": "Computer Science and Engineering, Penn State University, State College, PA, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2023-01-01 00:00:00",
"pubType": "trans",
"pages": "670-683",
"year": "2023",
"issn": "1939-1374",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cgc/2012/3027/0/06382840",
"title": "Efficient Structural Query Evaluation over Social Data",
"doi": null,
"abstractUrl": "/proceedings-article/cgc/2012/06382840/12OmNwcl7C9",
"parentPublication": {
"id": "proceedings/cgc/2012/3027/0",
"title": "2012 International Conference on Cloud and Green Computing (CGC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2017/6543/0/6543a387",
"title": "Reverse Top-k Geo-Social Keyword Queries in Road Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2017/6543a387/12OmNxTVTZ8",
"parentPublication": {
"id": "proceedings/icde/2017/6543/0",
"title": "2017 IEEE 33rd International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2018/5520/0/552000a965",
"title": "Why-Not Questions on Top-k Geo-Social Keyword Queries in Road Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2018/552000a965/14Fq0V7LOyD",
"parentPublication": {
"id": "proceedings/icde/2018/5520/0",
"title": "2018 IEEE 34th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300a312",
"title": "Continuous Geo-Social Group Monitoring over Moving Users",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300a312/1FwFboYjmOA",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09894074",
"title": "Willingness Maximization for Ego Network Data Extraction in Multiple Online Social Networks",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09894074/1GIq734SFLa",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09935277",
"title": "Continuous Geo-Social Group Monitoring in Dynamic LBSNs",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09935277/1HYqASRP8Vq",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mdm/2019/3363/0/336300a391",
"title": "Towards Usability on Reverse Top-k Geo-Social Keyword Query Results",
"doi": null,
"abstractUrl": "/proceedings-article/mdm/2019/336300a391/1ckrNUXqReE",
"parentPublication": {
"id": "proceedings/mdm/2019/3363/0",
"title": "2019 20th IEEE International Conference on Mobile Data Management (MDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/05/09122565",
"title": "Efficient Processing of Group Planning Queries Over Spatial-Social Networks",
"doi": null,
"abstractUrl": "/journal/tk/2022/05/09122565/1kRRvDuoYPS",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icws/2021/1681/0/168100a198",
"title": "NETR-Tree: An Efficient Framework for Social-Based Time-Aware Spatial Keyword Query",
"doi": null,
"abstractUrl": "/proceedings-article/icws/2021/168100a198/1yrHHe3H6ve",
"parentPublication": {
"id": "proceedings/icws/2021/1681/0",
"title": "2021 IEEE International Conference on Web Services (ICWS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2023/06/09647960",
"title": "Privacy-Preserving Ranked Spatial Keyword Query in Mobile Cloud-Assisted Fog Computing",
"doi": null,
"abstractUrl": "/journal/tm/2023/06/09647960/1ziK4XH9xPq",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09534675",
"articleId": "1wLbhutLwha",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09616429",
"articleId": "1yA7421aIOQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNC36tSf",
"title": "Aug.",
"year": "2013",
"issueNum": "08",
"idPrefix": "tg",
"pubType": "journal",
"volume": "19",
"label": "Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxD9h59",
"doi": "10.1109/TVCG.2012.325",
"abstract": "This paper presents the first method for full-body trajectory optimization of physics-based human motion that does not rely on motion capture, specified key-poses, or periodic motion. Optimization is performed using a small set of simple goals, for example, one hand should be on the ground, or the center-of-mass should be above a particular height. These objectives are applied to short spacetime windows which can be composed to express goals over an entire animation. Specific contact locations needed to achieve objectives are not required by our method. We show that the method can synthesize many different kinds of movement, including walking, hand walking, breakdancing, flips, and crawling. Most of these movements have never been previously synthesized by physics-based methods.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents the first method for full-body trajectory optimization of physics-based human motion that does not rely on motion capture, specified key-poses, or periodic motion. Optimization is performed using a small set of simple goals, for example, one hand should be on the ground, or the center-of-mass should be above a particular height. These objectives are applied to short spacetime windows which can be composed to express goals over an entire animation. Specific contact locations needed to achieve objectives are not required by our method. We show that the method can synthesize many different kinds of movement, including walking, hand walking, breakdancing, flips, and crawling. Most of these movements have never been previously synthesized by physics-based methods.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents the first method for full-body trajectory optimization of physics-based human motion that does not rely on motion capture, specified key-poses, or periodic motion. Optimization is performed using a small set of simple goals, for example, one hand should be on the ground, or the center-of-mass should be above a particular height. These objectives are applied to short spacetime windows which can be composed to express goals over an entire animation. Specific contact locations needed to achieve objectives are not required by our method. We show that the method can synthesize many different kinds of movement, including walking, hand walking, breakdancing, flips, and crawling. Most of these movements have never been previously synthesized by physics-based methods.",
"title": "Trajectory Optimization for Full-Body Movements with Complex Contacts",
"normalizedTitle": "Trajectory Optimization for Full-Body Movements with Complex Contacts",
"fno": "ttg2013081405",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Optimization",
"Trajectory",
"Legged Locomotion",
"Joints",
"Linear Programming",
"Animation",
"Humans",
"Motion Control",
"Physics Based Animation",
"Character Animation"
],
"authors": [
{
"givenName": "M.",
"surname": "Al Borno",
"fullName": "M. Al Borno",
"affiliation": "Dept. of Comput. Sci., Univ. of Toronto, Toronto, ON, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "M.",
"surname": "de Lasa",
"fullName": "M. de Lasa",
"affiliation": "Autodesk Canada, Toronto, ON, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "A.",
"surname": "Hertzmann",
"fullName": "A. Hertzmann",
"affiliation": "Dept. of Comput. Sci., Univ. of Toronto, Toronto, ON, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "08",
"pubDate": "2013-08-01 00:00:00",
"pubType": "trans",
"pages": "1405-1414",
"year": "2013",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icndc/2010/8382/0/05645365",
"title": "Force/Torque-based Compliance Control for Humanoid Robot to Compensate the Landing Impact Force",
"doi": null,
"abstractUrl": "/proceedings-article/icndc/2010/05645365/12OmNAoDibc",
"parentPublication": {
"id": "proceedings/icndc/2010/8382/0",
"title": "2010 First International Conference on Networking and Distributed Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2014/6572/0/6572a627",
"title": "Full Body Person Identification Using the Kinect Sensor",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2014/6572a627/12OmNrNh0Q2",
"parentPublication": {
"id": "proceedings/ictai/2014/6572/0",
"title": "2014 IEEE 26th International Conference on Tools with Artificial Intelligence (ICTAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/simultech/2014/060/0/07094997",
"title": "An effective implementation of agent's complex actions by reusing primitive motions",
"doi": null,
"abstractUrl": "/proceedings-article/simultech/2014/07094997/12OmNxdm4rR",
"parentPublication": {
"id": "proceedings/simultech/2014/060/0",
"title": "2014 International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icccnt/2014/2696/0/06963001",
"title": "Foot plant detection for motion capture data by curve saliency",
"doi": null,
"abstractUrl": "/proceedings-article/icccnt/2014/06963001/12OmNyugyTj",
"parentPublication": {
"id": "proceedings/icccnt/2014/2696/0",
"title": "2014 5th International Conference on Computing, Communication and Networking Technologies (ICCCNT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/case/2012/0430/0/06386470",
"title": "Walking pattern generation based on energy function and inverse pendulum model for biped robot",
"doi": null,
"abstractUrl": "/proceedings-article/case/2012/06386470/12OmNzcxZ9h",
"parentPublication": {
"id": "proceedings/case/2012/0430/0",
"title": "2012 IEEE International Conference on Automation Science and Engineering (CASE 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icisce/2016/2535/0/2535a799",
"title": "A Stable Walking Strategy of Quadruped Robot Based on Foot Trajectory Planning",
"doi": null,
"abstractUrl": "/proceedings-article/icisce/2016/2535a799/12OmNzgwmMR",
"parentPublication": {
"id": "proceedings/icisce/2016/2535/0",
"title": "2016 3rd International Conference on Information Science and Control Engineering (ICISCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icndc/2010/8382/0/05645366",
"title": "Optimal Momentum Compensation with Waist Joint for Online Biped Gait Generating of Humanoid Robot",
"doi": null,
"abstractUrl": "/proceedings-article/icndc/2010/05645366/12OmNzlUKzP",
"parentPublication": {
"id": "proceedings/icndc/2010/8382/0",
"title": "2010 First International Conference on Networking and Distributed Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2017/06/mcg2017060028",
"title": "Full-Body Animation of Human Locomotion in Reduced Gravity Using Physics-Based Control",
"doi": null,
"abstractUrl": "/magazine/cg/2017/06/mcg2017060028/13rRUwwslv6",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wcmeim/2021/2172/0/217200a087",
"title": "Foot Trajectory Planning and Prototype Experiment of Double Closed-Chain Walking Leg",
"doi": null,
"abstractUrl": "/proceedings-article/wcmeim/2021/217200a087/1ANLtlYmHtu",
"parentPublication": {
"id": "proceedings/wcmeim/2021/2172/0",
"title": "2021 4th World Conference on Mechanical Engineering and Intelligent Manufacturing (WCMEIM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2022/6814/0/681400a118",
"title": "Crowd Simulation with Feedback Based on Locomotion State",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2022/681400a118/1I6RQ8VlGNi",
"parentPublication": {
"id": "proceedings/cw/2022/6814/0",
"title": "2022 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttg2013081386",
"articleId": "13rRUwI5U7X",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttg2013081415",
"articleId": "13rRUxASu0K",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "17ShDTXWRGi",
"name": "ttg2013081405s2.mov",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg2013081405s2.mov",
"extension": "mov",
"size": "46.4 MB",
"__typename": "WebExtraType"
},
{
"id": "17ShDTXWRGh",
"name": "ttg2013081405s1.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg2013081405s1.pdf",
"extension": "pdf",
"size": "206 kB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1HMOit1lSk8",
"title": "Dec.",
"year": "2022",
"issueNum": "12",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "Dec.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1vzYfxgOoeI",
"doi": "10.1109/TVCG.2021.3100095",
"abstract": "We propose a novel method for exploring the dynamics of physically based animated characters, and learning a task-agnostic action space that makes movement optimization easier. Like several previous article, we parameterize actions as target states, and learn a short-horizon goal-conditioned low-level control policy that drives the agent's state towards the targets. Our novel contribution is that with our exploration data, we are able to learn the low-level policy in a generic manner and without any reference movement data. Trained once for each agent or simulation environment, the policy improves the efficiency of optimizing both trajectories and high-level policies across multiple tasks and optimization algorithms. We also contribute novel visualizations that show how using target states as actions makes optimized trajectories more robust to disturbances; this manifests as wider optima that are easy to find. Due to its simplicity and generality, our proposed approach should provide a building block that can improve a large variety of movement optimization methods and applications.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose a novel method for exploring the dynamics of physically based animated characters, and learning a task-agnostic action space that makes movement optimization easier. Like several previous article, we parameterize actions as target states, and learn a short-horizon goal-conditioned low-level control policy that drives the agent's state towards the targets. Our novel contribution is that with our exploration data, we are able to learn the low-level policy in a generic manner and without any reference movement data. Trained once for each agent or simulation environment, the policy improves the efficiency of optimizing both trajectories and high-level policies across multiple tasks and optimization algorithms. We also contribute novel visualizations that show how using target states as actions makes optimized trajectories more robust to disturbances; this manifests as wider optima that are easy to find. Due to its simplicity and generality, our proposed approach should provide a building block that can improve a large variety of movement optimization methods and applications.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose a novel method for exploring the dynamics of physically based animated characters, and learning a task-agnostic action space that makes movement optimization easier. Like several previous article, we parameterize actions as target states, and learn a short-horizon goal-conditioned low-level control policy that drives the agent's state towards the targets. Our novel contribution is that with our exploration data, we are able to learn the low-level policy in a generic manner and without any reference movement data. Trained once for each agent or simulation environment, the policy improves the efficiency of optimizing both trajectories and high-level policies across multiple tasks and optimization algorithms. We also contribute novel visualizations that show how using target states as actions makes optimized trajectories more robust to disturbances; this manifests as wider optima that are easy to find. Due to its simplicity and generality, our proposed approach should provide a building block that can improve a large variety of movement optimization methods and applications.",
"title": "Learning Task-Agnostic Action Spaces for Movement Optimization",
"normalizedTitle": "Learning Task-Agnostic Action Spaces for Movement Optimization",
"fno": "09497687",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computer Animation",
"Learning Artificial Intelligence",
"Optimisation",
"Exploration Data",
"High Level Policies",
"Low Level Policy",
"Movement Optimization Methods",
"Optimization Algorithms",
"Optimized Trajectories",
"Physically Based Animated Characters",
"Reference Movement Data",
"Short Horizon Goal Conditioned Low Level Control Policy",
"Target States",
"Task Agnostic Action Space",
"Optimization",
"Task Analysis",
"Trajectory Optimization",
"Reinforcement Learning",
"Training Data",
"Splines Mathematics",
"Movement Optimization",
"Trajectory Optimization",
"Policy Optimization",
"Hierarchical Reinforcement Learning",
"Action Space"
],
"authors": [
{
"givenName": "Amin",
"surname": "Babadi",
"fullName": "Amin Babadi",
"affiliation": "Department of Computer Science, Aalto University, Espoo, Finland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Michiel",
"surname": "van de Panne",
"fullName": "Michiel van de Panne",
"affiliation": "Department of Computer Science, University of British Columbia, Vancouver, BC, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "C. Karen",
"surname": "Liu",
"fullName": "C. Karen Liu",
"affiliation": "Department of Computer Science, Stanford University, Stanford, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Perttu",
"surname": "Hämäläinen",
"fullName": "Perttu Hämäläinen",
"affiliation": "Department of Computer Science, Aalto University, Espoo, Finland",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "12",
"pubDate": "2022-12-01 00:00:00",
"pubType": "trans",
"pages": "4700-4712",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ecbs/2012/4664/0/4664a150",
"title": "Route Separation Strategies for Human Movement Datasets",
"doi": null,
"abstractUrl": "/proceedings-article/ecbs/2012/4664a150/12OmNqGRGqv",
"parentPublication": {
"id": "proceedings/ecbs/2012/4664/0",
"title": "Engineering of Computer-Based Systems, IEEE International Conference on the",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aihas/1990/2043/0/00093932",
"title": "Robot task and movement planning",
"doi": null,
"abstractUrl": "/proceedings-article/aihas/1990/00093932/12OmNvjyy3G",
"parentPublication": {
"id": "proceedings/aihas/1990/2043/0",
"title": "1990 Simulation and Planning in High Autonomy Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2017/0733/0/0733a492",
"title": "Hand Movement Prediction Based Collision-Free Human-Robot Interaction",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2017/0733a492/12OmNxw5Bxq",
"parentPublication": {
"id": "proceedings/cvprw/2017/0733/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/etvis/2016/4731/0/07851161",
"title": "Multi-similarity matrices of eye movement data",
"doi": null,
"abstractUrl": "/proceedings-article/etvis/2016/07851161/12OmNz2C1oZ",
"parentPublication": {
"id": "proceedings/etvis/2016/4731/0",
"title": "2016 IEEE Second Workshop on Eye Tracking and Visualization (ETVIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acit/2018/0385/0/08672668",
"title": "Bidirectional Search Algorithm for Airport Ground Movement",
"doi": null,
"abstractUrl": "/proceedings-article/acit/2018/08672668/18Ipm7BUMHC",
"parentPublication": {
"id": "proceedings/acit/2018/0385/0",
"title": "2018 International Arab Conference on Information Technology (ACIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2022/9744/0/974400a818",
"title": "Imitation Learning-Based Drone Motion Planning in Dense Obstacle Scenarios",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2022/974400a818/1MrFUfPjOJq",
"parentPublication": {
"id": "proceedings/ictai/2022/9744/0",
"title": "2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800l1145",
"title": "Efficient Derivative Computation for Cumulative B-Splines on Lie Groups",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800l1145/1m3ojTPmeyI",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/03/09172089",
"title": "Visualizing Movement Control Optimization Landscapes",
"doi": null,
"abstractUrl": "/journal/tg/2022/03/09172089/1mrN57MhqSI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2020/7303/0/730300b115",
"title": "Towards Fast Data-Driven Smooth Path Planning with Fair Curves",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2020/730300b115/1nkDkrXGwco",
"parentPublication": {
"id": "proceedings/compsac/2020/7303/0",
"title": "2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2020/8316/0/831600b064",
"title": "Soft Policy Optimization using Dual-Track Advantage Estimator",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2020/831600b064/1r54xIzg2iI",
"parentPublication": {
"id": "proceedings/icdm/2020/8316/0",
"title": "2020 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09495135",
"articleId": "1vyjtJyV16g",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09503317",
"articleId": "1vJVD4PhhdK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1HMOG7qxPgs",
"name": "ttg202212-09497687s1-supp2-3100095.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202212-09497687s1-supp2-3100095.mp4",
"extension": "mp4",
"size": "70 MB",
"__typename": "WebExtraType"
},
{
"id": "1HMOGBqlDva",
"name": "ttg202212-09497687s1-supp1-3100095.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202212-09497687s1-supp1-3100095.pdf",
"extension": "pdf",
"size": "5.26 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvqEvRe",
"title": "July-Aug.",
"year": "2015",
"issueNum": "04",
"idPrefix": "cg",
"pubType": "magazine",
"volume": "35",
"label": "July-Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxYINaN",
"doi": "10.1109/MCG.2015.69",
"abstract": "Domestic energy conservation is critical to reducing energy demand and greenhouse gas emissions. Personal visualization has a role to play in the design of appropriate feedback for encouraging more effective home energy use, but the unique nature of residential energy informatics introduces new design issues. This article reviews current approaches and discusses unaddressed challenges related to better conceptual models, context, enhanced communicative scope, and functional aesthetics. Based on a proposed theoretical framework, the author identifies important gaps in the current design space of residential energy visualizations related to richer data models, a broader concept of context, an enhanced communicative scope, and a better ecological fit in the home.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Domestic energy conservation is critical to reducing energy demand and greenhouse gas emissions. Personal visualization has a role to play in the design of appropriate feedback for encouraging more effective home energy use, but the unique nature of residential energy informatics introduces new design issues. This article reviews current approaches and discusses unaddressed challenges related to better conceptual models, context, enhanced communicative scope, and functional aesthetics. Based on a proposed theoretical framework, the author identifies important gaps in the current design space of residential energy visualizations related to richer data models, a broader concept of context, an enhanced communicative scope, and a better ecological fit in the home.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Domestic energy conservation is critical to reducing energy demand and greenhouse gas emissions. Personal visualization has a role to play in the design of appropriate feedback for encouraging more effective home energy use, but the unique nature of residential energy informatics introduces new design issues. This article reviews current approaches and discusses unaddressed challenges related to better conceptual models, context, enhanced communicative scope, and functional aesthetics. Based on a proposed theoretical framework, the author identifies important gaps in the current design space of residential energy visualizations related to richer data models, a broader concept of context, an enhanced communicative scope, and a better ecological fit in the home.",
"title": "Design Challenges and Opportunities for Eco-Feedback in the Home",
"normalizedTitle": "Design Challenges and Opportunities for Eco-Feedback in the Home",
"fno": "mcg2015040052",
"hasPdf": true,
"idPrefix": "cg",
"keywords": [
"Air Pollution",
"Building Management Systems",
"Data Visualisation",
"Electrical Engineering Computing",
"Energy Conservation",
"Data Models",
"Residential Energy Visualizations",
"Functional Aesthetics",
"Residential Energy Informatics",
"Home Energy",
"Personal Visualization",
"Energy Demand Reduction",
"Greenhouse Gas Emissions",
"Domestic Energy Conservation",
"Eco Feedback",
"Data Visualization",
"Biomedical Monitoring",
"Visual Analytics",
"Mobile Communication",
"Context Modeling",
"Analytical Models",
"Psychology",
"Energy Conservation",
"Computer Graphics",
"Personal Visualization",
"Energy Conservation",
"Energy Visualizations",
"In Home Displays",
"Ambient Visualizations",
"Functional Aesthetics"
],
"authors": [
{
"givenName": "Lyn",
"surname": "Bartram",
"fullName": "Lyn Bartram",
"affiliation": "Simon Fraser University",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2015-07-01 00:00:00",
"pubType": "mags",
"pages": "52-62",
"year": "2015",
"issn": "0272-1716",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/dexa/2016/3635/0/3635a153",
"title": "Application of a Home Energy Management System for Incentive-Based Demand Response Program Implementation",
"doi": null,
"abstractUrl": "/proceedings-article/dexa/2016/3635a153/12OmNBOCWl7",
"parentPublication": {
"id": "proceedings/dexa/2016/3635/0",
"title": "2016 27th International Workshop on Database and Expert Systems Applications (DEXA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isgt/2012/2158/0/06175561",
"title": "Challenges and opportunities to bring prices to devices",
"doi": null,
"abstractUrl": "/proceedings-article/isgt/2012/06175561/12OmNBTJIGy",
"parentPublication": {
"id": "proceedings/isgt/2012/2158/0",
"title": "Innovative Smart Grid Technologies, IEEE PES",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cerma/2010/4204/0/4204a568",
"title": "Definition of a Home Automation System for Energy Management and Efficiency",
"doi": null,
"abstractUrl": "/proceedings-article/cerma/2010/4204a568/12OmNyen1t7",
"parentPublication": {
"id": "proceedings/cerma/2010/4204/0",
"title": "Electronics, Robotics and Automotive Mechanics Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icstm/2015/9854/0/07225477",
"title": "Wireless Home Energy Consumption Control based on prioritised load switching",
"doi": null,
"abstractUrl": "/proceedings-article/icstm/2015/07225477/12OmNz2C1nH",
"parentPublication": {
"id": "proceedings/icstm/2015/9854/0",
"title": "2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccve/2012/4900/0/4900a316",
"title": "Optimization of Home Energy Usage by Intelligently Charging/Discharging EV/PHEV",
"doi": null,
"abstractUrl": "/proceedings-article/iccve/2012/4900a316/12OmNzXFoE9",
"parentPublication": {
"id": "proceedings/iccve/2012/4900/0",
"title": "International Conference on Connected Vehicles and Expo (ICCVE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hcs/2006/8867/0/07477741",
"title": "Wireless in the home - opportunities and challenges",
"doi": null,
"abstractUrl": "/proceedings-article/hcs/2006/07477741/12OmNzt0Izu",
"parentPublication": {
"id": "proceedings/hcs/2006/8867/0",
"title": "2006 IEEE Hot Chips 18 Symposium (HCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/uic-atc-scalcom-cbdcom-iop-smartworld/2016/2771/0/07816954",
"title": "From Building Control to Eco-Feedback: Opportunities and Challenges",
"doi": null,
"abstractUrl": "/proceedings-article/uic-atc-scalcom-cbdcom-iop-smartworld/2016/07816954/12OmNzzP5QG",
"parentPublication": {
"id": "proceedings/uic-atc-scalcom-cbdcom-iop-smartworld/2016/2771/0",
"title": "2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/igcc/2014/6177/0/07039174",
"title": "Towards eco-friendly home networking",
"doi": null,
"abstractUrl": "/proceedings-article/igcc/2014/07039174/12OmNzzfTjW",
"parentPublication": {
"id": "proceedings/igcc/2014/6177/0",
"title": "2014 International Green Computing Conference (IGCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsgea/2018/6953/0/695301a144",
"title": "The Smart Home System Based on ARM Platform",
"doi": null,
"abstractUrl": "/proceedings-article/icsgea/2018/695301a144/17D45Xq6dCx",
"parentPublication": {
"id": "proceedings/icsgea/2018/6953/0",
"title": "2018 International Conference on Smart Grid and Electrical Automation (ICSGEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcce/2019/4689/0/468900a979",
"title": "Genetic Algorithm Based Optimal Strategy for Smart Home Energy Management System with Solar Power and Electric Vehicle",
"doi": null,
"abstractUrl": "/proceedings-article/icmcce/2019/468900a979/1h0Fbighs8E",
"parentPublication": {
"id": "proceedings/icmcce/2019/4689/0",
"title": "2019 4th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "mcg2015040038",
"articleId": "13rRUzp02qz",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "mcg2015040063",
"articleId": "13rRUxAATa8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvjQ8W5",
"title": "Nov.",
"year": "2012",
"issueNum": "11",
"idPrefix": "tk",
"pubType": "journal",
"volume": "24",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUy0qnGG",
"doi": "10.1109/TKDE.2011.146",
"abstract": "Given a collection of Boolean spatiotemporal (ST) event-types, the cascading spatiotemporal pattern (CSTP) discovery process finds partially ordered subsets of these event-types whose instances are located together and occur serially. For example, analysis of crime data sets may reveal frequent occurrence of misdemeanors and drunk driving after and near bar closings on weekends, as well as after and near large gatherings such as football games. Discovering CSTPs from ST data sets is important for application domains such as public safety (e.g., identifying crime attractors and generators) and natural disaster planning, (e.g., preparing for hurricanes). However, CSTP discovery presents multiple challenges; three important ones are 1) the exponential cardinality of candidate patterns with respect to the number of event types, 2) computationally complex ST neighborhood enumeration required to evaluate the interest measure and 3) the difficulty of balancing computational complexity and statistical interpretation. Current approaches for ST data mining focus on mining totally ordered sequences or unordered subsets. In contrast, our recent work explores partially ordered patterns. Recently, we represented CSTPs as directed acyclic graphs (DAGs); proposed a new interest measure, the cascade participation index (CPI); outlined the general structure of a cascading spatiotemporal pattern miner (CSTPM); evaluated filtering strategies to enhance computational savings using a real-world crime data set and proposed a nested loop-based CSTPM to address the challenge posed by exponential cardinality of candidate patterns. This paper adds to our recent work by offering a new computational insight, namely, that the computational bottleneck for CSTP discovery lies in the interest measure evaluation. With this insight, we propose a new CSTPM based on spatiotemporal partitioning that significantly lowers the cost of interest measure evaluation. Analytical evaluation shows that our new CSTPM is correct and complete. Results from significant amount of new experimental evaluation with both synthetic and real data show that our new ST partitioning-based CSTPM outperforms the CSTPM from our previous work. We also present a case study that verifies the applicability of CSTP discovery process.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Given a collection of Boolean spatiotemporal (ST) event-types, the cascading spatiotemporal pattern (CSTP) discovery process finds partially ordered subsets of these event-types whose instances are located together and occur serially. For example, analysis of crime data sets may reveal frequent occurrence of misdemeanors and drunk driving after and near bar closings on weekends, as well as after and near large gatherings such as football games. Discovering CSTPs from ST data sets is important for application domains such as public safety (e.g., identifying crime attractors and generators) and natural disaster planning, (e.g., preparing for hurricanes). However, CSTP discovery presents multiple challenges; three important ones are 1) the exponential cardinality of candidate patterns with respect to the number of event types, 2) computationally complex ST neighborhood enumeration required to evaluate the interest measure and 3) the difficulty of balancing computational complexity and statistical interpretation. Current approaches for ST data mining focus on mining totally ordered sequences or unordered subsets. In contrast, our recent work explores partially ordered patterns. Recently, we represented CSTPs as directed acyclic graphs (DAGs); proposed a new interest measure, the cascade participation index (CPI); outlined the general structure of a cascading spatiotemporal pattern miner (CSTPM); evaluated filtering strategies to enhance computational savings using a real-world crime data set and proposed a nested loop-based CSTPM to address the challenge posed by exponential cardinality of candidate patterns. This paper adds to our recent work by offering a new computational insight, namely, that the computational bottleneck for CSTP discovery lies in the interest measure evaluation. With this insight, we propose a new CSTPM based on spatiotemporal partitioning that significantly lowers the cost of interest measure evaluation. Analytical evaluation shows that our new CSTPM is correct and complete. Results from significant amount of new experimental evaluation with both synthetic and real data show that our new ST partitioning-based CSTPM outperforms the CSTPM from our previous work. We also present a case study that verifies the applicability of CSTP discovery process.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Given a collection of Boolean spatiotemporal (ST) event-types, the cascading spatiotemporal pattern (CSTP) discovery process finds partially ordered subsets of these event-types whose instances are located together and occur serially. For example, analysis of crime data sets may reveal frequent occurrence of misdemeanors and drunk driving after and near bar closings on weekends, as well as after and near large gatherings such as football games. Discovering CSTPs from ST data sets is important for application domains such as public safety (e.g., identifying crime attractors and generators) and natural disaster planning, (e.g., preparing for hurricanes). However, CSTP discovery presents multiple challenges; three important ones are 1) the exponential cardinality of candidate patterns with respect to the number of event types, 2) computationally complex ST neighborhood enumeration required to evaluate the interest measure and 3) the difficulty of balancing computational complexity and statistical interpretation. Current approaches for ST data mining focus on mining totally ordered sequences or unordered subsets. In contrast, our recent work explores partially ordered patterns. Recently, we represented CSTPs as directed acyclic graphs (DAGs); proposed a new interest measure, the cascade participation index (CPI); outlined the general structure of a cascading spatiotemporal pattern miner (CSTPM); evaluated filtering strategies to enhance computational savings using a real-world crime data set and proposed a nested loop-based CSTPM to address the challenge posed by exponential cardinality of candidate patterns. This paper adds to our recent work by offering a new computational insight, namely, that the computational bottleneck for CSTP discovery lies in the interest measure evaluation. With this insight, we propose a new CSTPM based on spatiotemporal partitioning that significantly lowers the cost of interest measure evaluation. Analytical evaluation shows that our new CSTPM is correct and complete. Results from significant amount of new experimental evaluation with both synthetic and real data show that our new ST partitioning-based CSTPM outperforms the CSTPM from our previous work. We also present a case study that verifies the applicability of CSTP discovery process.",
"title": "Cascading Spatio-Temporal Pattern Discovery",
"normalizedTitle": "Cascading Spatio-Temporal Pattern Discovery",
"fno": "ttk2012111977",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Correlation",
"Data Mining",
"Time Measurement",
"Hurricanes",
"Indexes",
"Data Models",
"Meteorology",
"Spatiotemporal Partial Order",
"Cascading Spatiotemporal Patterns",
"Space Time K Function",
"Cascade Participation Index",
"Spatiotemporal Join",
"Spatio Temporal Continuity",
"Positive ST Autocorrelation"
],
"authors": [
{
"givenName": "Pradeep",
"surname": "Mohan",
"fullName": "Pradeep Mohan",
"affiliation": "University of Minnesota, Twin-Cities, Minneapolis",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shashi",
"surname": "Shekhar",
"fullName": "Shashi Shekhar",
"affiliation": "University of Minnesota, Twin-Cities, Minneapolis",
"__typename": "ArticleAuthorType"
},
{
"givenName": "James A.",
"surname": "Shine",
"fullName": "James A. Shine",
"affiliation": "US Army Corps of Engineers, Alexandria",
"__typename": "ArticleAuthorType"
},
{
"givenName": "James P.",
"surname": "Rogers",
"fullName": "James P. Rogers",
"affiliation": "US Army Corps of Engineers, Alexandria",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2012-11-01 00:00:00",
"pubType": "trans",
"pages": "1977-1992",
"year": "2012",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/avss/2012/4797/0/4797a458",
"title": "Crowd Event Perception Based on Spatio-temporal Viscous Fluid Field",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2012/4797a458/12OmNBU1jIf",
"parentPublication": {
"id": "proceedings/avss/2012/4797/0",
"title": "2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icws/2015/7272/0/7272a747",
"title": "STaaS: Spatio Temporal Historian as a Service",
"doi": null,
"abstractUrl": "/proceedings-article/icws/2015/7272a747/12OmNvo67zf",
"parentPublication": {
"id": "proceedings/icws/2015/7272/0",
"title": "2015 IEEE International Conference on Web Services (ICWS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2015/8493/0/8493b560",
"title": "Contrast Pattern Based Methods for Visualizing and Predicting Spatiotemporal Events",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2015/8493b560/12OmNweTvQU",
"parentPublication": {
"id": "proceedings/icdmw/2015/8493/0",
"title": "2015 IEEE International Conference on Data Mining Workshop (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2011/0394/0/05995416",
"title": "Optimal spatio-temporal path discovery for video event detection",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2011/05995416/12OmNyXMQ8n",
"parentPublication": {
"id": "proceedings/cvpr/2011/0394/0",
"title": "CVPR 2011",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2016/04/07352322",
"title": "Hierarchical Spatio-Temporal Pattern Discovery and Predictive Modeling",
"doi": null,
"abstractUrl": "/journal/tk/2016/04/07352322/13rRUwdrdSU",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2007/04/k0453",
"title": "Discovery of Periodic Patterns in Spatiotemporal Sequences",
"doi": null,
"abstractUrl": "/journal/tk/2007/04/k0453/13rRUxjyX4j",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/2021/02/08481451",
"title": "Deep Learning for Spatio-Temporal Modeling of Dynamic Spontaneous Emotions",
"doi": null,
"abstractUrl": "/journal/ta/2021/02/08481451/146z4GGFXDh",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbd/2018/8034/0/803400a177",
"title": "Spatio-Temporal Pattern Analysis and Prediction for Urban Crime",
"doi": null,
"abstractUrl": "/proceedings-article/cbd/2018/803400a177/17D45XERmlu",
"parentPublication": {
"id": "proceedings/cbd/2018/8034/0",
"title": "2018 Sixth International Conference on Advanced Cloud and Big Data (CBD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09793708",
"title": "Classification-Labeled Continuousization and Multi-Domain Spatio-Temporal Fusion for Fine-Grained Urban Crime Prediction",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09793708/1E5LzI2tveE",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093291",
"title": "Spatio-Temporal Ranked-Attention Networks for Video Captioning",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093291/1jPbtj4tmc8",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttk2012111963",
"articleId": "13rRUyY294Y",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttk2012111993",
"articleId": "13rRUxNmPEe",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNAle6QD",
"title": "February",
"year": "2012",
"issueNum": "02",
"idPrefix": "tg",
"pubType": "journal",
"volume": "18",
"label": "February",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUILtJzx",
"doi": "10.1109/TVCG.2011.50",
"abstract": "Mixed reality visualizations are increasingly studied for use in image guided surgery (IGS) systems, yet few mixed reality systems have been introduced for daily use into the operating room (OR). This may be the result of several factors: the systems are developed from a technical perspective, are rarely evaluated in the field, and/or lack consideration of the end user and the constraints of the OR. We introduce the Data, Visualization processing, View (DVV) taxonomy which defines each of the major components required to implement a mixed reality IGS system. We propose that these components be considered and used as validation criteria for introducing a mixed reality IGS system into the OR. A taxonomy of IGS visualization systems is a step toward developing a common language that will help developers and end users discuss and understand the constituents of a mixed reality visualization system, facilitating a greater presence of future systems in the OR. We evaluate the DVV taxonomy based on its goodness of fit and completeness. We demonstrate the utility of the DVV taxonomy by classifying 17 state-of-the-art research papers in the domain of mixed reality visualization IGS systems. Our classification shows that few IGS visualization systems' components have been validated and even fewer are evaluated.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Mixed reality visualizations are increasingly studied for use in image guided surgery (IGS) systems, yet few mixed reality systems have been introduced for daily use into the operating room (OR). This may be the result of several factors: the systems are developed from a technical perspective, are rarely evaluated in the field, and/or lack consideration of the end user and the constraints of the OR. We introduce the Data, Visualization processing, View (DVV) taxonomy which defines each of the major components required to implement a mixed reality IGS system. We propose that these components be considered and used as validation criteria for introducing a mixed reality IGS system into the OR. A taxonomy of IGS visualization systems is a step toward developing a common language that will help developers and end users discuss and understand the constituents of a mixed reality visualization system, facilitating a greater presence of future systems in the OR. We evaluate the DVV taxonomy based on its goodness of fit and completeness. We demonstrate the utility of the DVV taxonomy by classifying 17 state-of-the-art research papers in the domain of mixed reality visualization IGS systems. Our classification shows that few IGS visualization systems' components have been validated and even fewer are evaluated.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Mixed reality visualizations are increasingly studied for use in image guided surgery (IGS) systems, yet few mixed reality systems have been introduced for daily use into the operating room (OR). This may be the result of several factors: the systems are developed from a technical perspective, are rarely evaluated in the field, and/or lack consideration of the end user and the constraints of the OR. We introduce the Data, Visualization processing, View (DVV) taxonomy which defines each of the major components required to implement a mixed reality IGS system. We propose that these components be considered and used as validation criteria for introducing a mixed reality IGS system into the OR. A taxonomy of IGS visualization systems is a step toward developing a common language that will help developers and end users discuss and understand the constituents of a mixed reality visualization system, facilitating a greater presence of future systems in the OR. We evaluate the DVV taxonomy based on its goodness of fit and completeness. We demonstrate the utility of the DVV taxonomy by classifying 17 state-of-the-art research papers in the domain of mixed reality visualization IGS systems. Our classification shows that few IGS visualization systems' components have been validated and even fewer are evaluated.",
"title": "DVV: A Taxonomy for Mixed Reality Visualization in Image Guided Surgery",
"normalizedTitle": "DVV: A Taxonomy for Mixed Reality Visualization in Image Guided Surgery",
"fno": "ttg2012020332",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Taxonomy",
"Mixed Reality",
"Augmented Reality",
"Augmented Virtuality",
"Visualization",
"Image Guided Surgery"
],
"authors": [
{
"givenName": "Marta",
"surname": "Kersten-Oertel",
"fullName": "Marta Kersten-Oertel",
"affiliation": "Montreal Neurological Institute (MNI), Montréal",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Pierre",
"surname": "Jannin",
"fullName": "Pierre Jannin",
"affiliation": "Projet-Unité Visages-U746 INRIA, INSERM, CNRS and Université de Rennes 1, Rennes",
"__typename": "ArticleAuthorType"
},
{
"givenName": "D. Louis",
"surname": "Collins",
"fullName": "D. Louis Collins",
"affiliation": "Montreal Neurological Institute (MNI), Montréal",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2012-02-01 00:00:00",
"pubType": "trans",
"pages": "332-352",
"year": "2012",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/ismar-amh/2009/5508/0/05336726",
"title": "Loosely-coupled mixed reality: Using the environment metaphorically",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-amh/2009/05336726/12OmNCbU2Wk",
"parentPublication": {
"id": "proceedings/ismar-amh/2009/5508/0",
"title": "2009 IEEE International Symposium on Mixed and Augmented Reality - Arts, Media and Humanities",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2010/6237/0/05444792",
"title": "Mixed reality in virtual world teleconferencing",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2010/05444792/12OmNwpoFEM",
"parentPublication": {
"id": "proceedings/vr/2010/6237/0",
"title": "2010 IEEE Virtual Reality Conference (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvvrhc/1998/8283/0/82830078",
"title": "Vision and Graphics in Producing Mixed Reality Worlds",
"doi": null,
"abstractUrl": "/proceedings-article/cvvrhc/1998/82830078/12OmNylbov1",
"parentPublication": {
"id": "proceedings/cvvrhc/1998/8283/0",
"title": "Computer Vision for Virtual Reality Based Human Communications, Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2010/6237/0/05444815",
"title": "Egocentric space-distorting visualizations for rapid environment exploration in mobile mixed reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2010/05444815/12OmNylsZU8",
"parentPublication": {
"id": "proceedings/vr/2010/6237/0",
"title": "2010 IEEE Virtual Reality Conference (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/pc/2009/03/mpc2009030002",
"title": "Through Tinted Eyeglasses",
"doi": null,
"abstractUrl": "/magazine/pc/2009/03/mpc2009030002/13rRUx0xPki",
"parentPublication": {
"id": "mags/pc",
"title": "IEEE Pervasive Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09978915",
"title": "Visual Cue Based Corrective Feedback for Motor Skill Training in Mixed Reality: A Survey",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09978915/1IXUnNBj0Yw",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a124",
"title": "X-Space: A Tool for Extending Mixed Reality Space from Web2D Visualization Anywhere",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a124/1J7W7m1yZgI",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2022/5365/0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a891",
"title": "MR-FoodCoach: Enabling a convenience store on mixed reality space for healthier purchases",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a891/1J7WnK9PRxS",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2022/5365/0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/09/09060980",
"title": "Visualization Techniques in Augmented Reality: A Taxonomy, Methods and Patterns",
"doi": null,
"abstractUrl": "/journal/tg/2021/09/09060980/1iRo7RmpTa0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aivr/2020/7463/0/746300a017",
"title": "Interactive Design of Gallery Walls via Mixed Reality",
"doi": null,
"abstractUrl": "/proceedings-article/aivr/2020/746300a017/1qpzDsm1dIc",
"parentPublication": {
"id": "proceedings/aivr/2020/7463/0",
"title": "2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttg2012020309",
"articleId": "13rRUxBJhmP",
"__typename": "AdjacentArticleType"
},
"next": null,
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzmclnL",
"title": "November/December",
"year": "2006",
"issueNum": "06",
"idPrefix": "tg",
"pubType": "journal",
"volume": "12",
"label": "November/December",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUNvgz9B",
"doi": "10.1109/TVCG.2006.109",
"abstract": "Abstract—This paper presents a tool for the visual analysis of navigation patterns of moving entities, such as users, virtual characters, or vehicles in 3D Virtual Environments (VEs). The tool, called VU-Flow, provides a set of interactive visualizations that highlight interesting navigation behaviors of single or groups of moving entities that were the VE together or separately. The visualizations help to improve the design of VEs and to study the navigation behavior of users, e.g., during controlled experiments. Besides VEs, the proposed techniques could also be applied to visualize real-world data recorded by positioning systems, allowing one to employ VU-Flow in domains such as urban planning, transportation, and emergency response.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Abstract—This paper presents a tool for the visual analysis of navigation patterns of moving entities, such as users, virtual characters, or vehicles in 3D Virtual Environments (VEs). The tool, called VU-Flow, provides a set of interactive visualizations that highlight interesting navigation behaviors of single or groups of moving entities that were the VE together or separately. The visualizations help to improve the design of VEs and to study the navigation behavior of users, e.g., during controlled experiments. Besides VEs, the proposed techniques could also be applied to visualize real-world data recorded by positioning systems, allowing one to employ VU-Flow in domains such as urban planning, transportation, and emergency response.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Abstract—This paper presents a tool for the visual analysis of navigation patterns of moving entities, such as users, virtual characters, or vehicles in 3D Virtual Environments (VEs). The tool, called VU-Flow, provides a set of interactive visualizations that highlight interesting navigation behaviors of single or groups of moving entities that were the VE together or separately. The visualizations help to improve the design of VEs and to study the navigation behavior of users, e.g., during controlled experiments. Besides VEs, the proposed techniques could also be applied to visualize real-world data recorded by positioning systems, allowing one to employ VU-Flow in domains such as urban planning, transportation, and emergency response.",
"title": "VU-Flow: A Visualization Tool for Analyzing Navigation in Virtual Environments",
"normalizedTitle": "VU-Flow: A Visualization Tool for Analyzing Navigation in Virtual Environments",
"fno": "v1475",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Information Visualization",
"Virtual Reality",
"Evaluation Methodology",
"Visualization Systems And Software"
],
"authors": [
{
"givenName": "Luca",
"surname": "Chittaro",
"fullName": "Luca Chittaro",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Roberto",
"surname": "Ranon",
"fullName": "Roberto Ranon",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lucio",
"surname": "Ieronutti",
"fullName": "Lucio Ieronutti",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2006-11-01 00:00:00",
"pubType": "trans",
"pages": "1475-1485",
"year": "2006",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/vr/1999/0093/0/00930096",
"title": "User-Centered Design and Evaluation of a Real-Time Battlefield Visualization Virtual Environment",
"doi": null,
"abstractUrl": "/proceedings-article/vr/1999/00930096/12OmNA2cYEt",
"parentPublication": {
"id": "proceedings/vr/1999/0093/0",
"title": "Proceedings of Virtual Reality",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2008/2047/0/04476620",
"title": "Poster: An Approach to Study of Hypermedia Information Navigation in Virtual Environments",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2008/04476620/12OmNAolGUm",
"parentPublication": {
"id": "proceedings/3dui/2008/2047/0",
"title": "2008 IEEE Symposium on 3D User Interfaces",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2005/8929/0/01492761",
"title": "The effect of trails on first-time and subsequent navigation in a virtual environment",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2005/01492761/12OmNBfqG2v",
"parentPublication": {
"id": "proceedings/vr/2005/8929/0",
"title": "IEEE Virtual Reality 2005",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2010/6237/0/05444816",
"title": "Improved Redirection with Distractors: A large-scale-real-walking locomotion interface and its effect on navigation in virtual environments",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2010/05444816/12OmNqBbHKZ",
"parentPublication": {
"id": "proceedings/vr/2010/6237/0",
"title": "2010 IEEE Virtual Reality Conference (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar/2013/2869/0/06671807",
"title": "User awareness of tracking uncertainties in AR navigation scenarios",
"doi": null,
"abstractUrl": "/proceedings-article/ismar/2013/06671807/12OmNqFJhRx",
"parentPublication": {
"id": "proceedings/ismar/2013/2869/0",
"title": "2013 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2017/6647/0/07892348",
"title": "Steering locomotion by vestibular perturbation in room-scale VR",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2017/07892348/12OmNvrMUgU",
"parentPublication": {
"id": "proceedings/vr/2017/6647/0",
"title": "2017 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aqsdt/1992/2620/0/00205852",
"title": "A-Vu: a visualization tool for complex software systems",
"doi": null,
"abstractUrl": "/proceedings-article/aqsdt/1992/00205852/12OmNzZEAvd",
"parentPublication": {
"id": "proceedings/aqsdt/1992/2620/0",
"title": "Proceedings of the Second Symposium on Assessment of Quality Software Development Tools",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440821",
"title": "An Information-Theoretic Approach to the Cost-benefit Analysis of Visualization in Virtual Environments",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440821/17D45WB0qbn",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2022/9617/0/961700a802",
"title": "User Preference for Navigation Instructions in Mixed Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2022/961700a802/1CJbQXinARi",
"parentPublication": {
"id": "proceedings/vr/2022/9617/0",
"title": "2022 IEEE on Conference Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08797721",
"title": "Virtual vs. Physical Navigation in VR: Study of Gaze and Body Segments Temporal Reorientation Behaviour",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08797721/1cJ0WHR3fPi",
"parentPublication": {
"id": "proceedings/vr/2019/1377/0",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "v1461",
"articleId": "13rRUwgQpDk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "v1486",
"articleId": "13rRUxC0SEa",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1IbM4t1NH1K",
"title": "Dec.",
"year": "2022",
"issueNum": "06",
"idPrefix": "bd",
"pubType": "journal",
"volume": "8",
"label": "Dec.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1rFvAIU5Og0",
"doi": "10.1109/TBDATA.2021.3063553",
"abstract": "Accurate long-term origin-destination demand (OD) prediction can help understand traffic flow dynamics, which plays an essential role in urban transportation planning. However, the main challenge originates from the complex and dynamic spatial-temporal correlation of the time-varying traffic information. In response, a graph deep learning model for long-term OD prediction (ST-GDL) is proposed in this article, which is among the pioneering work that obtains both short-term and long-term OD predictions simultaneously. ST-GDL avoids the conventional multi-step forecasting and thus prevents learning from prediction errors, rendering better long-term forecasts. The proposed method captures time attributes from multiple time scales, namely closeness, periodicity, and trend, to study the features with temporal dynamics. In addition, two gate mechanisms are introduced over the vanilla convolution operation to alleviates the error accumulation issue of typical recurrent forecast in long-term OD prediction. A method based on graph convolution is proposed to capture the dynamic spatial relationship, which projects the transportation network into a graphical time-series. Finally, the long-term OD prediction results are obtained by combining the extracted spatio-temporal features with external features from the meteorological information. Case studies on practical datasets show that the proposed model is superior to existing methods in long-term OD prediction problems.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Accurate long-term origin-destination demand (OD) prediction can help understand traffic flow dynamics, which plays an essential role in urban transportation planning. However, the main challenge originates from the complex and dynamic spatial-temporal correlation of the time-varying traffic information. In response, a graph deep learning model for long-term OD prediction (ST-GDL) is proposed in this article, which is among the pioneering work that obtains both short-term and long-term OD predictions simultaneously. ST-GDL avoids the conventional multi-step forecasting and thus prevents learning from prediction errors, rendering better long-term forecasts. The proposed method captures time attributes from multiple time scales, namely closeness, periodicity, and trend, to study the features with temporal dynamics. In addition, two gate mechanisms are introduced over the vanilla convolution operation to alleviates the error accumulation issue of typical recurrent forecast in long-term OD prediction. A method based on graph convolution is proposed to capture the dynamic spatial relationship, which projects the transportation network into a graphical time-series. Finally, the long-term OD prediction results are obtained by combining the extracted spatio-temporal features with external features from the meteorological information. Case studies on practical datasets show that the proposed model is superior to existing methods in long-term OD prediction problems.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Accurate long-term origin-destination demand (OD) prediction can help understand traffic flow dynamics, which plays an essential role in urban transportation planning. However, the main challenge originates from the complex and dynamic spatial-temporal correlation of the time-varying traffic information. In response, a graph deep learning model for long-term OD prediction (ST-GDL) is proposed in this article, which is among the pioneering work that obtains both short-term and long-term OD predictions simultaneously. ST-GDL avoids the conventional multi-step forecasting and thus prevents learning from prediction errors, rendering better long-term forecasts. The proposed method captures time attributes from multiple time scales, namely closeness, periodicity, and trend, to study the features with temporal dynamics. In addition, two gate mechanisms are introduced over the vanilla convolution operation to alleviates the error accumulation issue of typical recurrent forecast in long-term OD prediction. A method based on graph convolution is proposed to capture the dynamic spatial relationship, which projects the transportation network into a graphical time-series. Finally, the long-term OD prediction results are obtained by combining the extracted spatio-temporal features with external features from the meteorological information. Case studies on practical datasets show that the proposed model is superior to existing methods in long-term OD prediction problems.",
"title": "Long-Term Origin-Destination Demand Prediction With Graph Deep Learning",
"normalizedTitle": "Long-Term Origin-Destination Demand Prediction With Graph Deep Learning",
"fno": "09369004",
"hasPdf": true,
"idPrefix": "bd",
"keywords": [
"Deep Learning Artificial Intelligence",
"Forecasting Theory",
"Graph Theory",
"Road Traffic",
"Time Series",
"Traffic Information Systems",
"Transportation",
"Dynamic Spatial Relationship",
"Dynamic Spatial Temporal Correlation",
"Graph Convolution",
"Graph Deep Learning Model",
"Graphical Time Series",
"Long Term Forecasting",
"Long Term OD Prediction Problems",
"Long Term Origin Destination Demand Prediction",
"Meteorological Information",
"Multistep Forecasting",
"Short Term OD Predictions",
"ST GDL",
"Time Varying Traffic Information",
"Traffic Flow Dynamics",
"Urban Transportation Planning",
"Vanilla Convolution Operation",
"Predictive Models",
"Convolution",
"Deep Learning",
"Feature Extraction",
"Correlation",
"Task Analysis",
"Forecasting",
"Long Term OD Prediction",
"Graph Deep Learning",
"Gate Mechanism",
"Graph Convolution"
],
"authors": [
{
"givenName": "Xiexin",
"surname": "Zou",
"fullName": "Xiexin Zou",
"affiliation": "Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shiyao",
"surname": "Zhang",
"fullName": "Shiyao Zhang",
"affiliation": "Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chenhan",
"surname": "Zhang",
"fullName": "Chenhan Zhang",
"affiliation": "Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "James J.Q.",
"surname": "Yu",
"fullName": "James J.Q. Yu",
"affiliation": "Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Edward",
"surname": "Chung",
"fullName": "Edward Chung",
"affiliation": "The Hong Kong Polytechnic University, Kowloon, Hong Kong",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2022-12-01 00:00:00",
"pubType": "trans",
"pages": "1481-1495",
"year": "2022",
"issn": "2332-7790",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tp/2023/03/09785888",
"title": "Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation",
"doi": null,
"abstractUrl": "/journal/tp/2023/03/09785888/1DPaAhAefgQ",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2022/9792/0/09912866",
"title": "Dynamic Graph Convolutional Network for Long Short-term Traffic Flow Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2022/09912866/1HBKboFr85O",
"parentPublication": {
"id": "proceedings/iscc/2022/9792/0",
"title": "2022 IEEE Symposium on Computers and Communications (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2022/5099/0/509900a879",
"title": "Origin-Destination Traffic Prediction based on Hybrid Spatio-Temporal Network",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2022/509900a879/1KpCBZggOS4",
"parentPublication": {
"id": "proceedings/icdm/2022/5099/0",
"title": "2022 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2019/9552/0/955200a760",
"title": "Taxi Origin-Destination Demand Prediction with Contextualized Spatial-Temporal Network",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2019/955200a760/1cdOTb4hTJC",
"parentPublication": {
"id": "proceedings/icme/2019/9552/0",
"title": "2019 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mdm/2019/3363/0/336300a226",
"title": "STCNN: A Spatio-Temporal Convolutional Neural Network for Long-Term Traffic Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/mdm/2019/336300a226/1ckrQrE0EQE",
"parentPublication": {
"id": "proceedings/mdm/2019/3363/0",
"title": "2019 20th IEEE International Conference on Mobile Data Management (MDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2020/2903/0/09101647",
"title": "Stochastic Origin-Destination Matrix Forecasting Using Dual-Stage Graph Convolutional, Recurrent Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2020/09101647/1kaMCw5TKWA",
"parentPublication": {
"id": "proceedings/icde/2020/2903/0",
"title": "2020 IEEE 36th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2020/2903/0/09101359",
"title": "Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2020/09101359/1kaMzQnyYPm",
"parentPublication": {
"id": "proceedings/icde/2020/2903/0",
"title": "2020 IEEE 36th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2020/8316/0/831600b160",
"title": "Multi-attention 3D Residual Neural Network for Origin-Destination Crowd Flow Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2020/831600b160/1r54CJAvOFy",
"parentPublication": {
"id": "proceedings/icdm/2020/8316/0",
"title": "2020 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/01/09416848",
"title": "Inferring Origin-Destination Flows From Population Distribution",
"doi": null,
"abstractUrl": "/journal/tk/2023/01/09416848/1t8VNb1SvEk",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2021/0898/0/089800a268",
"title": "Clustering Shift Graph Convolutional Network for Taxi Origin-Destination Demand Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2021/089800a268/1zw61N7RoA0",
"parentPublication": {
"id": "proceedings/ictai/2021/0898/0",
"title": "2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09512470",
"articleId": "1w0wwuGrVkY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09506836",
"articleId": "1vNfkchrt1m",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwCJOWs",
"title": "Oct.",
"year": "2016",
"issueNum": "10",
"idPrefix": "tk",
"pubType": "journal",
"volume": "28",
"label": "Oct.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwjoNxy",
"doi": "10.1109/TKDE.2016.2581158",
"abstract": "In team sports like soccer, utilizing tracking data for analysis is challenging due to the dynamic and multi-agent nature of the data. The biggest issue surrounds the changing of positions or “roles” between players on a frame-to-frame basis, which causes misalignment of the data and makes it difficult to perform team analysis. In this paper, we present an unsupervised method to learn a formation template which allows us to “align” the tracking data at the frame level. Not only does this approach give important contextual information to facilitate large-scale analysis (e.g., we know when a player is in the left-wing position compared to left-back), it also yields the team structure or “formation” which serves as a strong descriptor for identifying a team’s style. The utility of the approach is demonstrated on a full season of player and ball tracking data from a professional soccer league consisting of over 21.5 million frames of player tracking data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In team sports like soccer, utilizing tracking data for analysis is challenging due to the dynamic and multi-agent nature of the data. The biggest issue surrounds the changing of positions or “roles” between players on a frame-to-frame basis, which causes misalignment of the data and makes it difficult to perform team analysis. In this paper, we present an unsupervised method to learn a formation template which allows us to “align” the tracking data at the frame level. Not only does this approach give important contextual information to facilitate large-scale analysis (e.g., we know when a player is in the left-wing position compared to left-back), it also yields the team structure or “formation” which serves as a strong descriptor for identifying a team’s style. The utility of the approach is demonstrated on a full season of player and ball tracking data from a professional soccer league consisting of over 21.5 million frames of player tracking data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In team sports like soccer, utilizing tracking data for analysis is challenging due to the dynamic and multi-agent nature of the data. The biggest issue surrounds the changing of positions or “roles” between players on a frame-to-frame basis, which causes misalignment of the data and makes it difficult to perform team analysis. In this paper, we present an unsupervised method to learn a formation template which allows us to “align” the tracking data at the frame level. Not only does this approach give important contextual information to facilitate large-scale analysis (e.g., we know when a player is in the left-wing position compared to left-back), it also yields the team structure or “formation” which serves as a strong descriptor for identifying a team’s style. The utility of the approach is demonstrated on a full season of player and ball tracking data from a professional soccer league consisting of over 21.5 million frames of player tracking data.",
"title": "Discovering Team Structures in Soccer from Spatiotemporal Data",
"normalizedTitle": "Discovering Team Structures in Soccer from Spatiotemporal Data",
"fno": "07492601",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Trajectory",
"Probability Density Function",
"Heating",
"Entropy",
"Spatiotemporal Phenomena",
"Graphical Models",
"Distribution Functions",
"Spatio Temporal Data",
"Formation",
"Team Analysis",
"Multi Agent",
"Sports Analytics",
"Soccer",
"Role",
"Alignment",
"Group Behaviour"
],
"authors": [
{
"givenName": "Alina",
"surname": "Bialkowski",
"fullName": "Alina Bialkowski",
"affiliation": "Image and Video Laboratory, Queensland University of Technology, Brisbane City, Australia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Patrick",
"surname": "Lucey",
"fullName": "Patrick Lucey",
"affiliation": "STATS, Chicago, IL",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peter",
"surname": "Carr",
"fullName": "Peter Carr",
"affiliation": "Disney Research, Pittsburgh, PA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Iain",
"surname": "Matthews",
"fullName": "Iain Matthews",
"affiliation": "Disney Research, Pittsburgh, PA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sridha",
"surname": "Sridharan",
"fullName": "Sridha Sridharan",
"affiliation": "Image and Video Laboratory, Queensland University of Technology, Brisbane City, Australia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Clinton",
"surname": "Fookes",
"fullName": "Clinton Fookes",
"affiliation": "Image and Video Laboratory, Queensland University of Technology, Brisbane City, Australia",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "10",
"pubDate": "2016-10-01 00:00:00",
"pubType": "trans",
"pages": "2596-2605",
"year": "2016",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/dcoss/2011/0512/0/05982204",
"title": "A wireless sensor network for soccer team monitoring",
"doi": null,
"abstractUrl": "/proceedings-article/dcoss/2011/05982204/12OmNyugyJ1",
"parentPublication": {
"id": "proceedings/dcoss/2011/0512/0",
"title": "2011 International Conference on Distributed Computing in Sensor Systems and Workshops (DCOSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2014/4302/0/4302a725",
"title": "Large-Scale Analysis of Soccer Matches Using Spatiotemporal Tracking Data",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2014/4302a725/12OmNz61dIH",
"parentPublication": {
"id": "proceedings/icdm/2014/4302/0",
"title": "2014 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2010/7846/0/05571291",
"title": "Dynamic Visualizations for Soccer Statistical Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2010/05571291/12OmNzTH0V2",
"parentPublication": {
"id": "proceedings/iv/2010/7846/0",
"title": "2010 14th International Conference Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2014/4274/0/4274a009",
"title": "Identifying Team Style in Soccer Using Formations Learned from Spatiotemporal Tracking Data",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2014/4274a009/12OmNzwHvjK",
"parentPublication": {
"id": "proceedings/icdmw/2014/4274/0",
"title": "2014 IEEE International Conference on Data Mining Workshop (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440804",
"title": "ForVizor: Visualizing Spatio-Temporal Team Formations in Soccer",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440804/17D45WXIkAs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2018/9156/0/915600a409",
"title": "Smart Data Scouting in Professional Soccer: Evaluating Passing Performance Based on Position Tracking Data",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2018/915600a409/17D45WaTkoi",
"parentPublication": {
"id": "proceedings/e-science/2018/9156/0",
"title": "2018 IEEE 14th International Conference on e-Science (e-Science)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/091500c141",
"title": "Transductive Weakly-Supervised Player Detection using Soccer Broadcast Videos",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500c141/1B13zMZjj9e",
"parentPublication": {
"id": "proceedings/wacv/2022/0915/0",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2022/8739/0/873900d490",
"title": "SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videos",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2022/873900d490/1G56YcMtuko",
"parentPublication": {
"id": "proceedings/cvprw/2022/8739/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09894103",
"title": "Team-Builder: Toward More Effective Lineup Selection in Soccer",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09894103/1GIqpPbyH7y",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300c825",
"title": "Explicit Spatiotemporal Joint Relation Learning for Tracking Human Pose",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300c825/1i5mpre7N72",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07496867",
"articleId": "13rRUwjGoM4",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07322265",
"articleId": "13rRUyfKIIk",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1wznUTxaKsw",
"title": "Oct.",
"year": "2021",
"issueNum": "10",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Oct.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1jyxzgbbDs4",
"doi": "10.1109/TVCG.2020.2992200",
"abstract": "Visualizing massive scale human movement in cities plays an important role in solving many of the problems that modern cities face (e.g., traffic optimization, business site configuration). In this article, we study a big mobile location dataset that covers millions of city residents, but is temporally sparse on the trajectory of individual user. Mapping sparse trajectories to illustrate population movement poses several challenges from both analysis and visualization perspectives. In the literature, there are a few techniques designed for sparse trajectory visualization; yet they do not consider trajectories collected from mobile apps that possess long-tailed sparsity with record intervals as long as hours. This article introduces UrbanMotion, a visual analytics system that extends the original wind map design by supporting map-matched local movements, multi-directional population flows, and population distributions. Effective methods are proposed to extract and aggregate population movements from dense parts of the trajectories leveraging their long-tailed sparsity. Both characteristic and anomalous patterns are discovered and visualized. We conducted three case studies, one comparative experiment, and collected expert feedback in the application domains of commuting analysis, event detection, and business site configuration. The study result demonstrates the significance and effectiveness of our system in helping to complete key analytics tasks for urban users.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Visualizing massive scale human movement in cities plays an important role in solving many of the problems that modern cities face (e.g., traffic optimization, business site configuration). In this article, we study a big mobile location dataset that covers millions of city residents, but is temporally sparse on the trajectory of individual user. Mapping sparse trajectories to illustrate population movement poses several challenges from both analysis and visualization perspectives. In the literature, there are a few techniques designed for sparse trajectory visualization; yet they do not consider trajectories collected from mobile apps that possess long-tailed sparsity with record intervals as long as hours. This article introduces UrbanMotion, a visual analytics system that extends the original wind map design by supporting map-matched local movements, multi-directional population flows, and population distributions. Effective methods are proposed to extract and aggregate population movements from dense parts of the trajectories leveraging their long-tailed sparsity. Both characteristic and anomalous patterns are discovered and visualized. We conducted three case studies, one comparative experiment, and collected expert feedback in the application domains of commuting analysis, event detection, and business site configuration. The study result demonstrates the significance and effectiveness of our system in helping to complete key analytics tasks for urban users.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Visualizing massive scale human movement in cities plays an important role in solving many of the problems that modern cities face (e.g., traffic optimization, business site configuration). In this article, we study a big mobile location dataset that covers millions of city residents, but is temporally sparse on the trajectory of individual user. Mapping sparse trajectories to illustrate population movement poses several challenges from both analysis and visualization perspectives. In the literature, there are a few techniques designed for sparse trajectory visualization; yet they do not consider trajectories collected from mobile apps that possess long-tailed sparsity with record intervals as long as hours. This article introduces UrbanMotion, a visual analytics system that extends the original wind map design by supporting map-matched local movements, multi-directional population flows, and population distributions. Effective methods are proposed to extract and aggregate population movements from dense parts of the trajectories leveraging their long-tailed sparsity. Both characteristic and anomalous patterns are discovered and visualized. We conducted three case studies, one comparative experiment, and collected expert feedback in the application domains of commuting analysis, event detection, and business site configuration. The study result demonstrates the significance and effectiveness of our system in helping to complete key analytics tasks for urban users.",
"title": "UrbanMotion: Visual Analysis of Metropolitan-Scale Sparse Trajectories",
"normalizedTitle": "UrbanMotion: Visual Analysis of Metropolitan-Scale Sparse Trajectories",
"fno": "09086086",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Image Motion Analysis",
"Location Based Services",
"Mobile Computing",
"Town And Country Planning",
"Long Tailed Sparsity",
"Metropolitan Scale Sparse Trajectories",
"Big Mobile Location Dataset",
"Sparse Trajectory Visualization",
"Mobile Apps",
"Visual Analytics System",
"Map Matched Local Movements",
"Population Distributions",
"Multidirectional Population Flows",
"Human Movement",
"Wind Map Design",
"Sparse Trajectories Mapping",
"Trajectory",
"Data Visualization",
"Urban Areas",
"Sociology",
"Statistics",
"Visualization",
"Spatiotemporal Phenomena",
"Movement Visualization",
"Sparse Trajectory",
"Wind Map"
],
"authors": [
{
"givenName": "Lei",
"surname": "Shi",
"fullName": "Lei Shi",
"affiliation": "SKLSDE and Beijing Advanced Innovation Center for Big Data and Brain Computing, School of Computer Science and Engineering, Beihang University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Congcong",
"surname": "Huang",
"fullName": "Congcong Huang",
"affiliation": "SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Meijun",
"surname": "Liu",
"fullName": "Meijun Liu",
"affiliation": "SKLSDE and Beijing Advanced Innovation Center for Big Data and Brain Computing, School of Computer Science and Engineering, Beihang University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jia",
"surname": "Yan",
"fullName": "Jia Yan",
"affiliation": "SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tao",
"surname": "Jiang",
"fullName": "Tao Jiang",
"affiliation": "SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zhihao",
"surname": "Tan",
"fullName": "Zhihao Tan",
"affiliation": "SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yifan",
"surname": "Hu",
"fullName": "Yifan Hu",
"affiliation": "Yahoo Labs, Sunnyvale, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wei",
"surname": "Chen",
"fullName": "Wei Chen",
"affiliation": "State Key Lab of CAD&CG, Zhejiang University, Hangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiatian",
"surname": "Zhang",
"fullName": "Xiatian Zhang",
"affiliation": "Beijing Tendcloud Tianxia Technology Co., Ltd, Beijing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "10",
"pubDate": "2021-10-01 00:00:00",
"pubType": "trans",
"pages": "3881-3899",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/lcn/2015/6770/0/07366290",
"title": "Toward a robust sparse data representation for wireless sensor networks",
"doi": null,
"abstractUrl": "/proceedings-article/lcn/2015/07366290/12OmNApLGxw",
"parentPublication": {
"id": "proceedings/lcn/2015/6770/0",
"title": "2015 IEEE 40th Conference on Local Computer Networks (LCN 2015)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2012/4711/0/4711a158",
"title": "Spatiotemporal Saliency Detection via Sparse Representation",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2012/4711a158/12OmNzAoi3b",
"parentPublication": {
"id": "proceedings/icme/2012/4711/0",
"title": "2012 IEEE International Conference on Multimedia and Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2018/05/mcg2018050026",
"title": "Spatio-Temporal Urban Data Analysis: A Visual Analytics Perspective",
"doi": null,
"abstractUrl": "/magazine/cg/2018/05/mcg2018050026/13WBGTItFGV",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2022/10/09855834",
"title": "Cerebron: A Reconfigurable Architecture for Spatiotemporal Sparse Spiking Neural Networks",
"doi": null,
"abstractUrl": "/journal/si/2022/10/09855834/1FSY6IEYuc0",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08807274",
"title": "A Natural-language-based Visual Query Approach of Uncertain Human Trajectories",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08807274/1cG67KjJLz2",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2019/9226/0/922600a232",
"title": "Interactive Spatiotemporal Visualization of Phase Space Particle Trajectories Using Distance Plots",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2019/922600a232/1cMF7xn5Rbq",
"parentPublication": {
"id": "proceedings/pacificvis/2019/9226/0",
"title": "2019 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mdm/2019/3363/0/336300a473",
"title": "Fine-Grained Dynamic Population Mapping Method Based on Large-Scale Sparse Mobile Phone Data",
"doi": null,
"abstractUrl": "/proceedings-article/mdm/2019/336300a473/1ckrMZ4XUR2",
"parentPublication": {
"id": "proceedings/mdm/2019/3363/0",
"title": "2019 20th IEEE International Conference on Mobile Data Management (MDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a378",
"title": "RoseTrajVis: Visual Analytics of Trajectories with Rose Diagrams",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a378/1rSRa9dXxDO",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2021/9184/0/918400c189",
"title": "TrajForesee: How limited detailed trajectories enhance large-scale sparse information to predict vehicle trajectories?",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2021/918400c189/1uGXouWwcH6",
"parentPublication": {
"id": "proceedings/icde/2021/9184/0",
"title": "2021 IEEE 37th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mipr/2021/1865/0/186500a260",
"title": "Clustering Trajectories via Sparse Auto-encoders",
"doi": null,
"abstractUrl": "/proceedings-article/mipr/2021/186500a260/1xPsquajJ6g",
"parentPublication": {
"id": "proceedings/mipr/2021/1865/0",
"title": "2021 IEEE 4th International Conference on Multimedia Information Processing and Retrieval (MIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09082171",
"articleId": "1jqf3m1ydCo",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09088257",
"articleId": "1jBRtSpGSVq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1wGsKFgeS0U",
"name": "ttg202110-09086086s1-supp1-2992200.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202110-09086086s1-supp1-2992200.pdf",
"extension": "pdf",
"size": "2.71 MB",
"__typename": "WebExtraType"
},
{
"id": "1wGsKo8D5xC",
"name": "ttg202110-09086086s1-supp2-2992200.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202110-09086086s1-supp2-2992200.mp4",
"extension": "mp4",
"size": "42.4 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNxiKs8S",
"title": "April-June",
"year": "2020",
"issueNum": "02",
"idPrefix": "su",
"pubType": "journal",
"volume": "5",
"label": "April-June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1kxWWHQPbJC",
"doi": "10.1109/TSUSC.2018.2841998",
"abstract": "Long distance high bandwidth networks are spanning several continents and many remote Healthcare centers are centralizing their data centers for economic reasons. For the best performance of their data centers, TCP (Transmission Control Protocol) performance and data security are the main critical issues in these network scenarios. TCP performance is directly related to its congestion control mechanism which is responsible for detecting and reacting to the overload traffic on the network. Data security is related to the security mechanism being used by sender and receiver nodes during communication. Linux users, which have rapidly increased in the last five years and most of the Healthcare data centers are being deployed on the Linux operating system, focus the researchers to work on Linux to enhance its performance and security accordingly. The Linux operating system uses TCP CUBIC as a congestion control mechanism with TCP during communication. TCP CUBIC became the default congestion control mechanism of Linux in 2006 after kernel 2.6.18. TCP CUBIC is fundamentally a loss based TCP congestion control mechanism and at each packet loss detection, it reduces its Congestion Window (cwnd) size 20 percent instead of 50 percent as in trademark congestion control mechanism Standard TCP. The aim of this paper is to design a new security mechanism that will work with TCP CUBIC to achieve the maximum possible performance and security over the network link. In this paper, Network Simulator 2 (NS-2) is used to compare the performance of TCP CUBIC with state-of-the-art mechanisms in long and short Round Trip Time (RTT), high bandwidth network scenarios. Results show that when new security mechanism is used with TCP CUBIC, overall better performance in the form of protocol fairness, TCP friendliness, goodput, and convergence time is achieved over the network link.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Long distance high bandwidth networks are spanning several continents and many remote Healthcare centers are centralizing their data centers for economic reasons. For the best performance of their data centers, TCP (Transmission Control Protocol) performance and data security are the main critical issues in these network scenarios. TCP performance is directly related to its congestion control mechanism which is responsible for detecting and reacting to the overload traffic on the network. Data security is related to the security mechanism being used by sender and receiver nodes during communication. Linux users, which have rapidly increased in the last five years and most of the Healthcare data centers are being deployed on the Linux operating system, focus the researchers to work on Linux to enhance its performance and security accordingly. The Linux operating system uses TCP CUBIC as a congestion control mechanism with TCP during communication. TCP CUBIC became the default congestion control mechanism of Linux in 2006 after kernel 2.6.18. TCP CUBIC is fundamentally a loss based TCP congestion control mechanism and at each packet loss detection, it reduces its Congestion Window (cwnd) size 20 percent instead of 50 percent as in trademark congestion control mechanism Standard TCP. The aim of this paper is to design a new security mechanism that will work with TCP CUBIC to achieve the maximum possible performance and security over the network link. In this paper, Network Simulator 2 (NS-2) is used to compare the performance of TCP CUBIC with state-of-the-art mechanisms in long and short Round Trip Time (RTT), high bandwidth network scenarios. Results show that when new security mechanism is used with TCP CUBIC, overall better performance in the form of protocol fairness, TCP friendliness, goodput, and convergence time is achieved over the network link.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Long distance high bandwidth networks are spanning several continents and many remote Healthcare centers are centralizing their data centers for economic reasons. For the best performance of their data centers, TCP (Transmission Control Protocol) performance and data security are the main critical issues in these network scenarios. TCP performance is directly related to its congestion control mechanism which is responsible for detecting and reacting to the overload traffic on the network. Data security is related to the security mechanism being used by sender and receiver nodes during communication. Linux users, which have rapidly increased in the last five years and most of the Healthcare data centers are being deployed on the Linux operating system, focus the researchers to work on Linux to enhance its performance and security accordingly. The Linux operating system uses TCP CUBIC as a congestion control mechanism with TCP during communication. TCP CUBIC became the default congestion control mechanism of Linux in 2006 after kernel 2.6.18. TCP CUBIC is fundamentally a loss based TCP congestion control mechanism and at each packet loss detection, it reduces its Congestion Window (cwnd) size 20 percent instead of 50 percent as in trademark congestion control mechanism Standard TCP. The aim of this paper is to design a new security mechanism that will work with TCP CUBIC to achieve the maximum possible performance and security over the network link. In this paper, Network Simulator 2 (NS-2) is used to compare the performance of TCP CUBIC with state-of-the-art mechanisms in long and short Round Trip Time (RTT), high bandwidth network scenarios. Results show that when new security mechanism is used with TCP CUBIC, overall better performance in the form of protocol fairness, TCP friendliness, goodput, and convergence time is achieved over the network link.",
"title": "A Sustainable Solution to Support Data Security in High Bandwidth Healthcare Remote Locations by Using TCP CUBIC Mechanism",
"normalizedTitle": "A Sustainable Solution to Support Data Security in High Bandwidth Healthcare Remote Locations by Using TCP CUBIC Mechanism",
"fno": "08368259",
"hasPdf": true,
"idPrefix": "su",
"keywords": [
"Computer Facilities",
"Cryptographic Protocols",
"Health Care",
"Linux",
"Medical Computing",
"Telecommunication Congestion Control",
"Telecommunication Traffic",
"Transport Protocols",
"Round Trip Time",
"Protocol Fairness",
"Convergence Time",
"NS 2",
"Network Simulator 2",
"Packet Loss Detection",
"Loss Based TCP Congestion Control Mechanism",
"Kernel 2 6 18 TCP CUBIC",
"Sender Nodes",
"Receiver Nodes",
"Network Overload Traffic",
"Transmission Control Protocol",
"TCP Standard",
"High Bandwidth Healthcare Remote Locations",
"TCP Performance",
"Remote Healthcare Centers",
"Long Distance High Bandwidth Networks",
"TCP CUBIC Mechanism",
"TCP Friendliness",
"High Bandwidth Network Scenarios",
"Network Link",
"Trademark Congestion Control Mechanism",
"Default Congestion Control Mechanism",
"Linux Operating System",
"Healthcare Data Centers",
"Security Mechanism",
"Data Security",
"Efficiency 20 0 Percent",
"Microsoft Windows",
"Protocols",
"Linux",
"Bandwidth",
"Ciphers",
"Security",
"Congestion Control",
"Protocol Fairness",
"Goodput",
"Convergence Time",
"TCP CUBIC",
"Healthcare Centers"
],
"authors": [
{
"givenName": "Mudassar",
"surname": "Ahmad",
"fullName": "Mudassar Ahmad",
"affiliation": "Department of Computer Science, National Textile University, Faisalabad, Punjab, Pakistan",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Sohail",
"surname": "Jabbar",
"fullName": "Sohail Jabbar",
"affiliation": "CfACS IoT Lab, Department of Computing and Mathematics, Manchester Metropolitan University, Manchester",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Awais",
"surname": "Ahmad",
"fullName": "Awais Ahmad",
"affiliation": "Dipartimento di Informatica (DI), Università degli Studi di Milano Statale, Milano, MI, Italy",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Francesco",
"surname": "Piccialli",
"fullName": "Francesco Piccialli",
"affiliation": "University of Naples Federico II, Naples, Italy",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gwanggil",
"surname": "Jeon",
"fullName": "Gwanggil Jeon",
"affiliation": "Department of Embedded Systems Engineering, Incheon National University, Yeonsu-gu, South Korea",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2020-07-01 00:00:00",
"pubType": "trans",
"pages": "249-259",
"year": "2020",
"issn": "2377-3782",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icoin/2018/2290/0/08343201",
"title": "Identification of TCP congestion control algorithms with convolution neural networks",
"doi": null,
"abstractUrl": "/proceedings-article/icoin/2018/08343201/12OmNxA3YRo",
"parentPublication": {
"id": "proceedings/icoin/2018/2290/0",
"title": "2018 International Conference on Information Networking (ICOIN)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/candar/2013/2796/0/06726892",
"title": "Improving RTT Fairness on CUBIC TCP",
"doi": null,
"abstractUrl": "/proceedings-article/candar/2013/06726892/12OmNyYm2EE",
"parentPublication": {
"id": "proceedings/candar/2013/2796/0",
"title": "2013 First International Symposium on Computing and Networking - Across Practical Development and Theoretical Research (CANDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnc/2013/5287/0/06504217",
"title": "A deterministic loss model based analysis of CUBIC",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2013/06504217/12OmNyrqzo3",
"parentPublication": {
"id": "proceedings/icnc/2013/5287/0",
"title": "2013 International Conference on Computing, Networking and Communications (ICNC 2013)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnc/2018/3652/0/08390285",
"title": "Characterizing Emerging Markets: An Evaluation of TCP congestion control with real internet traffic over HTTP2",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2018/08390285/12OmNzZmZnn",
"parentPublication": {
"id": "proceedings/icnc/2018/3652/0",
"title": "2018 International Conference on Computing, Networking and Communications (ICNC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/nt/2014/04/06594906",
"title": "TCP Congestion Avoidance Algorithm Identification",
"doi": null,
"abstractUrl": "/journal/nt/2014/04/06594906/13rRUzp02ls",
"parentPublication": {
"id": "trans/nt",
"title": "IEEE/ACM Transactions on Networking",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2018/2666/1/266601a811",
"title": "Cyclic Performance Fluctuation of TCP BBR",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2018/266601a811/144U9b4EROW",
"parentPublication": {
"id": "proceedings/compsac/2018/2666/2",
"title": "2018 IEEE 42nd Annual Computer Software and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2018/6950/0/08538521",
"title": "Modest BBR: Enabling Better Fairness for BBR Congestion Control",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2018/08538521/17D45WB0qdO",
"parentPublication": {
"id": "proceedings/iscc/2018/6950/0",
"title": "2018 IEEE Symposium on Computers and Communications (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/lcnw/2017/6584/0/08110223",
"title": "Enhancement in Data-Recovery and Re-Transmit Mechanisms of TCP",
"doi": null,
"abstractUrl": "/proceedings-article/lcnw/2017/08110223/17D45WaTkct",
"parentPublication": {
"id": "proceedings/lcnw/2017/6584/0",
"title": "2017 IEEE 42nd Conference on Local Computer Networks Workshops (LCN Workshops)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2020/06/08684219",
"title": "Optimizing TCP Loss Recovery Performance Over Mobile Data Networks",
"doi": null,
"abstractUrl": "/journal/tm/2020/06/08684219/1j4G1pDysW4",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2020/7303/0/730300b139",
"title": "Mechanism of Cyclic Performance Fluctuation of TCP BBR and CUBIC TCP Communications",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2020/730300b139/1nkDi1rsoNi",
"parentPublication": {
"id": "proceedings/compsac/2020/7303/0",
"title": "2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08319950",
"articleId": "1kxWXg7b9cs",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08259031",
"articleId": "1kxWVem1Jeg",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNAQJzJb",
"title": "Nov.",
"year": "2015",
"issueNum": "11",
"idPrefix": "co",
"pubType": "magazine",
"volume": "48",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUypGGey",
"doi": "10.1109/MC.2015.332",
"abstract": "Powerful computers and advanced sensors enable precise simulations of the atmospheric state, requiring data assimilation to connect simulations to real-world sensor data using statistical mathematics and dynamical systems theory. Numerical weather prediction (NWP) thus enables simulations that more closely represent the real world. The authors explore the NWP-associated challenges in managing big data through supercomputing.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Powerful computers and advanced sensors enable precise simulations of the atmospheric state, requiring data assimilation to connect simulations to real-world sensor data using statistical mathematics and dynamical systems theory. Numerical weather prediction (NWP) thus enables simulations that more closely represent the real world. The authors explore the NWP-associated challenges in managing big data through supercomputing.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Powerful computers and advanced sensors enable precise simulations of the atmospheric state, requiring data assimilation to connect simulations to real-world sensor data using statistical mathematics and dynamical systems theory. Numerical weather prediction (NWP) thus enables simulations that more closely represent the real world. The authors explore the NWP-associated challenges in managing big data through supercomputing.",
"title": "Big Ensemble Data Assimilation in Numerical Weather Prediction",
"normalizedTitle": "Big Ensemble Data Assimilation in Numerical Weather Prediction",
"fno": "mco2015110015",
"hasPdf": true,
"idPrefix": "co",
"keywords": [
"Atmospheric Modeling",
"Computational Modeling",
"Weather Forecasting",
"Data Models",
"Predictive Models",
"Big Data",
"High Performance Computing",
"Numerical Weather Prediction",
"Data Assimilation",
"Large Ensemble",
"Big Data",
"Visualization"
],
"authors": [
{
"givenName": "Takemasa",
"surname": "Miyoshi",
"fullName": "Takemasa Miyoshi",
"affiliation": "RIKEN Advanced Institute for Computational Science, University of Maryland, and Japan Agency for Marine-Earth Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Keiichi",
"surname": "Kondo",
"fullName": "Keiichi Kondo",
"affiliation": "RIKEN Advanced Institute for Computational Science",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Koji",
"surname": "Terasaki",
"fullName": "Koji Terasaki",
"affiliation": "RIKEN Advanced Institute for Computational Science",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2015-11-01 00:00:00",
"pubType": "mags",
"pages": "15-21",
"year": "2015",
"issn": "0018-9162",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/hpcmpugc/2006/2797/0/04134070",
"title": "Characterization of High Altitude Turbulence for Air Force Platforms",
"doi": null,
"abstractUrl": "/proceedings-article/hpcmpugc/2006/04134070/12OmNAkWvba",
"parentPublication": {
"id": "proceedings/hpcmpugc/2006/2797/0",
"title": "2006 HPCMP Users Group Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2016/4273/0/07870932",
"title": "Manufacturing of weather forecasting simulations on high performance infrastructures",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2016/07870932/12OmNBTJIGH",
"parentPublication": {
"id": "proceedings/e-science/2016/4273/0",
"title": "2016 IEEE 12th International Conference on e-Science (e-Science)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcmp-ugc/2006/2797/0/27970296",
"title": "Characterization of High Altitude Turbulence for Air Force Platforms",
"doi": null,
"abstractUrl": "/proceedings-article/hpcmp-ugc/2006/27970296/12OmNBpVQ6v",
"parentPublication": {
"id": "proceedings/hpcmp-ugc/2006/2797/0",
"title": "HPCMP Users Group Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcmpugc/2006/2797/0/04134068",
"title": "Successes and Future of the Joint Weather Research and Forecasting Model Distributed Center Project",
"doi": null,
"abstractUrl": "/proceedings-article/hpcmpugc/2006/04134068/12OmNvA1hmX",
"parentPublication": {
"id": "proceedings/hpcmpugc/2006/2797/0",
"title": "2006 HPCMP Users Group Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcmp-ugc/2009/3946/0/3946a249",
"title": "Climatologies Based on the Weather Research and Forecast (WRF) Model",
"doi": null,
"abstractUrl": "/proceedings-article/hpcmp-ugc/2009/3946a249/12OmNwHyZWS",
"parentPublication": {
"id": "proceedings/hpcmp-ugc/2009/3946/0",
"title": "HPCMP Users Group Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icppw/2014/5615/0/5615a079",
"title": "Data-centric HPC for Numerical Weather Forecasting",
"doi": null,
"abstractUrl": "/proceedings-article/icppw/2014/5615a079/12OmNy3RRwk",
"parentPublication": {
"id": "proceedings/icppw/2014/5615/0",
"title": "2014 43nd International Conference on Parallel Processing Workshops (ICCPW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2018/9156/0/915600a274",
"title": "Toward a Cloud Ecosystem for Modeling as a Service",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2018/915600a274/17D45WrVfZx",
"parentPublication": {
"id": "proceedings/e-science/2018/9156/0",
"title": "2018 IEEE 14th International Conference on e-Science (e-Science)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icctech/2022/9918/0/991800a007",
"title": "Towards Global Simulated Satellite Imagery based on Next-Generation Numerical Weather Prediction Model",
"doi": null,
"abstractUrl": "/proceedings-article/icctech/2022/991800a007/1KYsWHIwSyc",
"parentPublication": {
"id": "proceedings/icctech/2022/9918/0",
"title": "2022 International Conference on Computer Technologies (ICCTech)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asonam/2019/6868/0/09072970",
"title": "Multivariate Motif Detection in Local Weather Big Data",
"doi": null,
"abstractUrl": "/proceedings-article/asonam/2019/09072970/1jjAbW6zEQ0",
"parentPublication": {
"id": "proceedings/asonam/2019/6868/0",
"title": "2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sc/2020/9998/0/999800a001",
"title": "A 1024-Member Ensemble Data Assimilation with 3.5-Km Mesh Global Weather Simulations",
"doi": null,
"abstractUrl": "/proceedings-article/sc/2020/999800a001/1oeORswZpYY",
"parentPublication": {
"id": "proceedings/sc/2020/9998/0/",
"title": "2020 SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "mco2015110012",
"articleId": "13rRUxlgxZ1",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "mco2015110023",
"articleId": "13rRUynZ5rp",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1BhzoX5mYSY",
"title": "April",
"year": "2022",
"issueNum": "04",
"idPrefix": "tg",
"pubType": "journal",
"volume": "28",
"label": "April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1ndVrOUHniw",
"doi": "10.1109/TVCG.2020.3025072",
"abstract": "Biases inevitably occur in numerical weather prediction (NWP) due to an idealized numerical assumption for modeling chaotic atmospheric systems. Therefore, the rapid and accurate identification and calibration of biases is crucial for NWP in weather forecasting. Conventional approaches, such as various analog post-processing forecast methods, have been designed to aid in bias calibration. However, these approaches fail to consider the spatiotemporal correlations of forecast bias, which can considerably affect calibration efficacy. In this article, we propose a novel bias pattern extraction approach based on forecasting-observation probability density by merging historical forecasting and observation datasets. Given a spatiotemporal scope, our approach extracts and fuses bias patterns and automatically divides regions with similar bias patterns. Termed <italic>BicaVis</italic>, our spatiotemporal bias pattern visual analytics system is proposed to assist experts in drafting calibration curves on the basis of these bias patterns. To verify the effectiveness of our approach, we conduct two case studies with real-world reanalysis datasets. The feedback collected from domain experts confirms the efficacy of our approach.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Biases inevitably occur in numerical weather prediction (NWP) due to an idealized numerical assumption for modeling chaotic atmospheric systems. Therefore, the rapid and accurate identification and calibration of biases is crucial for NWP in weather forecasting. Conventional approaches, such as various analog post-processing forecast methods, have been designed to aid in bias calibration. However, these approaches fail to consider the spatiotemporal correlations of forecast bias, which can considerably affect calibration efficacy. In this article, we propose a novel bias pattern extraction approach based on forecasting-observation probability density by merging historical forecasting and observation datasets. Given a spatiotemporal scope, our approach extracts and fuses bias patterns and automatically divides regions with similar bias patterns. Termed <italic>BicaVis</italic>, our spatiotemporal bias pattern visual analytics system is proposed to assist experts in drafting calibration curves on the basis of these bias patterns. To verify the effectiveness of our approach, we conduct two case studies with real-world reanalysis datasets. The feedback collected from domain experts confirms the efficacy of our approach.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Biases inevitably occur in numerical weather prediction (NWP) due to an idealized numerical assumption for modeling chaotic atmospheric systems. Therefore, the rapid and accurate identification and calibration of biases is crucial for NWP in weather forecasting. Conventional approaches, such as various analog post-processing forecast methods, have been designed to aid in bias calibration. However, these approaches fail to consider the spatiotemporal correlations of forecast bias, which can considerably affect calibration efficacy. In this article, we propose a novel bias pattern extraction approach based on forecasting-observation probability density by merging historical forecasting and observation datasets. Given a spatiotemporal scope, our approach extracts and fuses bias patterns and automatically divides regions with similar bias patterns. Termed BicaVis, our spatiotemporal bias pattern visual analytics system is proposed to assist experts in drafting calibration curves on the basis of these bias patterns. To verify the effectiveness of our approach, we conduct two case studies with real-world reanalysis datasets. The feedback collected from domain experts confirms the efficacy of our approach.",
"title": "A Probability Density-Based Visual Analytics Approach to Forecast Bias Calibration",
"normalizedTitle": "A Probability Density-Based Visual Analytics Approach to Forecast Bias Calibration",
"fno": "09200793",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Atmospheric Techniques",
"Calibration",
"Data Analysis",
"Data Visualisation",
"Probability",
"Weather Forecasting",
"Spatiotemporal Scope",
"Approach Extracts",
"Fuses Bias Patterns",
"Similar Bias Patterns",
"Spatiotemporal Bias Pattern Visual Analytics System",
"Calibration Curves",
"Probability Density Based Visual Analytics Approach",
"Forecast Bias Calibration",
"Numerical Weather Prediction",
"NWP",
"Idealized Numerical Assumption",
"Chaotic Atmospheric Systems",
"Weather Forecasting",
"Analog Post Processing Forecast Methods",
"Spatiotemporal Correlations",
"Calibration Efficacy",
"Bias Pattern Extraction Approach",
"Forecasting Observation Probability Density",
"Historical Forecasting",
"Observation Datasets",
"Weather Forecasting",
"Calibration",
"Data Visualization",
"Spatiotemporal Phenomena",
"Atmospheric Modeling",
"Uncertainty",
"Weather Forecast",
"Pattern Extraction",
"Calibration",
"Visual Analytics"
],
"authors": [
{
"givenName": "Renpei",
"surname": "Huang",
"fullName": "Renpei Huang",
"affiliation": "School of Software, BNRIST, Tsinghua University, Beijing, P. R. China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Quan",
"surname": "Li",
"fullName": "Quan Li",
"affiliation": "WeBank, AI Group, Shenzhen, Guangdong, P. R. China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Li",
"surname": "Chen",
"fullName": "Li Chen",
"affiliation": "School of Software, BNRIST, Tsinghua University, Beijing, P. R. China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiaoru",
"surname": "Yuan",
"fullName": "Xiaoru Yuan",
"affiliation": "Key Laboratory of Machine Perception (Ministry of Education), and National Engineering Laboratory for Big Data Analysis and Application, Peking University, Beijing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2022-04-01 00:00:00",
"pubType": "trans",
"pages": "1732-1744",
"year": "2022",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cloudcom/2014/4093/0/4093a326",
"title": "Big Data Processing for Prediction of Traffic Time Based on Vertical Data Arrangement",
"doi": null,
"abstractUrl": "/proceedings-article/cloudcom/2014/4093a326/12OmNAkWvva",
"parentPublication": {
"id": "proceedings/cloudcom/2014/4093/0",
"title": "2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2015/9504/0/9504b021",
"title": "A Hierarchical Pattern Learning Framework for Forecasting Extreme Weather Events",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2015/9504b021/12OmNCfjeBb",
"parentPublication": {
"id": "proceedings/icdm/2015/9504/0",
"title": "2015 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2013/3142/0/3143a994",
"title": "Severe Hail Prediction within a Spatiotemporal Relational Data Mining Framework",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2013/3143a994/12OmNzZWbJ9",
"parentPublication": {
"id": "proceedings/icdmw/2013/3142/0",
"title": "2013 IEEE 13th International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icisce/2018/5500/0/550000a241",
"title": "Graph Attention LSTM Network: A New Model for Traffic Flow Forecasting",
"doi": null,
"abstractUrl": "/proceedings-article/icisce/2018/550000a241/17D45WK5Apt",
"parentPublication": {
"id": "proceedings/icisce/2018/5500/0",
"title": "2018 5th International Conference on Information Science and Control Engineering (ICISCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fskd/2009/3735/3/05358957",
"title": "Combination Forecasting of Fuzzy Forecast",
"doi": null,
"abstractUrl": "/proceedings-article/fskd/2009/05358957/17D45XeKgog",
"parentPublication": {
"id": "proceedings/fskd/2009/3735/3",
"title": "2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2009)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/05/09709128",
"title": "Semi-Supervised Air Quality Forecasting via Self-Supervised Hierarchical Graph Neural Network",
"doi": null,
"abstractUrl": "/journal/tk/2023/05/09709128/1AR0rfr1x84",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09837455",
"title": "CityNeuro: Towards Location and Time Prediction for Urban Abnormal Events",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09837455/1FdICjrjPgs",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2022/5099/0/509900b257",
"title": "Spatiotemporal Contextual Consistency Network for Precipitation Nowcasting",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2022/509900b257/1KpCnuzoddS",
"parentPublication": {
"id": "proceedings/icdm/2022/5099/0",
"title": "2022 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/08/09242313",
"title": "Foresee Urban Sparse Traffic Accidents: A Spatiotemporal Multi-Granularity Perspective",
"doi": null,
"abstractUrl": "/journal/tk/2022/08/09242313/1oijolExBNS",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ex/2022/01/09453192",
"title": "Robust Precipitation Bias Correction Through an Ordinal Distribution Autoencoder",
"doi": null,
"abstractUrl": "/magazine/ex/2022/01/09453192/1ulCBhHPV3G",
"parentPublication": {
"id": "mags/ex",
"title": "IEEE Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09721816",
"articleId": "1BhzDSfcFu8",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09210559",
"articleId": "1nzvbfAG62s",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1Bhzwq3YVva",
"name": "ttg202204-09200793s1-supp1-3025072.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202204-09200793s1-supp1-3025072.mp4",
"extension": "mp4",
"size": "164 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNAolH1h",
"title": "July",
"year": "2020",
"issueNum": "07",
"idPrefix": "tg",
"pubType": "journal",
"volume": "26",
"label": "July",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "17D45Vw15wQ",
"doi": "10.1109/TVCG.2018.2889470",
"abstract": "Successfully detecting, analyzing, and reasoning about collective anomalies is important for many real-life application domains (e.g., intrusion detection, fraud analysis, software security). The primary challenges to achieving this goal include the overwhelming number of low-risk events and their multimodal relationships, the diversity of collective anomalies by various data and anomaly types, and the difficulty in incorporating the domain knowledge of experts. In this paper, we propose the novel concept of the faceted High-Order Correlation Graph (HOCG). Compared with previous, low-order correlation graphs, HOCG achieves better user interactivity, computational scalability, and domain generality through synthesizing heterogeneous types of objects, their anomalies, and the multimodal relationships, all in a single graph. We design elaborate visual metaphors, interaction models, and the coordinated multiple view based interface to allow users to fully unleash the visual analytics power of the HOCG. We conduct case studies for three application domains and collect feedback from domain experts who apply our method to these scenarios. The results demonstrate the effectiveness of the HOCG in the overview of point anomalies, the detection of collective anomalies, and the reasoning process of root cause analyses.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Successfully detecting, analyzing, and reasoning about collective anomalies is important for many real-life application domains (e.g., intrusion detection, fraud analysis, software security). The primary challenges to achieving this goal include the overwhelming number of low-risk events and their multimodal relationships, the diversity of collective anomalies by various data and anomaly types, and the difficulty in incorporating the domain knowledge of experts. In this paper, we propose the novel concept of the faceted High-Order Correlation Graph (HOCG). Compared with previous, low-order correlation graphs, HOCG achieves better user interactivity, computational scalability, and domain generality through synthesizing heterogeneous types of objects, their anomalies, and the multimodal relationships, all in a single graph. We design elaborate visual metaphors, interaction models, and the coordinated multiple view based interface to allow users to fully unleash the visual analytics power of the HOCG. We conduct case studies for three application domains and collect feedback from domain experts who apply our method to these scenarios. The results demonstrate the effectiveness of the HOCG in the overview of point anomalies, the detection of collective anomalies, and the reasoning process of root cause analyses.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Successfully detecting, analyzing, and reasoning about collective anomalies is important for many real-life application domains (e.g., intrusion detection, fraud analysis, software security). The primary challenges to achieving this goal include the overwhelming number of low-risk events and their multimodal relationships, the diversity of collective anomalies by various data and anomaly types, and the difficulty in incorporating the domain knowledge of experts. In this paper, we propose the novel concept of the faceted High-Order Correlation Graph (HOCG). Compared with previous, low-order correlation graphs, HOCG achieves better user interactivity, computational scalability, and domain generality through synthesizing heterogeneous types of objects, their anomalies, and the multimodal relationships, all in a single graph. We design elaborate visual metaphors, interaction models, and the coordinated multiple view based interface to allow users to fully unleash the visual analytics power of the HOCG. We conduct case studies for three application domains and collect feedback from domain experts who apply our method to these scenarios. The results demonstrate the effectiveness of the HOCG in the overview of point anomalies, the detection of collective anomalies, and the reasoning process of root cause analyses.",
"title": "Visual Analysis of Collective Anomalies Using Faceted High-Order Correlation Graphs",
"normalizedTitle": "Visual Analysis of Collective Anomalies Using Faceted High-Order Correlation Graphs",
"fno": "08587186",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Fraud",
"Graph Theory",
"Inference Mechanisms",
"Security Of Data",
"HOCG",
"Point Anomalies",
"Collective Anomalies",
"Visual Analysis",
"Real Life Application Domains",
"Intrusion Detection",
"Fraud Analysis",
"Low Risk Events",
"Multimodal Relationships",
"Anomaly Types",
"High Order Correlation Graph",
"Previous Order Correlation Graphs",
"Low Order Correlation Graphs",
"Domain Generality",
"Single Graph",
"Domain Experts",
"Faceted High Order Correlation Graphs",
"Anomaly Detection",
"Correlation",
"Visual Analytics",
"Data Visualization",
"Software",
"Feature Extraction",
"Correlation Graph Visualization",
"Collective Anomaly"
],
"authors": [
{
"givenName": "Jia",
"surname": "Yan",
"fullName": "Jia Yan",
"affiliation": "TCA/SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Lei",
"surname": "Shi",
"fullName": "Lei Shi",
"affiliation": "School of Computer Science, Beihang University, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jun",
"surname": "Tao",
"fullName": "Jun Tao",
"affiliation": "Department of Computer Science & Engineering, University of Notre Dame, Notre Dame, IN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiaolong",
"surname": "Yu",
"fullName": "Xiaolong Yu",
"affiliation": "School of Computer Science, Fudan University, Shanghai, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zhou",
"surname": "Zhuang",
"fullName": "Zhou Zhuang",
"affiliation": "School of Computer Science, Fudan University, Shanghai, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Congcong",
"surname": "Huang",
"fullName": "Congcong Huang",
"affiliation": "SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Rulei",
"surname": "Yu",
"fullName": "Rulei Yu",
"affiliation": "SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Purui",
"surname": "Su",
"fullName": "Purui Su",
"affiliation": "TCA/SKLCS, Institute of Software, Chinese Academy of Sciences, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Chaoli",
"surname": "Wang",
"fullName": "Chaoli Wang",
"affiliation": "Department of Computer Science & Engineering, University of Notre Dame, Notre Dame, IN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yang",
"surname": "Chen",
"fullName": "Yang Chen",
"affiliation": "School of Computer Science, Fudan University, Shanghai, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "07",
"pubDate": "2020-07-01 00:00:00",
"pubType": "trans",
"pages": "2517-2534",
"year": "2020",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/big-data/2016/9005/0/07840677",
"title": "TelcoFlow: Visual exploration of collective behaviors based on telco data",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2016/07840677/12OmNBtCCyS",
"parentPublication": {
"id": "proceedings/big-data/2016/9005/0",
"title": "2016 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/edcc/2012/4671/0/4671a212",
"title": "Applying Data Mining for Detecting Anomalies in Satellites",
"doi": null,
"abstractUrl": "/proceedings-article/edcc/2012/4671a212/12OmNvSbBNH",
"parentPublication": {
"id": "proceedings/edcc/2012/4671/0",
"title": "European Dependable Computing Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2018/1424/0/142401a150",
"title": "Visual Analysis of Collective Anomalies Through High-Order Correlation Graph",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2018/142401a150/12OmNym2c5B",
"parentPublication": {
"id": "proceedings/pacificvis/2018/1424/0",
"title": "2018 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2011/4408/0/4408a527",
"title": "Detection of Cross-Channel Anomalies from Multiple Data Channels",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2011/4408a527/12OmNyoAA7d",
"parentPublication": {
"id": "proceedings/icdm/2011/4408/0",
"title": "2011 IEEE 11th International Conference on Data Mining",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2017/2715/0/08258192",
"title": "Online mining for association rules and collective anomalies in data streams",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2017/08258192/17D45W2WyyI",
"parentPublication": {
"id": "proceedings/big-data/2017/2715/0",
"title": "2017 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440040",
"title": "A Visual Analytics Framework for Spatiotemporal Trade Network Analysis",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440040/17D45WHONjL",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/05/09740038",
"title": "CSCAD: Correlation Structure-Based Collective Anomaly Detection in Complex System",
"doi": null,
"abstractUrl": "/journal/tk/2023/05/09740038/1BWZdToFUVW",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2020/1331/0/09102889",
"title": "Statistical Detection Of Collective Data Fraud",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2020/09102889/1kwqPpJuVvq",
"parentPublication": {
"id": "proceedings/icme/2020/1331/0",
"title": "2020 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2020/6251/0/09378419",
"title": "Failure Prediction in Datacenters Using Unsupervised Multimodal Anomaly Detection",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2020/09378419/1s645Gy8EDe",
"parentPublication": {
"id": "proceedings/big-data/2020/6251/0",
"title": "2020 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csci/2020/7624/0/762400a598",
"title": "Collective Anomaly Detection for Multivariate Data using Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/csci/2020/762400a598/1uGYtR0xPvq",
"parentPublication": {
"id": "proceedings/csci/2020/7624/0",
"title": "2020 International Conference on Computational Science and Computational Intelligence (CSCI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08585048",
"articleId": "17D45XoXP6a",
"__typename": "AdjacentArticleType"
},
"next": null,
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1kcw5DJAn2o",
"name": "ttg202007-08587186s1-hocg_tvcg_final.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202007-08587186s1-hocg_tvcg_final.mp4",
"extension": "mp4",
"size": "39.4 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1MTOUEFAeT6",
"title": "June",
"year": "2023",
"issueNum": "06",
"idPrefix": "tp",
"pubType": "journal",
"volume": "45",
"label": "June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1IHMNRyHTMs",
"doi": "10.1109/TPAMI.2022.3225476",
"abstract": "Anomaly detection has wide applications in machine intelligence but is still a difficult unsolved problem. Major challenges include the rarity of labeled anomalies and it is a class highly imbalanced problem. Traditional unsupervised anomaly detectors are suboptimal while supervised models can easily make biased predictions towards normal data. In this paper, we present a new supervised anomaly detector through introducing the novel Ensemble Active Learning Generative Adversarial Network (EAL-GAN). EAL-GAN is a conditional GAN having a unique one generator <italic>versus</italic> multiple discriminators architecture where anomaly detection is implemented by an auxiliary classifier of the discriminator. In addition to using the conditional GAN to generate class balanced supplementary training data, an innovative ensemble learning loss function ensuring each discriminator makes up for the deficiencies of the others is designed to overcome the class imbalanced problem, and an active learning algorithm is introduced to significantly reduce the cost of labeling real-world data. We present extensive experimental results to demonstrate that the new anomaly detector consistently outperforms a variety of SOTA methods by significant margins.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Anomaly detection has wide applications in machine intelligence but is still a difficult unsolved problem. Major challenges include the rarity of labeled anomalies and it is a class highly imbalanced problem. Traditional unsupervised anomaly detectors are suboptimal while supervised models can easily make biased predictions towards normal data. In this paper, we present a new supervised anomaly detector through introducing the novel Ensemble Active Learning Generative Adversarial Network (EAL-GAN). EAL-GAN is a conditional GAN having a unique one generator <italic>versus</italic> multiple discriminators architecture where anomaly detection is implemented by an auxiliary classifier of the discriminator. In addition to using the conditional GAN to generate class balanced supplementary training data, an innovative ensemble learning loss function ensuring each discriminator makes up for the deficiencies of the others is designed to overcome the class imbalanced problem, and an active learning algorithm is introduced to significantly reduce the cost of labeling real-world data. We present extensive experimental results to demonstrate that the new anomaly detector consistently outperforms a variety of SOTA methods by significant margins.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Anomaly detection has wide applications in machine intelligence but is still a difficult unsolved problem. Major challenges include the rarity of labeled anomalies and it is a class highly imbalanced problem. Traditional unsupervised anomaly detectors are suboptimal while supervised models can easily make biased predictions towards normal data. In this paper, we present a new supervised anomaly detector through introducing the novel Ensemble Active Learning Generative Adversarial Network (EAL-GAN). EAL-GAN is a conditional GAN having a unique one generator versus multiple discriminators architecture where anomaly detection is implemented by an auxiliary classifier of the discriminator. In addition to using the conditional GAN to generate class balanced supplementary training data, an innovative ensemble learning loss function ensuring each discriminator makes up for the deficiencies of the others is designed to overcome the class imbalanced problem, and an active learning algorithm is introduced to significantly reduce the cost of labeling real-world data. We present extensive experimental results to demonstrate that the new anomaly detector consistently outperforms a variety of SOTA methods by significant margins.",
"title": "Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning",
"normalizedTitle": "Supervised Anomaly Detection via Conditional Generative Adversarial Network and Ensemble Active Learning",
"fno": "09965739",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Detectors",
"Anomaly Detection",
"Generative Adversarial Networks",
"Ensemble Learning",
"Training",
"Generators",
"Task Analysis",
"Anomaly Detection",
"Conditional Generative Adversarial Network",
"Deep Learning",
"Ensemble Active Learning",
"Ensemble Of Anomaly Detectors",
"Outlier Detection"
],
"authors": [
{
"givenName": "Zhi",
"surname": "Chen",
"fullName": "Zhi Chen",
"affiliation": "Blockchain Research Center of China, School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu, Sichuan, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jiang",
"surname": "Duan",
"fullName": "Jiang Duan",
"affiliation": "Blockchain Research Center of China, School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu, Sichuan, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Li",
"surname": "Kang",
"fullName": "Li Kang",
"affiliation": "Blockchain Research Center of China, School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu, Sichuan, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Guoping",
"surname": "Qiu",
"fullName": "Guoping Qiu",
"affiliation": "College of Electronics and Information Engineering, Guangdong Key Lab for Intelligent Information Processing, Shenzhen Institute of Artificial intelligence and Robotics for Society, Shenzhen University, Shenzhen, Guangdong Province, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2023-06-01 00:00:00",
"pubType": "trans",
"pages": "7781-7798",
"year": "2023",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/2018/6420/0/642000i513",
"title": "Multi-agent Diverse Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000i513/17D45WXIkDV",
"parentPublication": {
"id": "proceedings/cvpr/2018/6420/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08546039",
"title": "3D Convolutional Generative Adversarial Networks for Detecting Temporal Irregularities in Videos",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08546039/17D45X7VTeW",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08545381",
"title": "Anomaly Detection via Minimum Likelihood Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08545381/17D45XcttmW",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2021/3902/0/09671994",
"title": "Anomaly detection of high-dimensional sparse data based on Ensemble Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2021/09671994/1A8hbtEBZS0",
"parentPublication": {
"id": "proceedings/big-data/2021/3902/0",
"title": "2021 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200o4418",
"title": "Dual Projection Generative Adversarial Networks for Conditional Image Generation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200o4418/1BmIOa3DnTq",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csde/2021/9552/0/09718461",
"title": "A Conditional Generative Adversarial Network for Non-rigid Point Set Registration",
"doi": null,
"abstractUrl": "/proceedings-article/csde/2021/09718461/1BogMWGWQUg",
"parentPublication": {
"id": "proceedings/csde/2021/9552/0",
"title": "2021 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2019/4896/0/489600b047",
"title": "Anomaly Detection in Time Series using Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2019/489600b047/1gAwYGpiiB2",
"parentPublication": {
"id": "proceedings/icdmw/2019/4896/0",
"title": "2019 International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csci/2020/7624/0/762400a598",
"title": "Collective Anomaly Detection for Multivariate Data using Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/csci/2020/762400a598/1uGYtR0xPvq",
"parentPublication": {
"id": "proceedings/csci/2020/7624/0",
"title": "2020 International Conference on Computational Science and Computational Intelligence (CSCI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/04/09626552",
"title": "DCT-GAN: Dilated Convolutional Transformer-Based GAN for Time Series Anomaly Detection",
"doi": null,
"abstractUrl": "/journal/tk/2023/04/09626552/1yNcV2zDN5e",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/12/09613799",
"title": "Triple Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/journal/tp/2022/12/09613799/1ythZwwBN2E",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09962797",
"articleId": "1IxvT5j9TeU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09944190",
"articleId": "1Ia7erwDC48",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvqEvRo",
"title": "PrePrints",
"year": "5555",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": null,
"label": "PrePrints",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1D6qPjvIP16",
"doi": "10.1109/TVCG.2022.3171074",
"abstract": "In domains such as agronomy or manufacturing, experts need to consider trade-offs when making decisions that involve several, often competing, objectives. Such analysis is complex and may be conducted over long periods of time, making it hard to revisit. In this paper, we consider the use of analytic provenance mechanisms to aid experts recall and keep track of trade-off analysis. We implemented VisProm, a web-based trade-off analysis system, that incorporates in-visualization provenance views, designed to help experts keep track of trade-offs and their objectives. We used VisProm as a technology probe to understand user needs and explore the potential role of provenance in this context. Through observation sessions with three groups of experts analyzing their own data, we make the following contributions. We first, identify eight high-level tasks that experts engaged in during trade-off analysis, such as locating and characterizing interest zones in the trade-off space, and show how these tasks can be supported by provenance visualization. Second, we refine findings from previous work on provenance purposes such as recall and reproduce, by identifying specific objects of these purposes related to trade-off analysis, such as interest zones, and exploration structure (e.g., exploration of alternatives and branches). Third, we discuss insights on how the identified provenance objects and our designs support these trade-off analysis tasks, both when revisiting past analysis and while actively exploring. And finally, we identify new opportunities for provenance-driven trade-off analysis, for example related to monitoring the coverage of the trade-off space, and tracking alternative trade-off scenarios.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In domains such as agronomy or manufacturing, experts need to consider trade-offs when making decisions that involve several, often competing, objectives. Such analysis is complex and may be conducted over long periods of time, making it hard to revisit. In this paper, we consider the use of analytic provenance mechanisms to aid experts recall and keep track of trade-off analysis. We implemented VisProm, a web-based trade-off analysis system, that incorporates in-visualization provenance views, designed to help experts keep track of trade-offs and their objectives. We used VisProm as a technology probe to understand user needs and explore the potential role of provenance in this context. Through observation sessions with three groups of experts analyzing their own data, we make the following contributions. We first, identify eight high-level tasks that experts engaged in during trade-off analysis, such as locating and characterizing interest zones in the trade-off space, and show how these tasks can be supported by provenance visualization. Second, we refine findings from previous work on provenance purposes such as recall and reproduce, by identifying specific objects of these purposes related to trade-off analysis, such as interest zones, and exploration structure (e.g., exploration of alternatives and branches). Third, we discuss insights on how the identified provenance objects and our designs support these trade-off analysis tasks, both when revisiting past analysis and while actively exploring. And finally, we identify new opportunities for provenance-driven trade-off analysis, for example related to monitoring the coverage of the trade-off space, and tracking alternative trade-off scenarios.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In domains such as agronomy or manufacturing, experts need to consider trade-offs when making decisions that involve several, often competing, objectives. Such analysis is complex and may be conducted over long periods of time, making it hard to revisit. In this paper, we consider the use of analytic provenance mechanisms to aid experts recall and keep track of trade-off analysis. We implemented VisProm, a web-based trade-off analysis system, that incorporates in-visualization provenance views, designed to help experts keep track of trade-offs and their objectives. We used VisProm as a technology probe to understand user needs and explore the potential role of provenance in this context. Through observation sessions with three groups of experts analyzing their own data, we make the following contributions. We first, identify eight high-level tasks that experts engaged in during trade-off analysis, such as locating and characterizing interest zones in the trade-off space, and show how these tasks can be supported by provenance visualization. Second, we refine findings from previous work on provenance purposes such as recall and reproduce, by identifying specific objects of these purposes related to trade-off analysis, such as interest zones, and exploration structure (e.g., exploration of alternatives and branches). Third, we discuss insights on how the identified provenance objects and our designs support these trade-off analysis tasks, both when revisiting past analysis and while actively exploring. And finally, we identify new opportunities for provenance-driven trade-off analysis, for example related to monitoring the coverage of the trade-off space, and tracking alternative trade-off scenarios.",
"title": "Understanding How In-Visualization Provenance Can Support Trade-off Analysis",
"normalizedTitle": "Understanding How In-Visualization Provenance Can Support Trade-off Analysis",
"fno": "09768153",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Task Analysis",
"Data Visualization",
"History",
"Decision Making",
"Probes",
"Optimization",
"Object Recognition",
"Provenance",
"Visualization",
"Trade Offs",
"Multi Criteria",
"Decision Making",
"Qualitative Study"
],
"authors": [
{
"givenName": "Mehdi Rafik",
"surname": "Chakhchoukh",
"fullName": "Mehdi Rafik Chakhchoukh",
"affiliation": "LISN, Universit Paris-Saclay, 27048 Gif-sur-Yvette, Ile-de-France, France, 91190",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nadia",
"surname": "Boukhelifa",
"fullName": "Nadia Boukhelifa",
"affiliation": "CEPIA, INRA, 27057 Paris, Ile-de-france, France, 75338",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Anastasia",
"surname": "Bezerianos",
"fullName": "Anastasia Bezerianos",
"affiliation": "LRI-Laboratoire de Recherche en Informatique, Universite Paris-Sud, Paris, orsay, France, 91405",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-05-01 00:00:00",
"pubType": "trans",
"pages": "1-1",
"year": "5555",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iccima/2001/1312/0/13120133",
"title": "Exploration and Exploitation Trade-Off in Multiagent Learning",
"doi": null,
"abstractUrl": "/proceedings-article/iccima/2001/13120133/12OmNAS9zuy",
"parentPublication": {
"id": "proceedings/iccima/2001/1312/0",
"title": "Computational Intelligence and Multimedia Applications, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isspit/2017/4662/0/08388644",
"title": "A standard decision format using provenance",
"doi": null,
"abstractUrl": "/proceedings-article/isspit/2017/08388644/12OmNvFHfHY",
"parentPublication": {
"id": "proceedings/isspit/2017/4662/0",
"title": "2017 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccad/2003/762/0/01257852",
"title": "A trade-off Oriented placement tool",
"doi": null,
"abstractUrl": "/proceedings-article/iccad/2003/01257852/12OmNwEJ0SM",
"parentPublication": {
"id": "proceedings/iccad/2003/762/0",
"title": "ICCAD-2003. International Conference on Computer Aided Design",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2008/3075/0/04439098",
"title": "Measuring Data Believability: A Provenance Approach",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2008/04439098/12OmNxcMSgM",
"parentPublication": {
"id": "proceedings/hicss/2008/3075/0",
"title": "Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/igcc/2012/2155/0/IEEECol",
"title": "Optimal energy trade-off schedules",
"doi": null,
"abstractUrl": "/proceedings-article/igcc/2012/IEEECol/12OmNyrIaKN",
"parentPublication": {
"id": "proceedings/igcc/2012/2155/0",
"title": "2012 International Green Computing Conference (IGCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/kbse/1996/7680/0/76800144",
"title": "Software Synthesis for Trade-off Design",
"doi": null,
"abstractUrl": "/proceedings-article/kbse/1996/76800144/12OmNz6iOkc",
"parentPublication": {
"id": "proceedings/kbse/1996/7680/0",
"title": "Knowledge-Based Software Engineering Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/sc/2017/04/07327204",
"title": "Self-Adaptive Trade-off Decision Making for Autoscaling Cloud-Based Services",
"doi": null,
"abstractUrl": "/journal/sc/2017/04/07327204/13rRUxDqS5M",
"parentPublication": {
"id": "trans/sc",
"title": "IEEE Transactions on Services Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903572",
"title": "The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903572/1GZonS2SkKs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2019/06/08788592",
"title": "Analytic Provenance in Practice: The Role of Provenance in Real-World Visualization and Data Analysis Environments",
"doi": null,
"abstractUrl": "/magazine/cg/2019/06/08788592/1cfqCMPtgRy",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2021/9184/0/918400c713",
"title": "PITA: Privacy Through Provenance Abstraction",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2021/918400c713/1uGXoWOC8zS",
"parentPublication": {
"id": "proceedings/icde/2021/9184/0",
"title": "2021 IEEE 37th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09767765",
"articleId": "1D4MJudYK3u",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09769931",
"articleId": "1D8asOXVetq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1D8arLUWsoM",
"name": "ttg555501-09768153s1-tvcg-3171074-mm.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg555501-09768153s1-tvcg-3171074-mm.zip",
"extension": "zip",
"size": "115 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNCcKQnG",
"title": "Sept.",
"year": "2016",
"issueNum": "09",
"idPrefix": "tm",
"pubType": "journal",
"volume": "15",
"label": "Sept.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxcbnHU",
"doi": "10.1109/TMC.2015.2489202",
"abstract": "The web browser is one of the most significant applications on mobile devices such as smartphones. However, the user experience of mobile web browsing is undesirable because of the slow resource loading. To improve the performance of web resource loading, client-side cache has been adopted as a key mechanism. However, the existing passive measurement studies cannot comprehensively characterize the “client-side” cache performance of mobile web browsing. For example, most of these studies mainly focus on client-side implementations but not server-side configurations, suffer from biased user behaviors, and fail to study “miscached” resources. To address these issues, in this article, we present a proactive approach to making a comprehensive measurement study on client-side cache performance. The key idea of our approach is to proactively crawl resources from hundreds of websites periodically with a fine-grained time interval. Thus, we are able to uncover the resource update history and cache configurations at the server side, and analyze the cache performance in various time granularities. Based on our collected data, we build a new cache analysis model and study the upper bound of how high percentage of resources could potentially be cached and how effectively the caching works in practice. We report detailed analysis results of different websites and various types of web resources, and identify the problems caused by unsatisfactory cache performance. In particular, we identify two major problems— Redundant Transfer and Miscached Resource, which lead to unsatisfactory cache performance. We investigate three main root causes: Same Content , Heuristic Expiration, and Conservative Expiration Time, and discuss what mobile web developers can do to mitigate those problems.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The web browser is one of the most significant applications on mobile devices such as smartphones. However, the user experience of mobile web browsing is undesirable because of the slow resource loading. To improve the performance of web resource loading, client-side cache has been adopted as a key mechanism. However, the existing passive measurement studies cannot comprehensively characterize the “client-side” cache performance of mobile web browsing. For example, most of these studies mainly focus on client-side implementations but not server-side configurations, suffer from biased user behaviors, and fail to study “miscached” resources. To address these issues, in this article, we present a proactive approach to making a comprehensive measurement study on client-side cache performance. The key idea of our approach is to proactively crawl resources from hundreds of websites periodically with a fine-grained time interval. Thus, we are able to uncover the resource update history and cache configurations at the server side, and analyze the cache performance in various time granularities. Based on our collected data, we build a new cache analysis model and study the upper bound of how high percentage of resources could potentially be cached and how effectively the caching works in practice. We report detailed analysis results of different websites and various types of web resources, and identify the problems caused by unsatisfactory cache performance. In particular, we identify two major problems— Redundant Transfer and Miscached Resource, which lead to unsatisfactory cache performance. We investigate three main root causes: Same Content , Heuristic Expiration, and Conservative Expiration Time, and discuss what mobile web developers can do to mitigate those problems.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The web browser is one of the most significant applications on mobile devices such as smartphones. However, the user experience of mobile web browsing is undesirable because of the slow resource loading. To improve the performance of web resource loading, client-side cache has been adopted as a key mechanism. However, the existing passive measurement studies cannot comprehensively characterize the “client-side” cache performance of mobile web browsing. For example, most of these studies mainly focus on client-side implementations but not server-side configurations, suffer from biased user behaviors, and fail to study “miscached” resources. To address these issues, in this article, we present a proactive approach to making a comprehensive measurement study on client-side cache performance. The key idea of our approach is to proactively crawl resources from hundreds of websites periodically with a fine-grained time interval. Thus, we are able to uncover the resource update history and cache configurations at the server side, and analyze the cache performance in various time granularities. Based on our collected data, we build a new cache analysis model and study the upper bound of how high percentage of resources could potentially be cached and how effectively the caching works in practice. We report detailed analysis results of different websites and various types of web resources, and identify the problems caused by unsatisfactory cache performance. In particular, we identify two major problems— Redundant Transfer and Miscached Resource, which lead to unsatisfactory cache performance. We investigate three main root causes: Same Content , Heuristic Expiration, and Conservative Expiration Time, and discuss what mobile web developers can do to mitigate those problems.",
"title": "Demystifying the Imperfect Client-Side Cache Performance of Mobile Web Browsing",
"normalizedTitle": "Demystifying the Imperfect Client-Side Cache Performance of Mobile Web Browsing",
"fno": "07295636",
"hasPdf": true,
"idPrefix": "tm",
"keywords": [
"Browsers",
"Mobile Communication",
"Servers",
"History",
"Mobile Computing",
"Uniform Resource Locators",
"Loading",
"Measurement",
"Mobile Web",
"Cache"
],
"authors": [
{
"givenName": "Xuanzhe",
"surname": "Liu",
"fullName": "Xuanzhe Liu",
"affiliation": "Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yun",
"surname": "Ma",
"fullName": "Yun Ma",
"affiliation": "Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yunxin",
"surname": "Liu",
"fullName": "Yunxin Liu",
"affiliation": "Microsoft Research, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tao",
"surname": "Xie",
"fullName": "Tao Xie",
"affiliation": "University of Illinois at Urbana-Champaign, Urbana, IL",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gang",
"surname": "Huang",
"fullName": "Gang Huang",
"affiliation": "Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "09",
"pubDate": "2016-09-01 00:00:00",
"pubType": "trans",
"pages": "2206-2220",
"year": "2016",
"issn": "1536-1233",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icycs/2008/3398/0/04709194",
"title": "Collecting Internet Malware Based on Client-side Honeypot",
"doi": null,
"abstractUrl": "/proceedings-article/icycs/2008/04709194/12OmNBSBkeV",
"parentPublication": {
"id": "proceedings/icycs/2008/3398/0",
"title": "2008 9th International Conference for Young Computer Scientists",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdcs/2018/6871/0/687101b347",
"title": "Rethinking Resource Management in Mobile Web: Measurement, Deployment, and Runtime",
"doi": null,
"abstractUrl": "/proceedings-article/icdcs/2018/687101b347/12OmNCd2rJC",
"parentPublication": {
"id": "proceedings/icdcs/2018/6871/0",
"title": "2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdcs/2016/1483/0/1483a777",
"title": "Real-Time Client-Side Phishing Prevention Add-On",
"doi": null,
"abstractUrl": "/proceedings-article/icdcs/2016/1483a777/12OmNvqEvJ2",
"parentPublication": {
"id": "proceedings/icdcs/2016/1483/0",
"title": "2016 IEEE 36th International Conference on Distributed Computing Systems (ICDCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2015/7082/0/07177455",
"title": "A case for application-managed cache for browser",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2015/07177455/12OmNwNwzLR",
"parentPublication": {
"id": "proceedings/icme/2015/7082/0",
"title": "2015 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2009/3807/0/05069437",
"title": "Neuro-fuzzy system in web client-side caching",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2009/05069437/12OmNx19k0b",
"parentPublication": {
"id": "proceedings/aiccsa/2009/3807/0",
"title": "2009 IEEE/ACS International Conference on Computer Systems and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2017/3861/0/07991579",
"title": "Client-Side Reconstruction of Composite Mementos Using ServiceWorker",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2017/07991579/12OmNzd7bDM",
"parentPublication": {
"id": "proceedings/jcdl/2017/3861/0",
"title": "2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2017/10/07801009",
"title": "SWAROVsky: Optimizing Resource Loading for Mobile Web Browsing",
"doi": null,
"abstractUrl": "/journal/tm/2017/10/07801009/13rRUIIVll7",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2017/09/07762888",
"title": "ReWAP: Reducing Redundant Transfers for Mobile Web Browsing via App-Specific Resource Packaging",
"doi": null,
"abstractUrl": "/journal/tm/2017/09/07762888/13rRUNvyalC",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ts/2013/12/tts2013121680",
"title": "Identifying Code of Individual Features in Client-Side Web Applications",
"doi": null,
"abstractUrl": "/journal/ts/2013/12/tts2013121680/13rRUwbs2cA",
"parentPublication": {
"id": "trans/ts",
"title": "IEEE Transactions on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2017/10/07926371",
"title": "Off-the-Hook: An Efficient and Usable Client-Side Phishing Prevention Application",
"doi": null,
"abstractUrl": "/journal/tc/2017/10/07926371/13rRUxBrGgc",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07305814",
"articleId": "13rRUxAATha",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07303936",
"articleId": "13rRUwwsltv",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzICEFt",
"title": "Nov.-Dec.",
"year": "2013",
"issueNum": "06",
"idPrefix": "sp",
"pubType": "magazine",
"volume": "11",
"label": "Nov.-Dec.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwbaqK1",
"doi": "10.1109/MSP.2013.103",
"abstract": "Simple tools are needed to support differential diagnosis in a cognitively complex setting. Tools that show similar patients' diagnoses and treatment trajectories might provide useful clinical decision support for emergency physicians who use a case-based reasoning approach. However, privacy concerns that arise with indirect use of electronic health records (EHRs) must be addressed. The authors present a method to abstract a collection of EHRs into a set of summarized patient types and demonstrate its use on a database of medical records.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Simple tools are needed to support differential diagnosis in a cognitively complex setting. Tools that show similar patients' diagnoses and treatment trajectories might provide useful clinical decision support for emergency physicians who use a case-based reasoning approach. However, privacy concerns that arise with indirect use of electronic health records (EHRs) must be addressed. The authors present a method to abstract a collection of EHRs into a set of summarized patient types and demonstrate its use on a database of medical records.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Simple tools are needed to support differential diagnosis in a cognitively complex setting. Tools that show similar patients' diagnoses and treatment trajectories might provide useful clinical decision support for emergency physicians who use a case-based reasoning approach. However, privacy concerns that arise with indirect use of electronic health records (EHRs) must be addressed. The authors present a method to abstract a collection of EHRs into a set of summarized patient types and demonstrate its use on a database of medical records.",
"title": "Nonconfidential Patient Types in Emergency Clinical Decision Support",
"normalizedTitle": "Nonconfidential Patient Types in Emergency Clinical Decision Support",
"fno": "msp2013060012",
"hasPdf": true,
"idPrefix": "sp",
"keywords": [
"Medical Services",
"Medical Diagnostic Imaging",
"Hospitals",
"Data Mining",
"Clinical Diagnosis",
"Decision Making",
"EH Rs",
"Data Mining",
"Clustering",
"Healthcare",
"Patient Types",
"Summarization",
"Privacy",
"Electronic Health Records"
],
"authors": [
{
"givenName": "Mark",
"surname": "Chignell",
"fullName": "Mark Chignell",
"affiliation": "University of Toronto",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mahsa",
"surname": "Rouzbahman",
"fullName": "Mahsa Rouzbahman",
"affiliation": "University of Toronto",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ryan",
"surname": "Kealey",
"fullName": "Ryan Kealey",
"affiliation": "University of Toronto",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Reza",
"surname": "Samavi",
"fullName": "Reza Samavi",
"affiliation": "University of Toronto",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Erin",
"surname": "Yu",
"fullName": "Erin Yu",
"affiliation": "Canadian Imperial Bank of Commerce",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tammy",
"surname": "Sieminowski",
"fullName": "Tammy Sieminowski",
"affiliation": "Bridgepoint Hospital in Toronto",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "06",
"pubDate": "2013-11-01 00:00:00",
"pubType": "mags",
"pages": "12-18",
"year": "2013",
"issn": "1540-7993",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/itng/2014/3187/0/06822184",
"title": "Impact of Online Clinical Data Exchange on Patient Time Saving in Healthcare Delivery",
"doi": null,
"abstractUrl": "/proceedings-article/itng/2014/06822184/12OmNBghtrw",
"parentPublication": {
"id": "proceedings/itng/2014/3187/0",
"title": "2014 Eleventh International Conference on Information Technology: New Generations (ITNG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2016/5473/0/07837899",
"title": "Measuring Patient Similarities via a Deep Architecture with Medical Concept Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2016/07837899/12OmNvjQ8Pp",
"parentPublication": {
"id": "proceedings/icdm/2016/5473/0",
"title": "2016 IEEE 16th International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2015/9548/0/9548a484",
"title": "Discovering the Temporal Interactions between Clinical Observations",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2015/9548a484/12OmNx9FhOI",
"parentPublication": {
"id": "proceedings/ichi/2015/9548/0",
"title": "2015 International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2017/3050/0/08217794",
"title": "Automated clinical diagnosis: The role of content in various sections of a clinical document",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217794/12OmNz61cXD",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbms/2014/4435/0/4435a251",
"title": "Adverse Drug Event Notification System: Reusing Clinical Patient Data for Semi-automatic ADE Detection",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/2014/4435a251/12OmNzBwGJX",
"parentPublication": {
"id": "proceedings/cbms/2014/4435/0",
"title": "2014 IEEE 27th International Symposium on Computer-Based Medical Systems (CBMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2014/2504/0/2504a656",
"title": "Meaningful Use of Electronic Health Records for Physician Collaboration: A Patient Centered Health Care Perspective",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2014/2504a656/12OmNzayNmc",
"parentPublication": {
"id": "proceedings/hicss/2014/2504/0",
"title": "2014 47th Hawaii International Conference on System Sciences (HICSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ex/2015/01/mex2015010070",
"title": "On Clinical Pathway Discovery from Electronic Health Record Data",
"doi": null,
"abstractUrl": "/magazine/ex/2015/01/mex2015010070/13rRUxYIN8J",
"parentPublication": {
"id": "mags/ex",
"title": "IEEE Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2018/9159/0/08594952",
"title": "Diagnosis Prediction via Medical Context Attention Networks Using Deep Generative Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2018/08594952/17D45W9KVFR",
"parentPublication": {
"id": "proceedings/icdm/2018/9159/0",
"title": "2018 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbms/2020/9429/0/942900a177",
"title": "A Clustering Framework for Patient Phenotyping with Application to Adverse Drug Events",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/2020/942900a177/1mLMis5V7m8",
"parentPublication": {
"id": "proceedings/cbms/2020/9429/0",
"title": "2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2020/8316/0/831600a412",
"title": "BiteNet: Bidirectional Temporal Encoder Network to Predict Medical Outcomes",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2020/831600a412/1r54FlmJyVi",
"parentPublication": {
"id": "proceedings/icdm/2020/8316/0",
"title": "2020 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "msp2013060010",
"articleId": "13rRUwcS1x3",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "msp2013060019",
"articleId": "13rRUyYBlf9",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvqEvRo",
"title": "PrePrints",
"year": "5555",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": null,
"label": "PrePrints",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1DvgD0GMunm",
"doi": "10.1109/TVCG.2022.3175626",
"abstract": "Physicians work at a very tight schedule and need decision-making support tools to help on improving and doing their work in a timely and dependable manner. Examining piles of sheets with test results and using systems with little visualization support to provide diagnostics is daunting, but that is still the usual way for the physicians' daily procedure, especially in developing countries. Electronic Health Records systems have been designed to keep the patients' history and reduce the time spent analyzing the patient's data. However, better tools to support decision-making are still needed. In this paper, we propose ClinicalPath, a visualization tool for users to track a patient's clinical path through a series of tests and data, which can aid in treatments and diagnoses. Our proposal is focused on patient's data analysis, presenting the test results and clinical history longitudinally. Both the visualization design and the system functionality were developed in close collaboration with experts in the medical domain to ensure a right fit of the technical solutions and the real needs of the professionals. We validated the proposed visualization based on case studies and user assessments through tasks based on the physician's daily activities. Our results show that our proposed system improves the physicians' experience in decision-making tasks, made with more confidence and better usage of the physicians' time, allowing them to take other needed care for the patients.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Physicians work at a very tight schedule and need decision-making support tools to help on improving and doing their work in a timely and dependable manner. Examining piles of sheets with test results and using systems with little visualization support to provide diagnostics is daunting, but that is still the usual way for the physicians' daily procedure, especially in developing countries. Electronic Health Records systems have been designed to keep the patients' history and reduce the time spent analyzing the patient's data. However, better tools to support decision-making are still needed. In this paper, we propose ClinicalPath, a visualization tool for users to track a patient's clinical path through a series of tests and data, which can aid in treatments and diagnoses. Our proposal is focused on patient's data analysis, presenting the test results and clinical history longitudinally. Both the visualization design and the system functionality were developed in close collaboration with experts in the medical domain to ensure a right fit of the technical solutions and the real needs of the professionals. We validated the proposed visualization based on case studies and user assessments through tasks based on the physician's daily activities. Our results show that our proposed system improves the physicians' experience in decision-making tasks, made with more confidence and better usage of the physicians' time, allowing them to take other needed care for the patients.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Physicians work at a very tight schedule and need decision-making support tools to help on improving and doing their work in a timely and dependable manner. Examining piles of sheets with test results and using systems with little visualization support to provide diagnostics is daunting, but that is still the usual way for the physicians' daily procedure, especially in developing countries. Electronic Health Records systems have been designed to keep the patients' history and reduce the time spent analyzing the patient's data. However, better tools to support decision-making are still needed. In this paper, we propose ClinicalPath, a visualization tool for users to track a patient's clinical path through a series of tests and data, which can aid in treatments and diagnoses. Our proposal is focused on patient's data analysis, presenting the test results and clinical history longitudinally. Both the visualization design and the system functionality were developed in close collaboration with experts in the medical domain to ensure a right fit of the technical solutions and the real needs of the professionals. We validated the proposed visualization based on case studies and user assessments through tasks based on the physician's daily activities. Our results show that our proposed system improves the physicians' experience in decision-making tasks, made with more confidence and better usage of the physicians' time, allowing them to take other needed care for the patients.",
"title": "ClinicalPath: a Visualization tool to Improve the Evaluation of Electronic Health Records in Clinical Decision-Making",
"normalizedTitle": "ClinicalPath: a Visualization tool to Improve the Evaluation of Electronic Health Records in Clinical Decision-Making",
"fno": "09779066",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualization",
"Task Analysis",
"Medical Services",
"History",
"Visualization",
"Medical Diagnostic Imaging",
"Decision Making",
"Information Visualization",
"Interactive Visualizations",
"Human Computer Interaction",
"Electronic Health Records"
],
"authors": [
{
"givenName": "Claudio D. G.",
"surname": "Linhares",
"fullName": "Claudio D. G. Linhares",
"affiliation": "Institute of Mathematics and Computer Sciences, University of Sao Paulo Campus of Sao Carlos, 42512 Sao Carlos, São Paulo, Brazil",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Daniel M.",
"surname": "Lima",
"fullName": "Daniel M. Lima",
"affiliation": "Institute of Mathematics and Computer Sciences, University of Sao Paulo Campus of Sao Carlos, 42512 Sao Carlos, São Paulo, Brazil",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jean R.",
"surname": "Ponciano",
"fullName": "Jean R. Ponciano",
"affiliation": "School of Applied Mathematics, Fundacao Getulio Vargas, 42500 Rio de Janeiro, RJ, Brazil",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mauro M.",
"surname": "Olivatto",
"fullName": "Mauro M. Olivatto",
"affiliation": "Graduate Course in Medicine, Universidade Federal da Fronteira Sul, 232192 Chapeco, Santa Catarina, Brazil",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Marco A.",
"surname": "Gutierrez",
"fullName": "Marco A. Gutierrez",
"affiliation": "Laboratorio de Informatica Biomedica, Universidade de Sao Paulo Instituto do Coracao, 42523 Sao Paulo, São Paulo, Brazil",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jorge",
"surname": "Poco",
"fullName": "Jorge Poco",
"affiliation": "School of Applied Mathematics, Fundacao Getulio Vargas, 42500 Rio de Janeiro, Rio de Janeiro, Brazil, 22250-900",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Caetano",
"surname": "Traina",
"fullName": "Caetano Traina",
"affiliation": "Computer Science, University of Sao Paulo Campus of Sao Carlos, 42512 Sao Carlos, São Paulo, Brazil",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Agma Juci Machado",
"surname": "Traina",
"fullName": "Agma Juci Machado Traina",
"affiliation": "Institute of Mathematics and Computer Sciences, University of Sao Paulo, Sao Carlos, Brazil.",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2022-05-01 00:00:00",
"pubType": "trans",
"pages": "1-1",
"year": "5555",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/bibe/2001/1423/0/00974425",
"title": "Medical decision-making and collaborative reasoning",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2001/00974425/12OmNqGRGdS",
"parentPublication": {
"id": "proceedings/bibe/2001/1423/0",
"title": "Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2011/1799/0/06120478",
"title": "Preserving Narratives in Electronic Health Records",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2011/06120478/12OmNvqEvIv",
"parentPublication": {
"id": "proceedings/bibm/2011/1799/0",
"title": "2011 IEEE International Conference on Bioinformatics and Biomedicine",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsc/2016/0662/0/0662a321",
"title": "Visualization of Pain Severity Events in Clinical Records Using Semantic Structures",
"doi": null,
"abstractUrl": "/proceedings-article/icsc/2016/0662a321/12OmNwB2dUS",
"parentPublication": {
"id": "proceedings/icsc/2016/0662/0",
"title": "2016 IEEE Tenth International Conference on Semantic Computing (ICSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbms/2014/4435/0/4435a497",
"title": "Need and Requirements Elicitation for Electronic Access to Patient's Medication History in the Emergency Department",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/2014/4435a497/12OmNwEJ13T",
"parentPublication": {
"id": "proceedings/cbms/2014/4435/0",
"title": "2014 IEEE 27th International Symposium on Computer-Based Medical Systems (CBMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vahc/2017/3187/0/08387501",
"title": "A timeline-based framework for aggregating and summarizing electronic health records",
"doi": null,
"abstractUrl": "/proceedings-article/vahc/2017/08387501/12OmNyYDDIU",
"parentPublication": {
"id": "proceedings/vahc/2017/3187/0",
"title": "2017 IEEE Workshop on Visual Analytics in Healthcare (VAHC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2011/0868/0/06004004",
"title": "Adaptive Visual Symbols for Personal Health Records",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2011/06004004/12OmNzVGcC4",
"parentPublication": {
"id": "proceedings/iv/2011/0868/0",
"title": "2011 15th International Conference on Information Visualisation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scamc/1983/0503/0/00764817",
"title": "Using experience to improve clinical decision making",
"doi": null,
"abstractUrl": "/proceedings-article/scamc/1983/00764817/12OmNzX6cgy",
"parentPublication": {
"id": "proceedings/scamc/1983/0503/0",
"title": "1983 The Seventh Annual Symposium on Computer Applications in Medical Care",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/sp/2013/06/msp2013060012",
"title": "Nonconfidential Patient Types in Emergency Clinical Decision Support",
"doi": null,
"abstractUrl": "/magazine/sp/2013/06/msp2013060012/13rRUwbaqK1",
"parentPublication": {
"id": "mags/sp",
"title": "IEEE Security & Privacy",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440832",
"title": "<italic>Doccurate</italic>: A Curation-Based Approach for Clinical Text Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440832/17D45WHONqh",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2019/2838/0/283800a392",
"title": "Visualization of Histopathological Decision Making Using a Roadbook Metaphor",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2019/283800a392/1cMF8urE6vS",
"parentPublication": {
"id": "proceedings/iv/2019/2838/0",
"title": "2019 23rd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09779102",
"articleId": "1DvgCK2YAyQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09780012",
"articleId": "1DBTCPd8JS8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1DwUCNxldcs",
"name": "ttg555501-09779066s1-supp1-3175626.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg555501-09779066s1-supp1-3175626.pdf",
"extension": "pdf",
"size": "190 kB",
"__typename": "WebExtraType"
},
{
"id": "1DwUCFIwl2g",
"name": "ttg555501-09779066s1-supp2-3175626.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg555501-09779066s1-supp2-3175626.mp4",
"extension": "mp4",
"size": "45 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1J9y2mtpt3a",
"title": "Jan.",
"year": "2023",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "29",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1H0GeYv7qog",
"doi": "10.1109/TVCG.2022.3209444",
"abstract": "Before seeing a patient for the first time, healthcare workers will typically conduct a comprehensive clinical chart review of the patient's electronic health record (EHR). Within the diverse documentation pieces included there, <italic>text notes</italic> are among the most important and thoroughly perused segments for this task; and yet they are among the least supported medium in terms of content navigation and overview. In this work, we delve deeper into the task of clinical chart review from a data visualization perspective and propose a hybrid <italic>graphics+text</italic> approach via <italic>ChartWalk</italic>, an interactive tool to support the review of text notes in EHRs. We report on our iterative design process grounded in input provided by a diverse range of healthcare professionals, with steps including: (a) initial requirements distilled from interviews and the literature, (b) an interim evaluation to validate design decisions, and (c) a task-based qualitative evaluation of our final design. We contribute lessons learned to better support the design of tools not only for clinical chart reviews but also other healthcare-related tasks around medical text analysis.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Before seeing a patient for the first time, healthcare workers will typically conduct a comprehensive clinical chart review of the patient's electronic health record (EHR). Within the diverse documentation pieces included there, <italic>text notes</italic> are among the most important and thoroughly perused segments for this task; and yet they are among the least supported medium in terms of content navigation and overview. In this work, we delve deeper into the task of clinical chart review from a data visualization perspective and propose a hybrid <italic>graphics+text</italic> approach via <italic>ChartWalk</italic>, an interactive tool to support the review of text notes in EHRs. We report on our iterative design process grounded in input provided by a diverse range of healthcare professionals, with steps including: (a) initial requirements distilled from interviews and the literature, (b) an interim evaluation to validate design decisions, and (c) a task-based qualitative evaluation of our final design. We contribute lessons learned to better support the design of tools not only for clinical chart reviews but also other healthcare-related tasks around medical text analysis.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Before seeing a patient for the first time, healthcare workers will typically conduct a comprehensive clinical chart review of the patient's electronic health record (EHR). Within the diverse documentation pieces included there, text notes are among the most important and thoroughly perused segments for this task; and yet they are among the least supported medium in terms of content navigation and overview. In this work, we delve deeper into the task of clinical chart review from a data visualization perspective and propose a hybrid graphics+text approach via ChartWalk, an interactive tool to support the review of text notes in EHRs. We report on our iterative design process grounded in input provided by a diverse range of healthcare professionals, with steps including: (a) initial requirements distilled from interviews and the literature, (b) an interim evaluation to validate design decisions, and (c) a task-based qualitative evaluation of our final design. We contribute lessons learned to better support the design of tools not only for clinical chart reviews but also other healthcare-related tasks around medical text analysis.",
"title": "<italic>ChartWalk</italic>: Navigating large collections of text notes in electronic health records for clinical chart review",
"normalizedTitle": "ChartWalk: Navigating large collections of text notes in electronic health records for clinical chart review",
"fno": "09904479",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Visualisation",
"Electronic Health Records",
"Health Care",
"Text Analysis",
"Chart Walk",
"Comprehensive Clinical Chart Review",
"Content Navigation",
"EHR",
"Electronic Health Records",
"Healthcare Related Tasks",
"Hybrid Graphics Text Approach",
"Task Based Qualitative Evaluation",
"Text Notes",
"Medical Services",
"Task Analysis",
"Visualization",
"Data Visualization",
"Navigation",
"Iterative Methods",
"Natural Language Processing",
"Electronic Health Record EHR",
"Text Visualization",
"Close Distant Reading",
"Clinical Overview",
"Medicine"
],
"authors": [
{
"givenName": "Nicole",
"surname": "Sultanum",
"fullName": "Nicole Sultanum",
"affiliation": "University of Toronto, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Farooq",
"surname": "Naeem",
"fullName": "Farooq Naeem",
"affiliation": "Centre for Addiction and Mental Health (CAMH), Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Michael",
"surname": "Brudno",
"fullName": "Michael Brudno",
"affiliation": "University of Toronto, Canada",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Fanny",
"surname": "Chevalier",
"fullName": "Fanny Chevalier",
"affiliation": "University of Toronto, Canada",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2023-01-01 00:00:00",
"pubType": "trans",
"pages": "1244-1254",
"year": "2023",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/snpd/2008/3263/0/3263a640",
"title": "Collation Strategy Based on Heuristics Chart for Myanmar Language",
"doi": null,
"abstractUrl": "/proceedings-article/snpd/2008/3263a640/12OmNAQJzON",
"parentPublication": {
"id": "proceedings/snpd/2008/3263/0",
"title": "2008 Ninth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2013/3142/0/3143a274",
"title": "MedCat: A Framework for High Level Conceptualization of Medical Notes",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2013/3143a274/12OmNApcutO",
"parentPublication": {
"id": "proceedings/icdmw/2013/3142/0",
"title": "2013 IEEE 13th International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2017/3050/0/08217883",
"title": "Medical concept intersection between outside medical records and consultant notes: A case study in transferred cardiovascular patients",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217883/12OmNBKmXke",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/1993/4960/0/00395744",
"title": "Text recognition enhancement with a probabilistic lattice chart parser",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/1993/00395744/12OmNBcAGMH",
"parentPublication": {
"id": "proceedings/icdar/1993/4960/0",
"title": "Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440832",
"title": "<italic>Doccurate</italic>: A Curation-Based Approach for Clinical Text Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440832/17D45WHONqh",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2021/0132/0/013200a083",
"title": "CATAN: Chart-aware temporal attention network for adverse outcome prediction",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2021/013200a083/1xIOSZuZuvK",
"parentPublication": {
"id": "proceedings/ichi/2021/0132/0",
"title": "2021 IEEE 9th International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2021/0132/0/013200a548",
"title": "NLP-Based Prediction of Medical Specialties at Hospital Admission Using Triage Notes",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2021/013200a548/1xIOTtAthlK",
"parentPublication": {
"id": "proceedings/ichi/2021/0132/0",
"title": "2021 IEEE 9th International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2021/0132/0/013200a153",
"title": "Identifying Mentions of Life Stressors in Clinical Notes",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2021/013200a153/1xIOWNubm7e",
"parentPublication": {
"id": "proceedings/ichi/2021/0132/0",
"title": "2021 IEEE 9th International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/01/09617561",
"title": "Natural Language to Visualization by Neural Machine Translation",
"doi": null,
"abstractUrl": "/journal/tg/2022/01/09617561/1yA76vDzhhC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vahc/2020/2644/0/264400a026",
"title": "Feature Extraction and Visualization of Respiratory Therapist Notes for Pediatric Long-Term Ventilator Dependent Patients",
"doi": null,
"abstractUrl": "/proceedings-article/vahc/2020/264400a026/1yhFDMfMzIs",
"parentPublication": {
"id": "proceedings/vahc/2020/2644/0",
"title": "2020 Workshop on Visual Analytics in Healthcare (VAHC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09904452",
"articleId": "1H1gordOnfy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09906007",
"articleId": "1H3ZU9zES3u",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1J9ycG0wjNm",
"name": "ttg202301-09904479s1-supp1-3209444.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202301-09904479s1-supp1-3209444.mp4",
"extension": "mp4",
"size": "63.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNxvO04Q",
"title": "Jan.",
"year": "2017",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "23",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxBJhvA",
"doi": "10.1109/TVCG.2016.2598465",
"abstract": "In this paper, we present a novel visual analytics system called NameClarifier to interactively disambiguate author names in publications by keeping humans in the loop. Specifically, NameClarifier quantifies and visualizes the similarities between ambiguous names and those that have been confirmed in digital libraries. The similarities are calculated using three key factors, namely, co-authorships, publication venues, and temporal information. Our system estimates all possible allocations, and then provides visual cues to users to help them validate every ambiguous case. By looping users in the disambiguation process, our system can achieve more reliable results than general data mining models for highly ambiguous cases. In addition, once an ambiguous case is resolved, the result is instantly added back to our system and serves as additional cues for all the remaining unidentified names. In this way, we open up the black box in traditional disambiguation processes, and help intuitively and comprehensively explain why the corresponding classifications should hold. We conducted two use cases and an expert review to demonstrate the effectiveness of NameClarifier.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, we present a novel visual analytics system called NameClarifier to interactively disambiguate author names in publications by keeping humans in the loop. Specifically, NameClarifier quantifies and visualizes the similarities between ambiguous names and those that have been confirmed in digital libraries. The similarities are calculated using three key factors, namely, co-authorships, publication venues, and temporal information. Our system estimates all possible allocations, and then provides visual cues to users to help them validate every ambiguous case. By looping users in the disambiguation process, our system can achieve more reliable results than general data mining models for highly ambiguous cases. In addition, once an ambiguous case is resolved, the result is instantly added back to our system and serves as additional cues for all the remaining unidentified names. In this way, we open up the black box in traditional disambiguation processes, and help intuitively and comprehensively explain why the corresponding classifications should hold. We conducted two use cases and an expert review to demonstrate the effectiveness of NameClarifier.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, we present a novel visual analytics system called NameClarifier to interactively disambiguate author names in publications by keeping humans in the loop. Specifically, NameClarifier quantifies and visualizes the similarities between ambiguous names and those that have been confirmed in digital libraries. The similarities are calculated using three key factors, namely, co-authorships, publication venues, and temporal information. Our system estimates all possible allocations, and then provides visual cues to users to help them validate every ambiguous case. By looping users in the disambiguation process, our system can achieve more reliable results than general data mining models for highly ambiguous cases. In addition, once an ambiguous case is resolved, the result is instantly added back to our system and serves as additional cues for all the remaining unidentified names. In this way, we open up the black box in traditional disambiguation processes, and help intuitively and comprehensively explain why the corresponding classifications should hold. We conducted two use cases and an expert review to demonstrate the effectiveness of NameClarifier.",
"title": "NameClarifier: A Visual Analytics System for Author Name Disambiguation",
"normalizedTitle": "NameClarifier: A Visual Analytics System for Author Name Disambiguation",
"fno": "07534824",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Libraries",
"Metadata",
"Algorithm Design And Analysis",
"Uncertainty",
"Visual Analytics",
"Analytical Reasoning",
"Name Disambiguation"
],
"authors": [
{
"givenName": "Qiaomu",
"surname": "Shen",
"fullName": "Qiaomu Shen",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tongshuang",
"surname": "Wu",
"fullName": "Tongshuang Wu",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haiyan",
"surname": "Yang",
"fullName": "Haiyan Yang",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yanhong",
"surname": "Wu",
"fullName": "Yanhong Wu",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Huamin",
"surname": "Qu",
"fullName": "Huamin Qu",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Weiwei",
"surname": "Cui",
"fullName": "Weiwei Cui",
"affiliation": "Microsoft Research",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2017-01-01 00:00:00",
"pubType": "trans",
"pages": "141-150",
"year": "2017",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/bdcat/2016/4617/0/6005a052",
"title": "A Visual Analytics Approach to Author Name Disambiguation",
"doi": null,
"abstractUrl": "/proceedings-article/bdcat/2016/6005a052/12OmNvjyxUp",
"parentPublication": {
"id": "proceedings/bdcat/2016/4617/0",
"title": "2016 IEEE/ACM 3rd International Conference on Big Data Computing Applications and Technologies (BDCAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2014/5666/0/07004487",
"title": "Large scale author name disambiguation in digital libraries",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2014/07004487/12OmNwCJOKZ",
"parentPublication": {
"id": "proceedings/big-data/2014/5666/0",
"title": "2014 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi-iat/2011/4513/3/4513c335",
"title": "Author Name Disambiguation in Citations",
"doi": null,
"abstractUrl": "/proceedings-article/wi-iat/2011/4513c335/12OmNwcCIR8",
"parentPublication": {
"id": "proceedings/wi-iat/2011/4513/3",
"title": "Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ic3/2014/5172/0/06897162",
"title": "Author name disambiguation using vector space model and hybrid similarity measures",
"doi": null,
"abstractUrl": "/proceedings-article/ic3/2014/06897162/12OmNxFsmp6",
"parentPublication": {
"id": "proceedings/ic3/2014/5172/0",
"title": "2014 Seventh International Conference on Contemporary Computing (IC3)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcce/2017/2628/0/2628a122",
"title": "An Online Name Disambiguation Method Based on Entity and Property Co-occurrence",
"doi": null,
"abstractUrl": "/proceedings-article/icmcce/2017/2628a122/12OmNz2C1AF",
"parentPublication": {
"id": "proceedings/icmcce/2017/2628/0",
"title": "2017 Second International Conference on Mechanical, Control and Computer Engineering (ICMCCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2016/4229/0/07559614",
"title": "Using co-authorship networks for author name disambiguation",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2016/07559614/12OmNzBOhLQ",
"parentPublication": {
"id": "proceedings/jcdl/2016/4229/0",
"title": "2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi/2006/2747/0/274700378",
"title": "Name Disambiguation in Person Information Mining",
"doi": null,
"abstractUrl": "/proceedings-article/wi/2006/274700378/12OmNzaQotb",
"parentPublication": {
"id": "proceedings/wi/2006/2747/0",
"title": "2006 IEEE/WIC/ACM International Conference on Web Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2019/0858/0/09005458",
"title": "Unsupervised Author Disambiguation using Heterogeneous Graph Convolutional Network Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2019/09005458/1hJsdmMJVoQ",
"parentPublication": {
"id": "proceedings/big-data/2019/0858/0",
"title": "2019 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/05/09147044",
"title": "A Collective Approach to Scholar Name Disambiguation",
"doi": null,
"abstractUrl": "/journal/tk/2022/05/09147044/1lIYCwlAKLS",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2021/9184/0/918400c317",
"title": "A Collective Approach to Scholar Name Disambiguation (Extended Abstract)",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2021/918400c317/1uGXsnGDirC",
"parentPublication": {
"id": "proceedings/icde/2021/9184/0",
"title": "2021 IEEE 37th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07534760",
"articleId": "13rRUwbaqLy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07539597",
"articleId": "13rRUy0qnLK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1LtQZ5gcy52",
"title": "April",
"year": "2023",
"issueNum": "02",
"idPrefix": "bd",
"pubType": "journal",
"volume": "9",
"label": "April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1ELg5qCGLWE",
"doi": "10.1109/TBDATA.2022.3188660",
"abstract": "Bitcoin is gaining ever increasing popularity. However, professional skills are required if people want to check bitcoin transaction information from the blockchain. As pointed out in a recent study, there is a lack of tools to support effective interactive investigation of bitcoin transactions. Therefore, we present a novel visualization system, <italic>BitAnalysis</italic>, for interactive bitcoin wallet investigation. The analytical and visualization functions of <italic>BitAnalysis</italic> are defined and developed by following the advice and requirements of a group of entrepreneurs and regulators of bitcoin-related business. <italic>BitAnalysis</italic> provides a rich set of functions and intuitive visual interfaces for the users, such as law-enforcement officers and regulators, to effectively visualize and analyze the transactions of a bitcoin wallet (i.e., a cluster of bitcoin addresses) and its related wallets, to track the flow of bitcoins, and to identify wallet correlation using our novel clustering functions. To achieve these functions, we have designed new visualization techniques for presenting bitcoin transactions information and introduced the <italic>connection diagram</italic> and <italic>bitcoin flow map</italic> as new ways of analyzing, tracking and monitoring the trading activities of a cluster of closely related wallets. We also present an extensive user study that validated the effectiveness and usability of <italic>BitAnalysis</italic>.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Bitcoin is gaining ever increasing popularity. However, professional skills are required if people want to check bitcoin transaction information from the blockchain. As pointed out in a recent study, there is a lack of tools to support effective interactive investigation of bitcoin transactions. Therefore, we present a novel visualization system, <italic>BitAnalysis</italic>, for interactive bitcoin wallet investigation. The analytical and visualization functions of <italic>BitAnalysis</italic> are defined and developed by following the advice and requirements of a group of entrepreneurs and regulators of bitcoin-related business. <italic>BitAnalysis</italic> provides a rich set of functions and intuitive visual interfaces for the users, such as law-enforcement officers and regulators, to effectively visualize and analyze the transactions of a bitcoin wallet (i.e., a cluster of bitcoin addresses) and its related wallets, to track the flow of bitcoins, and to identify wallet correlation using our novel clustering functions. To achieve these functions, we have designed new visualization techniques for presenting bitcoin transactions information and introduced the <italic>connection diagram</italic> and <italic>bitcoin flow map</italic> as new ways of analyzing, tracking and monitoring the trading activities of a cluster of closely related wallets. We also present an extensive user study that validated the effectiveness and usability of <italic>BitAnalysis</italic>.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Bitcoin is gaining ever increasing popularity. However, professional skills are required if people want to check bitcoin transaction information from the blockchain. As pointed out in a recent study, there is a lack of tools to support effective interactive investigation of bitcoin transactions. Therefore, we present a novel visualization system, BitAnalysis, for interactive bitcoin wallet investigation. The analytical and visualization functions of BitAnalysis are defined and developed by following the advice and requirements of a group of entrepreneurs and regulators of bitcoin-related business. BitAnalysis provides a rich set of functions and intuitive visual interfaces for the users, such as law-enforcement officers and regulators, to effectively visualize and analyze the transactions of a bitcoin wallet (i.e., a cluster of bitcoin addresses) and its related wallets, to track the flow of bitcoins, and to identify wallet correlation using our novel clustering functions. To achieve these functions, we have designed new visualization techniques for presenting bitcoin transactions information and introduced the connection diagram and bitcoin flow map as new ways of analyzing, tracking and monitoring the trading activities of a cluster of closely related wallets. We also present an extensive user study that validated the effectiveness and usability of BitAnalysis.",
"title": "BitAnalysis: A Visualization System for Bitcoin Wallet Investigation",
"normalizedTitle": "BitAnalysis: A Visualization System for Bitcoin Wallet Investigation",
"fno": "09815504",
"hasPdf": true,
"idPrefix": "bd",
"keywords": [
"Blockchains",
"Cryptocurrencies",
"Data Visualisation",
"Financial Data Processing",
"Analytical Functions",
"Bitcoin Addresses",
"Bitcoin Transaction Information",
"Bitcoin Transactions Information",
"Bitcoin Related Business Bit Analysisprovides",
"Closely Related Wallets",
"Effective Interactive Investigation",
"Interactive Bitcoin Wallet Investigation",
"Intuitive Visual Interfaces",
"Law Enforcement Officers",
"Novel Clustering Functions",
"Visualization Functions",
"Visualization System",
"Visualization Techniques",
"Wallet Correlation",
"Bitcoin",
"Data Visualization",
"Monitoring",
"Blockchains",
"Visualization",
"Anomaly Detection",
"Roads",
"Bitcoin",
"Fin Tech",
"Transaction Data",
"Visualization"
],
"authors": [
{
"givenName": "Yujing",
"surname": "Sun",
"fullName": "Yujing Sun",
"affiliation": "Department of Computer Science, University of Hong Kong, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hao",
"surname": "Xiong",
"fullName": "Hao Xiong",
"affiliation": "Department of Computer Science, University of Hong Kong, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Siu Ming",
"surname": "Yiu",
"fullName": "Siu Ming Yiu",
"affiliation": "Department of Computer Science, University of Hong Kong, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Kwok Yan",
"surname": "Lam",
"fullName": "Kwok Yan Lam",
"affiliation": "Department of Computer Science, Nanyang Technological University, Singapore",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "02",
"pubDate": "2023-04-01 00:00:00",
"pubType": "trans",
"pages": "621-636",
"year": "2023",
"issn": "2332-7790",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/wimob/2017/3839/0/08115844",
"title": "Blockchain-based payment collection supervision system using pervasive Bitcoin digital wallet",
"doi": null,
"abstractUrl": "/proceedings-article/wimob/2017/08115844/12OmNyv7lZP",
"parentPublication": {
"id": "proceedings/wimob/2017/3839/0",
"title": "2017 IEEE 13th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440044",
"title": "BitExTract: Interactive Visualization for Extracting Bitcoin Exchange Intelligence",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440044/17D45VTRovg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2018/9288/0/928800b469",
"title": "BiVA: Bitcoin Network Visualization & Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2018/928800b469/18jXBBaszPW",
"parentPublication": {
"id": "proceedings/icdmw/2018/9288/0",
"title": "2018 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2018/9288/0/928800a244",
"title": "EGRET: Extortion Graph Exploration Techniques in the Bitcoin Network",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2018/928800a244/18jXIxFHIQw",
"parentPublication": {
"id": "proceedings/icdmw/2018/9288/0",
"title": "2018 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/blockchain/2021/1760/0/176000a409",
"title": "On Creation of a Stablecoin Based on the Morini's Scheme of Inv&Sav Wallets and Antimoney",
"doi": null,
"abstractUrl": "/proceedings-article/blockchain/2021/176000a409/1AqxCH4hjGM",
"parentPublication": {
"id": "proceedings/blockchain/2021/1760/0",
"title": "2021 IEEE International Conference on Blockchain (Blockchain)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/blockchain/2021/1760/0/176000a388",
"title": "Diffusion: Analysis of Many-to-Many Transactions in Bitcoin",
"doi": null,
"abstractUrl": "/proceedings-article/blockchain/2021/176000a388/1Aqxu78h9UQ",
"parentPublication": {
"id": "proceedings/blockchain/2021/1760/0",
"title": "2021 IEEE International Conference on Blockchain (Blockchain)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trustcom/2021/1658/0/165800a911",
"title": "ESS: An Efficient Storage Scheme for Improving the Scalability of Bitcoin System",
"doi": null,
"abstractUrl": "/proceedings-article/trustcom/2021/165800a911/1BBz1eXd1Ic",
"parentPublication": {
"id": "proceedings/trustcom/2021/1658/0",
"title": "2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2022/8810/0/881000a767",
"title": "Introduction of a New Method for Preventing Recipient Unapproved Transactions to Bitcoin Wallet",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2022/881000a767/1FJ5R1qgWGI",
"parentPublication": {
"id": "proceedings/compsac/2022/8810/0",
"title": "2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccbb/2018/1277/0/08756455",
"title": "Bitcoin Blockchain Transactions Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/iccbb/2018/08756455/1bzYmpPzDEY",
"parentPublication": {
"id": "proceedings/iccbb/2018/1277/0",
"title": "2018 International Conference on Cloud Computing, Big Data and Blockchain (ICCBB)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvcbt/2019/3669/0/366900a021",
"title": "BitVis: An Interactive Visualization System for Bitcoin Accounts Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/cvcbt/2019/366900a021/1cdOxxsVcA0",
"parentPublication": {
"id": "proceedings/cvcbt/2019/3669/0",
"title": "2019 Crypto Valley Conference on Blockchain Technology (CVCBT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09880520",
"articleId": "1GttW4ON4bK",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09858628",
"articleId": "1FUYvtRM2gE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1x3fXNXb4TC",
"title": "July-Sept.",
"year": "2021",
"issueNum": "03",
"idPrefix": "ec",
"pubType": "journal",
"volume": "9",
"label": "July-Sept.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1lClzo4jZxC",
"doi": "10.1109/TETC.2020.3010464",
"abstract": "Bitcoin and its decentralized computing paradigm for digital currency trading are one of the most disruptive technology in the 21st century. This article presents a novel approach to developing a Bitcoin transaction forecast model, DLForecast, by leveraging deep neural networks for learning Bitcoin transaction network representations. DLForecast makes three original contributions. First, we explore three interesting properties between Bitcoin transaction accounts: topological connectivity pattern of Bitcoin accounts, transaction amount pattern, and transaction dynamics. Second, we construct a time-decaying reachability graph and a time-decaying transaction pattern graph, aiming at capturing different types of spatial-temporal Bitcoin transaction patterns. Third, we employ node embedding on both graphs and develop a Bitcoin transaction forecasting system between user accounts based on historical transactions with built-in time-decaying factor. To maintain an effective transaction forecasting performance, we leverage the multiplicative model update (MMU) ensemble to combine prediction models built on different transaction features extracted from each corresponding Bitcoin transaction graph. Evaluated on real-world Bitcoin transaction data, we show that our spatial-temporal forecasting model is efficient with fast runtime and effective with forecasting accuracy over 60 percent and improves the prediction performance by 50 percent when compared to forecasting model built on the static graph baseline.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Bitcoin and its decentralized computing paradigm for digital currency trading are one of the most disruptive technology in the 21st century. This article presents a novel approach to developing a Bitcoin transaction forecast model, DLForecast, by leveraging deep neural networks for learning Bitcoin transaction network representations. DLForecast makes three original contributions. First, we explore three interesting properties between Bitcoin transaction accounts: topological connectivity pattern of Bitcoin accounts, transaction amount pattern, and transaction dynamics. Second, we construct a time-decaying reachability graph and a time-decaying transaction pattern graph, aiming at capturing different types of spatial-temporal Bitcoin transaction patterns. Third, we employ node embedding on both graphs and develop a Bitcoin transaction forecasting system between user accounts based on historical transactions with built-in time-decaying factor. To maintain an effective transaction forecasting performance, we leverage the multiplicative model update (MMU) ensemble to combine prediction models built on different transaction features extracted from each corresponding Bitcoin transaction graph. Evaluated on real-world Bitcoin transaction data, we show that our spatial-temporal forecasting model is efficient with fast runtime and effective with forecasting accuracy over 60 percent and improves the prediction performance by 50 percent when compared to forecasting model built on the static graph baseline.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Bitcoin and its decentralized computing paradigm for digital currency trading are one of the most disruptive technology in the 21st century. This article presents a novel approach to developing a Bitcoin transaction forecast model, DLForecast, by leveraging deep neural networks for learning Bitcoin transaction network representations. DLForecast makes three original contributions. First, we explore three interesting properties between Bitcoin transaction accounts: topological connectivity pattern of Bitcoin accounts, transaction amount pattern, and transaction dynamics. Second, we construct a time-decaying reachability graph and a time-decaying transaction pattern graph, aiming at capturing different types of spatial-temporal Bitcoin transaction patterns. Third, we employ node embedding on both graphs and develop a Bitcoin transaction forecasting system between user accounts based on historical transactions with built-in time-decaying factor. To maintain an effective transaction forecasting performance, we leverage the multiplicative model update (MMU) ensemble to combine prediction models built on different transaction features extracted from each corresponding Bitcoin transaction graph. Evaluated on real-world Bitcoin transaction data, we show that our spatial-temporal forecasting model is efficient with fast runtime and effective with forecasting accuracy over 60 percent and improves the prediction performance by 50 percent when compared to forecasting model built on the static graph baseline.",
"title": "Bitcoin Transaction Forecasting With Deep Network Representation Learning",
"normalizedTitle": "Bitcoin Transaction Forecasting With Deep Network Representation Learning",
"fno": "09144374",
"hasPdf": true,
"idPrefix": "ec",
"keywords": [
"Cryptocurrencies",
"Deep Learning Artificial Intelligence",
"Distributed Databases",
"Financial Data Processing",
"Graph Theory",
"Topology",
"Transaction Processing",
"Deep Network Representation Learning",
"Decentralized Computing Paradigm",
"Digital Currency Trading",
"DL Forecast",
"Deep Neural Networks",
"Bitcoin Transaction Network Representations",
"Transaction Amount Pattern",
"Transaction Dynamics",
"Time Decaying Reachability Graph",
"Time Decaying Transaction Pattern Graph",
"Spatial Temporal Bitcoin Transaction Patterns",
"Bitcoin Transaction Forecasting System",
"Multiplicative Model Update",
"Bitcoin Transaction Graph",
"Bitcoin Transaction Data",
"Spatial Temporal Forecasting Model",
"Bitcoin Account Topological Connectivity Pattern",
"MMU",
"Bitcoin",
"Forecasting",
"Predictive Models",
"Feature Extraction",
"Peer To Peer Computing",
"Neural Networks",
"Data Models",
"Network Representation Learning",
"Large Scale And Dynamic Graph Mining",
"Transaction Forecasting As A Service"
],
"authors": [
{
"givenName": "Wenqi",
"surname": "Wei",
"fullName": "Wenqi Wei",
"affiliation": "School of Computer Science, Georgia Institute of Technology, Atlanta, GA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Qi",
"surname": "Zhang",
"fullName": "Qi Zhang",
"affiliation": "IBM T. J. Watson Research Center, Yorktown Heights, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ling",
"surname": "Liu",
"fullName": "Ling Liu",
"affiliation": "School of Computer Science, Georgia Institute of Technology, Atlanta, GA, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "03",
"pubDate": "2021-07-01 00:00:00",
"pubType": "trans",
"pages": "1359-1371",
"year": "2021",
"issn": "2168-6750",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/itnac/2017/6796/0/08215367",
"title": "Increased block size and Bitcoin blockchain dynamics",
"doi": null,
"abstractUrl": "/proceedings-article/itnac/2017/08215367/12OmNvT2p1C",
"parentPublication": {
"id": "proceedings/itnac/2017/6796/0",
"title": "2017 27th International Telecommunication Networks and Applications Conference (ITNAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dsc/2018/4210/0/421001a280",
"title": "Bitcoin Mixing Detection Using Deep Autoencoder",
"doi": null,
"abstractUrl": "/proceedings-article/dsc/2018/421001a280/12OmNxb5hp9",
"parentPublication": {
"id": "proceedings/dsc/2018/4210/0",
"title": "2018 IEEE Third International Conference on Data Science in Cyberspace (DSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2018/9159/0/08594932",
"title": "Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2018/08594932/17D45VTRovP",
"parentPublication": {
"id": "proceedings/icdm/2018/9159/0",
"title": "2018 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvcbt/2018/7204/0/720401a112",
"title": "(Short Paper) Inputs Reduction for More Space in Bitcoin Blocks",
"doi": null,
"abstractUrl": "/proceedings-article/cvcbt/2018/720401a112/17D45WLdYRc",
"parentPublication": {
"id": "proceedings/cvcbt/2018/7204/0",
"title": "2018 Crypto Valley Conference on Blockchain Technology (CVCBT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2018/9288/0/928800a168",
"title": "A New Forecasting Framework for Bitcoin Price with LSTM",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2018/928800a168/18jXI8eTZi8",
"parentPublication": {
"id": "proceedings/icdmw/2018/9288/0",
"title": "2018 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccbb/2018/1277/0/08756455",
"title": "Bitcoin Blockchain Transactions Visualization",
"doi": null,
"abstractUrl": "/proceedings-article/iccbb/2018/08756455/1bzYmpPzDEY",
"parentPublication": {
"id": "proceedings/iccbb/2018/1277/0",
"title": "2018 International Conference on Cloud Computing, Big Data and Blockchain (ICCBB)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2019/4896/0/489600a216",
"title": "Forecasting Ethereum STORJ Token Prices: Comparative Analyses of Applied Bitcoin Models",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2019/489600a216/1gAwRCNNiQo",
"parentPublication": {
"id": "proceedings/icdmw/2019/4896/0",
"title": "2019 International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/blockchain/2019/4693/0/469300a107",
"title": "Bitcoin Mining with Transaction Fees: A Game on the Block Size",
"doi": null,
"abstractUrl": "/proceedings-article/blockchain/2019/469300a107/1gjS53xOkOQ",
"parentPublication": {
"id": "proceedings/blockchain/2019/4693/0",
"title": "2019 IEEE International Conference on Blockchain (Blockchain)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigcom/2020/8275/0/09160462",
"title": "Measurement and Analysis of the Bitcoin Networks: A View from Mining Pools",
"doi": null,
"abstractUrl": "/proceedings-article/bigcom/2020/09160462/1m4CJmCFAVa",
"parentPublication": {
"id": "proceedings/bigcom/2020/8275/0",
"title": "2020 6th International Conference on Big Data Computing and Communications (BIGCOM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/smds/2021/0058/0/005800a162",
"title": "An Analysis of Transaction Handling in Bitcoin",
"doi": null,
"abstractUrl": "/proceedings-article/smds/2021/005800a162/1yeQugyN9MA",
"parentPublication": {
"id": "proceedings/smds/2021/0058/0",
"title": "2021 IEEE International Conference on Smart Data Services (SMDS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09296817",
"articleId": "1pDnRJsysMw",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09540927",
"articleId": "1x3g6JQfPmU",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNxvO04Q",
"title": "Jan.",
"year": "2017",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "23",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwbaqLy",
"doi": "10.1109/TVCG.2016.2598470",
"abstract": "In interactive data analysis processes, the dialogue between the human and the computer is the enabling mechanism that can lead to actionable observations about the phenomena being investigated. It is of paramount importance that this dialogue is not interrupted by slow computational mechanisms that do not consider any known temporal human-computer interaction characteristics that prioritize the perceptual and cognitive capabilities of the users. In cases where the analysis involves an integrated computational method, for instance to reduce the dimensionality of the data or to perform clustering, such non-optimal processes are often likely. To remedy this, progressive computations, where results are iteratively improved, are getting increasing interest in visual analytics. In this paper, we present techniques and design considerations to incorporate progressive methods within interactive analysis processes that involve high-dimensional data. We define methodologies to facilitate processes that adhere to the perceptual characteristics of users and describe how online algorithms can be incorporated within these. A set of design recommendations and according methods to support analysts in accomplishing high-dimensional data analysis tasks are then presented. Our arguments and decisions here are informed by observations gathered over a series of analysis sessions with analysts from finance. We document observations and recommendations from this study and present evidence on how our approach contribute to the efficiency and productivity of interactive visual analysis sessions involving high-dimensional data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In interactive data analysis processes, the dialogue between the human and the computer is the enabling mechanism that can lead to actionable observations about the phenomena being investigated. It is of paramount importance that this dialogue is not interrupted by slow computational mechanisms that do not consider any known temporal human-computer interaction characteristics that prioritize the perceptual and cognitive capabilities of the users. In cases where the analysis involves an integrated computational method, for instance to reduce the dimensionality of the data or to perform clustering, such non-optimal processes are often likely. To remedy this, progressive computations, where results are iteratively improved, are getting increasing interest in visual analytics. In this paper, we present techniques and design considerations to incorporate progressive methods within interactive analysis processes that involve high-dimensional data. We define methodologies to facilitate processes that adhere to the perceptual characteristics of users and describe how online algorithms can be incorporated within these. A set of design recommendations and according methods to support analysts in accomplishing high-dimensional data analysis tasks are then presented. Our arguments and decisions here are informed by observations gathered over a series of analysis sessions with analysts from finance. We document observations and recommendations from this study and present evidence on how our approach contribute to the efficiency and productivity of interactive visual analysis sessions involving high-dimensional data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In interactive data analysis processes, the dialogue between the human and the computer is the enabling mechanism that can lead to actionable observations about the phenomena being investigated. It is of paramount importance that this dialogue is not interrupted by slow computational mechanisms that do not consider any known temporal human-computer interaction characteristics that prioritize the perceptual and cognitive capabilities of the users. In cases where the analysis involves an integrated computational method, for instance to reduce the dimensionality of the data or to perform clustering, such non-optimal processes are often likely. To remedy this, progressive computations, where results are iteratively improved, are getting increasing interest in visual analytics. In this paper, we present techniques and design considerations to incorporate progressive methods within interactive analysis processes that involve high-dimensional data. We define methodologies to facilitate processes that adhere to the perceptual characteristics of users and describe how online algorithms can be incorporated within these. A set of design recommendations and according methods to support analysts in accomplishing high-dimensional data analysis tasks are then presented. Our arguments and decisions here are informed by observations gathered over a series of analysis sessions with analysts from finance. We document observations and recommendations from this study and present evidence on how our approach contribute to the efficiency and productivity of interactive visual analysis sessions involving high-dimensional data.",
"title": "Designing Progressive and Interactive Analytics Processes for High-Dimensional Data Analysis",
"normalizedTitle": "Designing Progressive and Interactive Analytics Processes for High-Dimensional Data Analysis",
"fno": "07534760",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Computers",
"Data Analysis",
"Principal Component Analysis",
"Visual Analytics",
"Algorithm Design And Analysis",
"Data Visualization",
"Visual Analytics",
"Progressive Analytics",
"High Dimensional Data",
"Iterative Refinement"
],
"authors": [
{
"givenName": "Cagatay",
"surname": "Turkay",
"fullName": "Cagatay Turkay",
"affiliation": "City University, London, UK",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Erdem",
"surname": "Kaya",
"fullName": "Erdem Kaya",
"affiliation": "Sabanci University, Turkey",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Selim",
"surname": "Balcisoy",
"fullName": "Selim Balcisoy",
"affiliation": "Sabanci University, Turkey",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Helwig",
"surname": "Hauser",
"fullName": "Helwig Hauser",
"affiliation": "University of Bergen, Norway",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2017-01-01 00:00:00",
"pubType": "trans",
"pages": "131-140",
"year": "2017",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/hicss/2013/4892/0/4892b495",
"title": "A Role for Reasoning in Visual Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2013/4892b495/12OmNqJ8tq4",
"parentPublication": {
"id": "proceedings/hicss/2013/4892/0",
"title": "2013 46th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2011/9618/0/05718616",
"title": "Pair Analytics: Capturing Reasoning Processes in Collaborative Visual Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2011/05718616/12OmNvAiShB",
"parentPublication": {
"id": "proceedings/hicss/2011/9618/0",
"title": "2011 44th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2013/04/mcg2013040022",
"title": "Customizing Computational Methods for Visual Analytics with Big Data",
"doi": null,
"abstractUrl": "/magazine/cg/2013/04/mcg2013040022/13rRUB7a1ij",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/01/07192719",
"title": "Visual Analytics for Development and Evaluation of Order Selection Criteria for Autoregressive Processes",
"doi": null,
"abstractUrl": "/journal/tg/2016/01/07192719/13rRUwfZBVo",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2017/01/mcg2017010100",
"title": "Sampling for Scalable Visual Analytics",
"doi": null,
"abstractUrl": "/magazine/cg/2017/01/mcg2017010100/13rRUxBa5pi",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/01/08019872",
"title": "DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks",
"doi": null,
"abstractUrl": "/journal/tg/2018/01/08019872/13rRUxlgxTs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2017/07/07473883",
"title": "Approximated and User Steerable tSNE for Progressive Visual Analytics",
"doi": null,
"abstractUrl": "/journal/tg/2017/07/07473883/13rRUxly8T1",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440814",
"title": "SIRIUS: Dual, Symmetric, Interactive Dimension Reductions",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440814/17D45XeKgns",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2018/6861/0/08802486",
"title": "SMARTexplore: Simplifying High-Dimensional Data Analysis through a Table-Based Visual Analytics Approach",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2018/08802486/1cJ6YwLGq40",
"parentPublication": {
"id": "proceedings/vast/2018/6861/0",
"title": "2018 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2019/9226/0/922600a237",
"title": "Designing Narrative Slideshows for Learning Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2019/922600a237/1cMF6FsJ8zK",
"parentPublication": {
"id": "proceedings/pacificvis/2019/9226/0",
"title": "2019 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07534744",
"articleId": "13rRUxOdD8k",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07534824",
"articleId": "13rRUxBJhvA",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzC5SI0",
"title": "Oct.-Dec.",
"year": "2018",
"issueNum": "04",
"idPrefix": "mc",
"pubType": "journal",
"volume": "4",
"label": "Oct.-Dec.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "17D45WaTkdy",
"doi": "10.1109/TMSCS.2018.2886851",
"abstract": "Scientific simulations on high performance computing (HPC) platforms generate large quantities of data. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. However, a systematic solution to support these steps has been lacking in the current HPC software ecosystem. To that end, this paper develops SIRIUS, a progressive JPEG-like data management scheme for storing and analyzing big scientific data. It co-designs data decimation, compression, and data storage, taking the hardware characteristics of each storage tier into considerations. With reasonably low overhead, our approach refactors simulation data, using either topological or uniform decimation, into a much smaller, reduced-accuracy base dataset, and a series of deltas that is used to augment the accuracy if needed. The base dataset and deltas are compressed and written to multiple storage tiers. Data saved on different tiers can then be selectively retrieved to restore the level of accuracy that satisfies data analytics. Thus, SIRIUS provides a paradigm shift towards elastic data analytics and enables end users to make trade-offs between analysis speed and accuracy on-the-fly. This paper further develops algorithms to preserve statistics for data decimation, a common requirement for reducing data. We assess the impact of SIRIUS on unstructured triangular meshes, a pervasive data model used in scientific simulations. In particular, we evaluate two realistic use cases: the blob detection in fusion and high-pressure area extraction in computational fluid dynamics.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Scientific simulations on high performance computing (HPC) platforms generate large quantities of data. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. However, a systematic solution to support these steps has been lacking in the current HPC software ecosystem. To that end, this paper develops SIRIUS, a progressive JPEG-like data management scheme for storing and analyzing big scientific data. It co-designs data decimation, compression, and data storage, taking the hardware characteristics of each storage tier into considerations. With reasonably low overhead, our approach refactors simulation data, using either topological or uniform decimation, into a much smaller, reduced-accuracy base dataset, and a series of deltas that is used to augment the accuracy if needed. The base dataset and deltas are compressed and written to multiple storage tiers. Data saved on different tiers can then be selectively retrieved to restore the level of accuracy that satisfies data analytics. Thus, SIRIUS provides a paradigm shift towards elastic data analytics and enables end users to make trade-offs between analysis speed and accuracy on-the-fly. This paper further develops algorithms to preserve statistics for data decimation, a common requirement for reducing data. We assess the impact of SIRIUS on unstructured triangular meshes, a pervasive data model used in scientific simulations. In particular, we evaluate two realistic use cases: the blob detection in fusion and high-pressure area extraction in computational fluid dynamics.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Scientific simulations on high performance computing (HPC) platforms generate large quantities of data. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. However, a systematic solution to support these steps has been lacking in the current HPC software ecosystem. To that end, this paper develops SIRIUS, a progressive JPEG-like data management scheme for storing and analyzing big scientific data. It co-designs data decimation, compression, and data storage, taking the hardware characteristics of each storage tier into considerations. With reasonably low overhead, our approach refactors simulation data, using either topological or uniform decimation, into a much smaller, reduced-accuracy base dataset, and a series of deltas that is used to augment the accuracy if needed. The base dataset and deltas are compressed and written to multiple storage tiers. Data saved on different tiers can then be selectively retrieved to restore the level of accuracy that satisfies data analytics. Thus, SIRIUS provides a paradigm shift towards elastic data analytics and enables end users to make trade-offs between analysis speed and accuracy on-the-fly. This paper further develops algorithms to preserve statistics for data decimation, a common requirement for reducing data. We assess the impact of SIRIUS on unstructured triangular meshes, a pervasive data model used in scientific simulations. In particular, we evaluate two realistic use cases: the blob detection in fusion and high-pressure area extraction in computational fluid dynamics.",
"title": "SIRIUS: Enabling Progressive Data Exploration for Extreme-Scale Scientific Data",
"normalizedTitle": "SIRIUS: Enabling Progressive Data Exploration for Extreme-Scale Scientific Data",
"fno": "08576666",
"hasPdf": true,
"idPrefix": "mc",
"keywords": [
"Data Analysis",
"Computational Modeling",
"Data Models",
"Analytical Models",
"Simulation",
"Feature Extraction",
"Transform Coding",
"High Performance Computing",
"Data Analytics",
"Storage",
"Data Reduction",
"Compression",
"Progressive Refactoring"
],
"authors": [
{
"givenName": "Zhenbo",
"surname": "Qiao",
"fullName": "Zhenbo Qiao",
"affiliation": "Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Tao",
"surname": "Lu",
"fullName": "Tao Lu",
"affiliation": "Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Huizhang",
"surname": "Luo",
"fullName": "Huizhang Luo",
"affiliation": "Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Qing",
"surname": "Liu",
"fullName": "Qing Liu",
"affiliation": "Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Scott",
"surname": "Klasky",
"fullName": "Scott Klasky",
"affiliation": "Oak Ridge National Laboratory, Oak Ridge, TN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Norbert",
"surname": "Podhorszki",
"fullName": "Norbert Podhorszki",
"affiliation": "Oak Ridge National Laboratory, Oak Ridge, TN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jinzhen",
"surname": "Wang",
"fullName": "Jinzhen Wang",
"affiliation": "Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2018-10-01 00:00:00",
"pubType": "trans",
"pages": "900-913",
"year": "2018",
"issn": "2332-7766",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/srds/2016/3513/0/3513a041",
"title": "Sirius: Neural Network Based Probabilistic Assertions for Detecting Silent Data Corruption in Parallel Programs",
"doi": null,
"abstractUrl": "/proceedings-article/srds/2016/3513a041/12OmNAZfxHR",
"parentPublication": {
"id": "proceedings/srds/2016/3513/0",
"title": "2016 IEEE 35th Symposium on Reliable Distributed Systems (SRDS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cloud/2015/7287/0/7287a122",
"title": "Hiding Media Data via Shaders: Enabling Private Sharing in the Clouds",
"doi": null,
"abstractUrl": "/proceedings-article/cloud/2015/7287a122/12OmNBqv2qh",
"parentPublication": {
"id": "proceedings/cloud/2015/7287/0",
"title": "2015 IEEE 8th International Conference on Cloud Computing (CLOUD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cluster/2017/2326/0/2326a058",
"title": "Canopus: A Paradigm Shift Towards Elastic Extreme-Scale Data Analytics on HPC Storage",
"doi": null,
"abstractUrl": "/proceedings-article/cluster/2017/2326a058/12OmNxV4iwK",
"parentPublication": {
"id": "proceedings/cluster/2017/2326/0",
"title": "2017 IEEE International Conference on Cluster Computing (CLUSTER)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2017/3835/0/3835a823",
"title": "Data Prefetching for Large Tiered Storage Systems",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2017/3835a823/12OmNxveNOr",
"parentPublication": {
"id": "proceedings/icdm/2017/3835/0",
"title": "2017 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ipdps/2018/4368/0/436801a348",
"title": "Understanding and Modeling Lossy Compression Schemes on HPC Scientific Data",
"doi": null,
"abstractUrl": "/proceedings-article/ipdps/2018/436801a348/12OmNyxXlpQ",
"parentPublication": {
"id": "proceedings/ipdps/2018/4368/0",
"title": "2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/1997/8262/0/82620205",
"title": "A topology modifying progressive decimation algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/1997/82620205/12OmNzQhP7p",
"parentPublication": {
"id": "proceedings/ieee-vis/1997/8262/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mascots/2019/4950/0/495000a410",
"title": "Profiling the Usage of an Extreme-Scale Archival Storage System",
"doi": null,
"abstractUrl": "/proceedings-article/mascots/2019/495000a410/1gFJsqBu75e",
"parentPublication": {
"id": "proceedings/mascots/2019/4950/0",
"title": "2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mascots/2019/4950/0/495000a125",
"title": "ExaPlan Archive: Data Placement and Provisioning for Large Storage Systems with Archival Tiers",
"doi": null,
"abstractUrl": "/proceedings-article/mascots/2019/495000a125/1gFJupnz4fm",
"parentPublication": {
"id": "proceedings/mascots/2019/4950/0",
"title": "2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2023/01/09380370",
"title": "High-Ratio Lossy Compression: Exploring the Autoencoder to Compress Scientific Data",
"doi": null,
"abstractUrl": "/journal/bd/2023/01/09380370/1s2FYtnQsZq",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/smartiot/2021/4511/0/451100a263",
"title": "Towards Enabling IoT Systems with Edge Intelligence",
"doi": null,
"abstractUrl": "/proceedings-article/smartiot/2021/451100a263/1xDQdWgrcvC",
"parentPublication": {
"id": "proceedings/smartiot/2021/4511/0",
"title": "2021 IEEE International Conference on Smart Internet of Things (SmartIoT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08573843",
"articleId": "17D45XH89oo",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08432098",
"articleId": "17D45VVho5f",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNxvwoOe",
"title": "PrePrints",
"year": "5555",
"issueNum": "01",
"idPrefix": "ts",
"pubType": "journal",
"volume": null,
"label": "PrePrints",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1La0yXKJWes",
"doi": "10.1109/TSE.2023.3250479",
"abstract": "Prior research has shown that public vulnerability systems such as US National Vulnerability Database (NVD) rely on a manual, time-consuming, and error-prone process which has led to inconsistencies and delays in releasing final vulnerability results. This work provides an approach to curate vulnerability reports in real-time and map textual vulnerability reports to machine readable structured vulnerability attribute data. Designed to support the time consuming human analysis done by vulnerability databases, the system leverages the Common Vulnerabilities and Exposures (CVE) list of vulnerabilities and the vulnerability attributes described by the National Institute of Standards and Technology (NIST) Vulnerability Description Ontology (VDO) framework. Our work uses Natural Language Processing (NLP), Machine Learning (ML) and novel Information Theoretical (IT) methods to provide automated techniques for near real-time publishing, and characterization of vulnerabilities using 28 attributes in 5 domains. Experiment results indicate that vulnerabilities can be evaluated up to 95 hours earlier than using manual methods, they can be characterized with F-Measure values over 0.9, and the proposed automated approach could save up to 47% of the time spent for CVE characterization.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Prior research has shown that public vulnerability systems such as US National Vulnerability Database (NVD) rely on a manual, time-consuming, and error-prone process which has led to inconsistencies and delays in releasing final vulnerability results. This work provides an approach to curate vulnerability reports in real-time and map textual vulnerability reports to machine readable structured vulnerability attribute data. Designed to support the time consuming human analysis done by vulnerability databases, the system leverages the Common Vulnerabilities and Exposures (CVE) list of vulnerabilities and the vulnerability attributes described by the National Institute of Standards and Technology (NIST) Vulnerability Description Ontology (VDO) framework. Our work uses Natural Language Processing (NLP), Machine Learning (ML) and novel Information Theoretical (IT) methods to provide automated techniques for near real-time publishing, and characterization of vulnerabilities using 28 attributes in 5 domains. Experiment results indicate that vulnerabilities can be evaluated up to 95 hours earlier than using manual methods, they can be characterized with F-Measure values over 0.9, and the proposed automated approach could save up to 47% of the time spent for CVE characterization.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Prior research has shown that public vulnerability systems such as US National Vulnerability Database (NVD) rely on a manual, time-consuming, and error-prone process which has led to inconsistencies and delays in releasing final vulnerability results. This work provides an approach to curate vulnerability reports in real-time and map textual vulnerability reports to machine readable structured vulnerability attribute data. Designed to support the time consuming human analysis done by vulnerability databases, the system leverages the Common Vulnerabilities and Exposures (CVE) list of vulnerabilities and the vulnerability attributes described by the National Institute of Standards and Technology (NIST) Vulnerability Description Ontology (VDO) framework. Our work uses Natural Language Processing (NLP), Machine Learning (ML) and novel Information Theoretical (IT) methods to provide automated techniques for near real-time publishing, and characterization of vulnerabilities using 28 attributes in 5 domains. Experiment results indicate that vulnerabilities can be evaluated up to 95 hours earlier than using manual methods, they can be characterized with F-Measure values over 0.9, and the proposed automated approach could save up to 47% of the time spent for CVE characterization.",
"title": "Empirical Validation of Automated Vulnerability Curation and Characterization",
"normalizedTitle": "Empirical Validation of Automated Vulnerability Curation and Characterization",
"fno": "10056768",
"hasPdf": true,
"idPrefix": "ts",
"keywords": [
"Security",
"NIST",
"Databases",
"Virtual Machine Monitors",
"Software",
"Feature Extraction",
"Codes",
"Software Vulnerability",
"CVE",
"Vulnerability Characterization",
"NIST Vulnerability Description Ontology"
],
"authors": [
{
"givenName": "Ahmet",
"surname": "Okutan",
"fullName": "Ahmet Okutan",
"affiliation": "Leidos, Reston, VA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Peter",
"surname": "Mell",
"fullName": "Peter Mell",
"affiliation": "National Institute of Standards and Technology, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mehdi",
"surname": "Mirakhorli",
"fullName": "Mehdi Mirakhorli",
"affiliation": "Department of Software Engineering, Rochester Institute of Technology, Rochester, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Igor",
"surname": "Khokhlov",
"fullName": "Igor Khokhlov",
"affiliation": "Sacred Heart University, Fairfield, CT, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Joanna C. S.",
"surname": "Santos",
"fullName": "Joanna C. S. Santos",
"affiliation": "Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Danielle",
"surname": "Gonzalez",
"fullName": "Danielle Gonzalez",
"affiliation": "Department of Software Engineering, Rochester Institute of Technology, Rochester, NY, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Steven",
"surname": "Simmons",
"fullName": "Steven Simmons",
"affiliation": "Department of Software Engineering, Rochester Institute of Technology, Rochester, NY, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2023-02-01 00:00:00",
"pubType": "trans",
"pages": "1-20",
"year": "5555",
"issn": "0098-5589",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icsme/2017/0992/0/0992a125",
"title": "Learning to Predict Severity of Software Vulnerability Using Only Vulnerability Description",
"doi": null,
"abstractUrl": "/proceedings-article/icsme/2017/0992a125/12OmNCyTyr4",
"parentPublication": {
"id": "proceedings/icsme/2017/0992/0",
"title": "2017 IEEE International Conference on Software Maintenance and Evolution (ICSME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cloudcom/2016/1445/0/07830734",
"title": "An Empirical Analysis of Vulnerabilities in Virtualization Technologies",
"doi": null,
"abstractUrl": "/proceedings-article/cloudcom/2016/07830734/12OmNqI04Yh",
"parentPublication": {
"id": "proceedings/cloudcom/2016/1445/0",
"title": "2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icccnt/2013/3926/0/06726782",
"title": "Vulnerability analysis on virtualized environment using FPVA",
"doi": null,
"abstractUrl": "/proceedings-article/icccnt/2013/06726782/12OmNyOHG62",
"parentPublication": {
"id": "proceedings/icccnt/2013/3926/0",
"title": "2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icccri/2016/3951/0/3951a071",
"title": "Assessment of Hypervisor Vulnerabilities",
"doi": null,
"abstractUrl": "/proceedings-article/icccri/2016/3951a071/12OmNyUnEKJ",
"parentPublication": {
"id": "proceedings/icccri/2016/3951/0",
"title": "2016 International Conference on Cloud Computing Research and Innovations (ICCCRI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/trustcom/2021/1658/0/165800a598",
"title": "DeepVuler: A Vulnerability Intelligence Mining System for Open-Source Communities",
"doi": null,
"abstractUrl": "/proceedings-article/trustcom/2021/165800a598/1BBzx2ssxWg",
"parentPublication": {
"id": "proceedings/trustcom/2021/1658/0",
"title": "2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsme/2022/7956/0/795600a175",
"title": "Heterogeneous Vulnerability Report Traceability Recovery by Vulnerability Aspect Matching",
"doi": null,
"abstractUrl": "/proceedings-article/icsme/2022/795600a175/1JeFkv4YcAo",
"parentPublication": {
"id": "proceedings/icsme/2022/7956/0",
"title": "2022 IEEE International Conference on Software Maintenance and Evolution (ICSME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/prdc/2022/8555/0/855500a152",
"title": "A Software Vulnerability Dataset of Large Open Source C/C++ Projects",
"doi": null,
"abstractUrl": "/proceedings-article/prdc/2022/855500a152/1KrgXdXxVXa",
"parentPublication": {
"id": "proceedings/prdc/2022/8555/0",
"title": "2022 IEEE 27th Pacific Rim International Symposium on Dependable Computing (PRDC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iceccs/2019/4646/0/464600a031",
"title": "Joint Prediction of Multiple Vulnerability Characteristics Through Multi-Task Learning",
"doi": null,
"abstractUrl": "/proceedings-article/iceccs/2019/464600a031/1etdTqJ6FIk",
"parentPublication": {
"id": "proceedings/iceccs/2019/4646/0",
"title": "2019 24th International Conference on Engineering of Complex Computer Systems (ICECCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsme/2019/3094/0/309400a135",
"title": "Automated Characterization of Software Vulnerabilities",
"doi": null,
"abstractUrl": "/proceedings-article/icsme/2019/309400a135/1fHlFN7k328",
"parentPublication": {
"id": "proceedings/icsme/2019/3094/0",
"title": "2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/issrew/2020/7735/0/773500a231",
"title": "Vulnerability Analysis as Trustworthiness Evidence in Security Benchmarking: A Case Study on Xen",
"doi": null,
"abstractUrl": "/proceedings-article/issrew/2020/773500a231/1q7ju6Srmog",
"parentPublication": {
"id": "proceedings/issrew/2020/7735/0",
"title": "2020 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "10054429",
"articleId": "1L6HTSw0SUo",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "10057998",
"articleId": "1LbFrIwvwfm",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvTBB87",
"title": "Jan.-March",
"year": "2017",
"issueNum": "01",
"idPrefix": "lt",
"pubType": "journal",
"volume": "10",
"label": "Jan.-March",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwkfAVM",
"doi": "10.1109/TLT.2016.2607747",
"abstract": "Educational data contains valuable information that can be harvested through learning analytics to provide new insights for a better education system. However, sharing or analysis of this data introduce privacy risks for the data subjects, mostly students. Existing work in the learning analytics literature identifies the need for privacy and pose interesting research directions, but fails to apply state of the art privacy protection methods with quantifiable and mathematically rigorous privacy guarantees. This work aims to employ and evaluate such methods on learning analytics by approaching the problem from two perspectives: (1) the data is anonymized and then shared with a learning analytics expert, and (2) the learning analytics expert is given a privacy-preserving interface that governs her access to the data. We develop proof-of-concept implementations of privacy preserving learning analytics tasks using both perspectives and run them on real and synthetic datasets. We also present an experimental study on the trade-off between individuals’ privacy and the accuracy of the learning analytics tasks.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Educational data contains valuable information that can be harvested through learning analytics to provide new insights for a better education system. However, sharing or analysis of this data introduce privacy risks for the data subjects, mostly students. Existing work in the learning analytics literature identifies the need for privacy and pose interesting research directions, but fails to apply state of the art privacy protection methods with quantifiable and mathematically rigorous privacy guarantees. This work aims to employ and evaluate such methods on learning analytics by approaching the problem from two perspectives: (1) the data is anonymized and then shared with a learning analytics expert, and (2) the learning analytics expert is given a privacy-preserving interface that governs her access to the data. We develop proof-of-concept implementations of privacy preserving learning analytics tasks using both perspectives and run them on real and synthetic datasets. We also present an experimental study on the trade-off between individuals’ privacy and the accuracy of the learning analytics tasks.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Educational data contains valuable information that can be harvested through learning analytics to provide new insights for a better education system. However, sharing or analysis of this data introduce privacy risks for the data subjects, mostly students. Existing work in the learning analytics literature identifies the need for privacy and pose interesting research directions, but fails to apply state of the art privacy protection methods with quantifiable and mathematically rigorous privacy guarantees. This work aims to employ and evaluate such methods on learning analytics by approaching the problem from two perspectives: (1) the data is anonymized and then shared with a learning analytics expert, and (2) the learning analytics expert is given a privacy-preserving interface that governs her access to the data. We develop proof-of-concept implementations of privacy preserving learning analytics tasks using both perspectives and run them on real and synthetic datasets. We also present an experimental study on the trade-off between individuals’ privacy and the accuracy of the learning analytics tasks.",
"title": "Privacy-Preserving Learning Analytics: Challenges and Techniques",
"normalizedTitle": "Privacy-Preserving Learning Analytics: Challenges and Techniques",
"fno": "07563858",
"hasPdf": true,
"idPrefix": "lt",
"keywords": [
"Data Privacy",
"Privacy",
"Education",
"Big Data",
"Context",
"Protection",
"Data Mining",
"Data Privacy",
"Learning Analytics",
"Learning Management Systems"
],
"authors": [
{
"givenName": "Mehmet Emre",
"surname": "Gursoy",
"fullName": "Mehmet Emre Gursoy",
"affiliation": "College of Computing, Georgia Institute of Technology, Atlanta, GA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ali",
"surname": "Inan",
"fullName": "Ali Inan",
"affiliation": "Computer Engineering Department, Adana Science and Technology University, Adana, Turkey",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Mehmet Ercan",
"surname": "Nergiz",
"fullName": "Mehmet Ercan Nergiz",
"affiliation": "Acadsoft Research, Gaziantep, Turkey",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yucel",
"surname": "Saygin",
"fullName": "Yucel Saygin",
"affiliation": "Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "01",
"pubDate": "2017-01-01 00:00:00",
"pubType": "trans",
"pages": "68-81",
"year": "2017",
"issn": "1939-1382",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/cloud/2017/1993/0/1993a342",
"title": "Privacy-Preserving Multi-Party Analytics over Arbitrarily Partitioned Data",
"doi": null,
"abstractUrl": "/proceedings-article/cloud/2017/1993a342/12OmNAle704",
"parentPublication": {
"id": "proceedings/cloud/2017/1993/0",
"title": "2017 IEEE 10th International Conference on Cloud Computing (CLOUD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ladc/2016/5120/0/5120a164",
"title": "Challenges on Anonymity, Privacy, and Big Data",
"doi": null,
"abstractUrl": "/proceedings-article/ladc/2016/5120a164/12OmNBO3Kjc",
"parentPublication": {
"id": "proceedings/ladc/2016/5120/0",
"title": "2016 Seventh Latin-American Symposium on Dependable Computing (LADC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ccgrid/2017/6611/0/07973820",
"title": "PRIVAaaS: Privacy Approach for a Distributed Cloud-Based Data Analytics Platforms",
"doi": null,
"abstractUrl": "/proceedings-article/ccgrid/2017/07973820/12OmNBqdr02",
"parentPublication": {
"id": "proceedings/ccgrid/2017/6611/0",
"title": "2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/spw/2013/0458/0/06565224",
"title": "Privacy Preserving Data Analytics for Smart Homes",
"doi": null,
"abstractUrl": "/proceedings-article/spw/2013/06565224/12OmNC36tOK",
"parentPublication": {
"id": "proceedings/spw/2013/0458/0",
"title": "2013 IEEE Security and Privacy Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/2016/0679/0/07543859",
"title": "Big Data Analytics: Security and privacy challenges",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/2016/07543859/12OmNCeK2kr",
"parentPublication": {
"id": "proceedings/iscc/2016/0679/0",
"title": "2016 IEEE Symposium on Computers and Communication (ISCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigdata-congress/2013/5006/0/06597142",
"title": "Challenges of Privacy Protection in Big Data Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/bigdata-congress/2013/06597142/12OmNxEjXZw",
"parentPublication": {
"id": "proceedings/bigdata-congress/2013/5006/0",
"title": "2013 IEEE International Congress on Big Data (BigData Congress)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2017/3800/0/3800a992",
"title": "Privacy-Preserving Big Data Stream Mining: Opportunities, Challenges, Directions",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2017/3800a992/12OmNyKJie6",
"parentPublication": {
"id": "proceedings/icdmw/2017/3800/0",
"title": "2017 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ucc/2015/5697/0/5697a281",
"title": "An Efficient and Privacy-Preserving Similarity Evaluation for Big Data Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/ucc/2015/5697a281/12OmNzV70OH",
"parentPublication": {
"id": "proceedings/ucc/2015/5697/0",
"title": "2015 IEEE/ACM 8th International Conference on Utility and Cloud Computing (UCC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ic/2018/02/mic2018020042",
"title": "Toward Practical Privacy-Preserving Analytics for IoT and Cloud-Based Healthcare Systems",
"doi": null,
"abstractUrl": "/magazine/ic/2018/02/mic2018020042/13rRUxC0Ssn",
"parentPublication": {
"id": "mags/ic",
"title": "IEEE Internet Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/soca/2019/5411/0/541100a176",
"title": "D&D: A Distributed and Disposable Approach to Privacy Preserving Data Analytics in User-Centric Healthcare",
"doi": null,
"abstractUrl": "/proceedings-article/soca/2019/541100a176/1gysLfe1Gvu",
"parentPublication": {
"id": "proceedings/soca/2019/5411/0",
"title": "2019 IEEE 12th Conference on Service-Oriented Computing and Applications (SOCA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07738510",
"articleId": "13rRUwInvFu",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07782787",
"articleId": "13rRUxBJhCp",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNzwHveF",
"title": "Feb.",
"year": "2020",
"issueNum": "01",
"idPrefix": "nt",
"pubType": "journal",
"volume": "28",
"label": "Feb.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1fPU2oFeoBa",
"doi": "10.1109/TNET.2019.2951713",
"abstract": "We study a problem of privacy-preserving mechanism design. A data collector wants to obtain data from individuals to perform some computations. To relieve the privacy threat to the contributors, the data collector adopts a privacy-preserving mechanism by adding random noise to the computation result, at the cost of reduced accuracy. Individuals decide whether to contribute data when faced with the privacy issue. Due to the intrinsic uncertainty in privacy protection, we model individuals' privacy-related decision using Prospect Theory. Such a theory more accurately models individuals' behavior under uncertainty than the traditional expected utility theory, whose prediction always deviates from practical human behavior. We show that the data collector's utility maximization problem involves a polynomial of high and fractional order, the root of which is difficult to compute analytically. We get around this issue by considering a large population approximation, and obtain a closed-form solution that well approximates the precise solution. We discover that the data collector who considers the more realistic Prospect Theory based individual decision modeling would adopt a more conservative privacy-preserving mechanism, compared with the case based on the expected utility theory modeling. We also study the impact of Prospect Theory parameters, and concludes that more loss-averse or risk-seeking individuals will trigger a more conservative mechanism. When individuals have different Prospect Theory parameters, simulations demonstrate that the privacy protection first becomes stronger and then becomes weaker as the heterogeneity increases from a low value to a high one.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We study a problem of privacy-preserving mechanism design. A data collector wants to obtain data from individuals to perform some computations. To relieve the privacy threat to the contributors, the data collector adopts a privacy-preserving mechanism by adding random noise to the computation result, at the cost of reduced accuracy. Individuals decide whether to contribute data when faced with the privacy issue. Due to the intrinsic uncertainty in privacy protection, we model individuals' privacy-related decision using Prospect Theory. Such a theory more accurately models individuals' behavior under uncertainty than the traditional expected utility theory, whose prediction always deviates from practical human behavior. We show that the data collector's utility maximization problem involves a polynomial of high and fractional order, the root of which is difficult to compute analytically. We get around this issue by considering a large population approximation, and obtain a closed-form solution that well approximates the precise solution. We discover that the data collector who considers the more realistic Prospect Theory based individual decision modeling would adopt a more conservative privacy-preserving mechanism, compared with the case based on the expected utility theory modeling. We also study the impact of Prospect Theory parameters, and concludes that more loss-averse or risk-seeking individuals will trigger a more conservative mechanism. When individuals have different Prospect Theory parameters, simulations demonstrate that the privacy protection first becomes stronger and then becomes weaker as the heterogeneity increases from a low value to a high one.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We study a problem of privacy-preserving mechanism design. A data collector wants to obtain data from individuals to perform some computations. To relieve the privacy threat to the contributors, the data collector adopts a privacy-preserving mechanism by adding random noise to the computation result, at the cost of reduced accuracy. Individuals decide whether to contribute data when faced with the privacy issue. Due to the intrinsic uncertainty in privacy protection, we model individuals' privacy-related decision using Prospect Theory. Such a theory more accurately models individuals' behavior under uncertainty than the traditional expected utility theory, whose prediction always deviates from practical human behavior. We show that the data collector's utility maximization problem involves a polynomial of high and fractional order, the root of which is difficult to compute analytically. We get around this issue by considering a large population approximation, and obtain a closed-form solution that well approximates the precise solution. We discover that the data collector who considers the more realistic Prospect Theory based individual decision modeling would adopt a more conservative privacy-preserving mechanism, compared with the case based on the expected utility theory modeling. We also study the impact of Prospect Theory parameters, and concludes that more loss-averse or risk-seeking individuals will trigger a more conservative mechanism. When individuals have different Prospect Theory parameters, simulations demonstrate that the privacy protection first becomes stronger and then becomes weaker as the heterogeneity increases from a low value to a high one.",
"title": "Prospect Theoretic Analysis of Privacy-Preserving Mechanism",
"normalizedTitle": "Prospect Theoretic Analysis of Privacy-Preserving Mechanism",
"fno": "08935104",
"hasPdf": true,
"idPrefix": "nt",
"keywords": [
"Data Privacy",
"Decision Making",
"Optimisation",
"Random Noise",
"Utility Theory",
"Prospect Theory Parameters",
"Privacy Protection",
"Privacy Preserving Mechanism Design",
"Data Collector",
"Privacy Threat",
"Computation Result",
"Privacy Issue",
"Model Individuals",
"Traditional Expected Utility Theory",
"Realistic Prospect Theory",
"Individual Decision Modeling",
"Conservative Privacy Preserving Mechanism",
"Expected Utility Theory Modeling",
"Conservative Mechanism",
"Prospect Theoretic Analysis",
"Privacy",
"Uncertainty",
"Computational Modeling",
"Data Models",
"Differential Privacy",
"Economics",
"Privacy Protection",
"Italic Xmlns Ali Http Www Niso Org Schemas Ali 1 0 Xmlns Mml Http Www W 3 Org 1998 Math Math ML Xmlns Xlink Http Www W 3 Org 1999 Xlink Xmlns Xsi Http Www W 3 Org 2001 XML Schema Instance Ε Italic Differential Privacy",
"Prospect Theory"
],
"authors": [
{
"givenName": "Guocheng",
"surname": "Liao",
"fullName": "Guocheng Liao",
"affiliation": "Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xu",
"surname": "Chen",
"fullName": "Xu Chen",
"affiliation": "School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jianwei",
"surname": "Huang",
"fullName": "Jianwei Huang",
"affiliation": "Department of Information Engineering, The Chinese University of Hong Kong, Hong Kong",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2020-01-01 00:00:00",
"pubType": "trans",
"pages": "71-83",
"year": "2020",
"issn": "1063-6692",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/mass/2022/7180/0/718000a108",
"title": "An Uncertain Graph Privacy Preserving Scheme Based on Node Similarity in Social Networks",
"doi": null,
"abstractUrl": "/proceedings-article/mass/2022/718000a108/1JeEj3947W8",
"parentPublication": {
"id": "proceedings/mass/2022/7180/0",
"title": "2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2022/5099/0/509900a528",
"title": "Heterogeneous Graph Neural Network for Privacy-Preserving Recommendation",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2022/509900a528/1KpCAUHCpS8",
"parentPublication": {
"id": "proceedings/icdm/2022/5099/0",
"title": "2022 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/nt/5555/01/10083154",
"title": "Privacy Protection Under Incomplete Social and Data Correlation Information",
"doi": null,
"abstractUrl": "/journal/nt/5555/01/10083154/1LSKvLX2vFm",
"parentPublication": {
"id": "trans/nt",
"title": "IEEE/ACM Transactions on Networking",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cecit/2022/3197/0/319700a285",
"title": "A Privacy-Preserving Mechanism Based on Privacy Situation Awareness for Information Sharing in OSNs",
"doi": null,
"abstractUrl": "/proceedings-article/cecit/2022/319700a285/1M66Kw8GJ2w",
"parentPublication": {
"id": "proceedings/cecit/2022/3197/0",
"title": "2022 3rd International Conference on Electronics, Communications and Information Technology (CECIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2021/08/08949708",
"title": "Privacy-Preserving Stochastic Gradual Learning",
"doi": null,
"abstractUrl": "/journal/tk/2021/08/08949708/1gi7sk2dtZe",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/nt/2020/04/09119841",
"title": "Social-Aware Privacy-Preserving Mechanism for Correlated Data",
"doi": null,
"abstractUrl": "/journal/nt/2020/04/09119841/1kJzeSUJHkA",
"parentPublication": {
"id": "trans/nt",
"title": "IEEE/ACM Transactions on Networking",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2023/01/09410446",
"title": "Privacy-Preserving Travel Time Prediction With Uncertainty Using GPS Trace Data",
"doi": null,
"abstractUrl": "/journal/tm/2023/01/09410446/1sYYsvkf0By",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/bd/2023/01/09511566",
"title": "Noiseless Privacy: Definition, Guarantees, and Applications",
"doi": null,
"abstractUrl": "/journal/bd/2023/01/09511566/1vYRCou260o",
"parentPublication": {
"id": "trans/bd",
"title": "IEEE Transactions on Big Data",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2022/11/09626571",
"title": "A Decentralized Mechanism Based on Differential Privacy for Privacy-Preserving Computation in Smart Grid",
"doi": null,
"abstractUrl": "/journal/tc/2022/11/09626571/1yNdbrbqWT6",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/nana/2021/4158/0/415800a373",
"title": "The Trade-off Between Privacy and Utility in Local Differential Privacy",
"doi": null,
"abstractUrl": "/proceedings-article/nana/2021/415800a373/1zdPQaiTywg",
"parentPublication": {
"id": "proceedings/nana/2021/4158/0",
"title": "2021 International Conference on Networking and Network Applications (NaNA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08932384",
"articleId": "1fJgom6W9oY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08930630",
"articleId": "1fEhGNqJm2k",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwE9On1",
"title": "April-June",
"year": "2020",
"issueNum": "02",
"idPrefix": "mu",
"pubType": "magazine",
"volume": "27",
"label": "April-June",
"downloadables": {
"hasCover": true,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1kBgRBPxFn2",
"doi": "10.1109/MMUL.2020.2993162",
"abstract": "With the explosion of multimedia data, machine learning applications are proliferating. Privacy concerns have recently resurfaced, due to a few prominent incidents of user data leakage, which divulged sensitive information to other people. Multimedia data platform providers––social networks, their affiliates or governments with access to users’ content––use algorithms to profile users by extracting or inferring demographic information, personality traits, relationships, opinions, and beliefs. These results, in turn, feed algorithms for targeted advertising but also for personalized content recommendation to maximize user engagement. While this is ostensibly for users’ benefit, they have serious privacy implications. We highlight this new problem of privacy protection against machines in contrast to the traditional problem of privacy protection against humans. We briefly touch upon our initial solution, a human-sensitivity-aware image perturbation model, which is able to modify the computational classification results of sensitive attributes while preserving the remaining attributes. We then point to many exciting open problems in this new area.",
"abstracts": [
{
"abstractType": "Regular",
"content": "With the explosion of multimedia data, machine learning applications are proliferating. Privacy concerns have recently resurfaced, due to a few prominent incidents of user data leakage, which divulged sensitive information to other people. Multimedia data platform providers––social networks, their affiliates or governments with access to users’ content––use algorithms to profile users by extracting or inferring demographic information, personality traits, relationships, opinions, and beliefs. These results, in turn, feed algorithms for targeted advertising but also for personalized content recommendation to maximize user engagement. While this is ostensibly for users’ benefit, they have serious privacy implications. We highlight this new problem of privacy protection against machines in contrast to the traditional problem of privacy protection against humans. We briefly touch upon our initial solution, a human-sensitivity-aware image perturbation model, which is able to modify the computational classification results of sensitive attributes while preserving the remaining attributes. We then point to many exciting open problems in this new area.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "With the explosion of multimedia data, machine learning applications are proliferating. Privacy concerns have recently resurfaced, due to a few prominent incidents of user data leakage, which divulged sensitive information to other people. Multimedia data platform providers––social networks, their affiliates or governments with access to users’ content––use algorithms to profile users by extracting or inferring demographic information, personality traits, relationships, opinions, and beliefs. These results, in turn, feed algorithms for targeted advertising but also for personalized content recommendation to maximize user engagement. While this is ostensibly for users’ benefit, they have serious privacy implications. We highlight this new problem of privacy protection against machines in contrast to the traditional problem of privacy protection against humans. We briefly touch upon our initial solution, a human-sensitivity-aware image perturbation model, which is able to modify the computational classification results of sensitive attributes while preserving the remaining attributes. We then point to many exciting open problems in this new area.",
"title": "Multimedia Data Privacy Against Machines",
"normalizedTitle": "Multimedia Data Privacy Against Machines",
"fno": "09115949",
"hasPdf": true,
"idPrefix": "mu",
"keywords": [
"Advertising Data Processing",
"Data Protection",
"Learning Artificial Intelligence",
"Multimedia Computing",
"Recommender Systems",
"Social Networking Online",
"Multimedia Data Privacy",
"Machine Learning Applications",
"Sensitive Information",
"Demographic Information",
"Personality Traits",
"Feed Algorithms",
"Targeted Advertising",
"Personalized Content Recommendation",
"User Engagement",
"Serious Privacy Implications",
"Privacy Protection",
"Human Sensitivity Aware Image Perturbation Model",
"Computational Classification Results",
"Sensitive Attributes",
"Multimedia Data Platform Providers",
"Social Networks",
"Data Privacy",
"Streaming Media",
"Privacy",
"Social Networking Online",
"Machine Learning Algorithms",
"Machine Learning",
"Government"
],
"authors": [
{
"givenName": "Mohan",
"surname": "Kankanhalli",
"fullName": "Mohan Kankanhalli",
"affiliation": "National University of Singapore",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2020-04-01 00:00:00",
"pubType": "mags",
"pages": "5-7",
"year": "2020",
"issn": "1070-986X",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "mags/it/2018/03/mit2018030073",
"title": "Understanding Privacy Violations in Big Data Systems",
"doi": null,
"abstractUrl": "/magazine/it/2018/03/mit2018030073/13rRUwkfAVE",
"parentPublication": {
"id": "mags/it",
"title": "IT Professional",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440807",
"title": "GraphProtector: A Visual Interface for Employing and Assessing Multiple Privacy Preserving Graph Algorithms",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440807/17D45WrVg0m",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mlbdbi/2021/1790/0/179000a324",
"title": "Research on Enterprise Information Security and Privacy Protection in Big Data Environment",
"doi": null,
"abstractUrl": "/proceedings-article/mlbdbi/2021/179000a324/1BQiG9MiFTW",
"parentPublication": {
"id": "proceedings/mlbdbi/2021/1790/0",
"title": "2021 3rd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/oj/2022/01/09933823",
"title": "Efficient Video Privacy Protection Against Malicious Face Recognition Models",
"doi": null,
"abstractUrl": "/journal/oj/2022/01/09933823/1HWLF6OcTTi",
"parentPublication": {
"id": "trans/oj",
"title": "IEEE Open Journal of the Computer Society",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mlise/2022/9246/0/924600a389",
"title": "APPFed: A Hybrid Privacy-Preserving Framework for Federated Learning over Sensitive Data",
"doi": null,
"abstractUrl": "/proceedings-article/mlise/2022/924600a389/1Ik8SDE0Ehy",
"parentPublication": {
"id": "proceedings/mlise/2022/9246/0",
"title": "2022 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/tps-isa/2022/7408/0/740800a055",
"title": "Privacy Challenges and Solutions for Image Data Sharing",
"doi": null,
"abstractUrl": "/proceedings-article/tps-isa/2022/740800a055/1Lxf5BCthxC",
"parentPublication": {
"id": "proceedings/tps-isa/2022/7408/0",
"title": "2022 IEEE 4th International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS-ISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icinc/2022/0969/0/096900a163",
"title": "Social Network Data Publishing Model Satisfying Differential Privacy",
"doi": null,
"abstractUrl": "/proceedings-article/icinc/2022/096900a163/1M6726tVIFq",
"parentPublication": {
"id": "proceedings/icinc/2022/0969/0",
"title": "2022 International Conference on Informatics, Networking and Computing (ICINC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mlbdbi/2020/9638/0/963800a222",
"title": "Anonymous Privacy Protection Algorithm Based on Sensitive Attribute Classification",
"doi": null,
"abstractUrl": "/proceedings-article/mlbdbi/2020/963800a222/1rxhzPo24vu",
"parentPublication": {
"id": "proceedings/mlbdbi/2020/9638/0",
"title": "2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigdatasecurity-hpsc-ids/2021/3927/0/392700a151",
"title": "Overview of Privacy Protection Data Release Anonymity Technology",
"doi": null,
"abstractUrl": "/proceedings-article/bigdatasecurity-hpsc-ids/2021/392700a151/1uPzd59Xvry",
"parentPublication": {
"id": "proceedings/bigdatasecurity-hpsc-ids/2021/3927/0",
"title": "2021 7th IEEE Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/01/09448513",
"title": "NetFense: Adversarial Defenses Against Privacy Attacks on Neural Networks for Graph Data",
"doi": null,
"abstractUrl": "/journal/tk/2023/01/09448513/1ugDQeDTD3O",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09115805",
"articleId": "1kBgPL6twSk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09069265",
"articleId": "1j4GnbGD54I",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1BtbeKGFJzW",
"title": "April",
"year": "2022",
"issueNum": "04",
"idPrefix": "tp",
"pubType": "journal",
"volume": "44",
"label": "April",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1nuwlh8UeNa",
"doi": "10.1109/TPAMI.2020.3026709",
"abstract": "We investigate privacy-preserving, video-based action recognition in deep learning, a problem with growing importance in smart camera applications. A novel adversarial training framework is formulated to learn an anonymization transform for input videos such that the trade-off between target utility task performance and the associated privacy budgets is explicitly optimized on the anonymized videos. Notably, the privacy budget, often defined and measured in task-driven contexts, cannot be reliably indicated using any single model performance because strong protection of privacy should sustain against any malicious model that tries to steal private information. To tackle this problem, we propose two new optimization strategies of model restarting and model ensemble to achieve stronger universal privacy protection against any attacker models. Extensive experiments have been carried out and analyzed. On the other hand, given few public datasets available with both utility and privacy labels, the data-driven (supervised) learning cannot exert its full power on this task. We first discuss an innovative heuristic of cross-dataset training and evaluation, enabling the use of multiple single-task datasets (one with target task labels and the other with privacy labels) in our problem. To further address this dataset challenge, we have constructed a new dataset, termed PA-HMDB51, with both target task labels (action) and selected privacy attributes (skin color, face, gender, nudity, and relationship) annotated on a per-frame basis. This first-of-its-kind video dataset and evaluation protocol can greatly facilitate visual privacy research and open up other opportunities. Our codes, models, and the PA-HMDB51 dataset are available at: <italic><uri>https://github.com/VITA-Group/PA-HMDB51</uri></italic>",
"abstracts": [
{
"abstractType": "Regular",
"content": "We investigate privacy-preserving, video-based action recognition in deep learning, a problem with growing importance in smart camera applications. A novel adversarial training framework is formulated to learn an anonymization transform for input videos such that the trade-off between target utility task performance and the associated privacy budgets is explicitly optimized on the anonymized videos. Notably, the privacy budget, often defined and measured in task-driven contexts, cannot be reliably indicated using any single model performance because strong protection of privacy should sustain against any malicious model that tries to steal private information. To tackle this problem, we propose two new optimization strategies of model restarting and model ensemble to achieve stronger universal privacy protection against any attacker models. Extensive experiments have been carried out and analyzed. On the other hand, given few public datasets available with both utility and privacy labels, the data-driven (supervised) learning cannot exert its full power on this task. We first discuss an innovative heuristic of cross-dataset training and evaluation, enabling the use of multiple single-task datasets (one with target task labels and the other with privacy labels) in our problem. To further address this dataset challenge, we have constructed a new dataset, termed PA-HMDB51, with both target task labels (action) and selected privacy attributes (skin color, face, gender, nudity, and relationship) annotated on a per-frame basis. This first-of-its-kind video dataset and evaluation protocol can greatly facilitate visual privacy research and open up other opportunities. Our codes, models, and the PA-HMDB51 dataset are available at: <italic><uri>https://github.com/VITA-Group/PA-HMDB51</uri></italic>",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We investigate privacy-preserving, video-based action recognition in deep learning, a problem with growing importance in smart camera applications. A novel adversarial training framework is formulated to learn an anonymization transform for input videos such that the trade-off between target utility task performance and the associated privacy budgets is explicitly optimized on the anonymized videos. Notably, the privacy budget, often defined and measured in task-driven contexts, cannot be reliably indicated using any single model performance because strong protection of privacy should sustain against any malicious model that tries to steal private information. To tackle this problem, we propose two new optimization strategies of model restarting and model ensemble to achieve stronger universal privacy protection against any attacker models. Extensive experiments have been carried out and analyzed. On the other hand, given few public datasets available with both utility and privacy labels, the data-driven (supervised) learning cannot exert its full power on this task. We first discuss an innovative heuristic of cross-dataset training and evaluation, enabling the use of multiple single-task datasets (one with target task labels and the other with privacy labels) in our problem. To further address this dataset challenge, we have constructed a new dataset, termed PA-HMDB51, with both target task labels (action) and selected privacy attributes (skin color, face, gender, nudity, and relationship) annotated on a per-frame basis. This first-of-its-kind video dataset and evaluation protocol can greatly facilitate visual privacy research and open up other opportunities. Our codes, models, and the PA-HMDB51 dataset are available at: https://github.com/VITA-Group/PA-HMDB51",
"title": "Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset",
"normalizedTitle": "Privacy-Preserving Deep Action Recognition: An Adversarial Learning Framework and A New Dataset",
"fno": "09207852",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Data Privacy",
"Image Representation",
"Learning Artificial Intelligence",
"Video Signal Processing",
"Associated Privacy Budgets",
"Anonymized Videos",
"Privacy Budget",
"Task Driven Contexts",
"Single Model Performance",
"Malicious Model",
"Optimization Strategies",
"Stronger Universal Privacy Protection",
"Attacker Models",
"Public Datasets",
"Privacy Labels",
"Cross Dataset Training",
"Single Task Datasets",
"Target Task Labels",
"Dataset Challenge",
"New Dataset",
"Selected Privacy",
"First Of Its Kind Video Dataset",
"Visual Privacy Research",
"PA HMDB 51 Dataset",
"Privacy Preserving Deep Action Recognition",
"Adversarial Learning Framework",
"Video Based Action Recognition",
"Deep Learning",
"Smart Camera Applications",
"Novel Adversarial Training Framework",
"Anonymization",
"Input Videos",
"Trade Off Between Target Utility Task Performance",
"Privacy",
"Data Privacy",
"Videos",
"Task Analysis",
"Visualization",
"Cryptography",
"Training",
"Visual Privacy",
"Action Recognition",
"Privacy Preserving Learning",
"Adversarial Learning"
],
"authors": [
{
"givenName": "Zhenyu",
"surname": "Wu",
"fullName": "Zhenyu Wu",
"affiliation": "Department of Computer Science and Engineering, Texas A&M University, College Station, TX, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Haotao",
"surname": "Wang",
"fullName": "Haotao Wang",
"affiliation": "Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zhaowen",
"surname": "Wang",
"fullName": "Zhaowen Wang",
"affiliation": "Adobe Research, San Jose, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Hailin",
"surname": "Jin",
"fullName": "Hailin Jin",
"affiliation": "Adobe Research, San Jose, CA, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zhangyang",
"surname": "Wang",
"fullName": "Zhangyang Wang",
"affiliation": "Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2022-04-01 00:00:00",
"pubType": "trans",
"pages": "2126-2139",
"year": "2022",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/re/2016/4121/0/4121a256",
"title": "Privacy Requirements: Findings and Lessons Learned in Developing a Privacy Platform",
"doi": null,
"abstractUrl": "/proceedings-article/re/2016/4121a256/12OmNxzMnUi",
"parentPublication": {
"id": "proceedings/re/2016/4121/0",
"title": "2016 IEEE 24th International Requirements Engineering Conference (RE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2019/1975/0/197500a791",
"title": "Learning Privacy Preserving Encodings Through Adversarial Training",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2019/197500a791/18j8G25MHWU",
"parentPublication": {
"id": "proceedings/wacv/2019/1975/0",
"title": "2019 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2021/3176/0/09666933",
"title": "Adversarial Mask Generation for Preserving Visual Privacy",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2021/09666933/1A6BtZP2NNu",
"parentPublication": {
"id": "proceedings/fg/2021/3176/0",
"title": "2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09802921",
"title": "Privacy-Preserving Analytics on Decentralized Social Graphs: The Case of Eigendecomposition",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09802921/1Eo1t8Q5Daw",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600u0132",
"title": "SPAct: Self-supervised Privacy Preservation for Action Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600u0132/1H0NQ1Rb5aE",
"parentPublication": {
"id": "proceedings/cvpr/2022/6946/0",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/5555/01/10066198",
"title": "RoPriv: Road Network-aware Privacy-preserving Framework in Spatial Crowdsourcing",
"doi": null,
"abstractUrl": "/journal/tm/5555/01/10066198/1LoWyYYDCN2",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2019/2506/0/250600a001",
"title": "Privacy-Preserving Action Recognition Using Coded Aperture Videos",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2019/250600a001/1iTvt9n9FaE",
"parentPublication": {
"id": "proceedings/cvprw/2019/2506/0",
"title": "2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/04/09099993",
"title": "Privacy-Preserving Feature Extraction via Adversarial Training",
"doi": null,
"abstractUrl": "/journal/tk/2022/04/09099993/1k93iV0Fg4M",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2021/12/09108400",
"title": "iTAM: Bilateral Privacy-Preserving Task Assignment for Mobile Crowdsensing",
"doi": null,
"abstractUrl": "/journal/tm/2021/12/09108400/1koLbGlOPa8",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2022/12/09432741",
"title": "Location Privacy-Preserving Task Recommendation With Geometric Range Query in Mobile Crowdsensing",
"doi": null,
"abstractUrl": "/journal/tm/2022/12/09432741/1tG8fZcVuec",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09206116",
"articleId": "1npxzECOhvG",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09216040",
"articleId": "1nJsCLJJPSo",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1BtbgeysHCw",
"name": "ttp202204-09207852s1-supp1-3026709.pdf",
"location": "https://www.computer.org/csdl/api/v1/extra/ttp202204-09207852s1-supp1-3026709.pdf",
"extension": "pdf",
"size": "11.1 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "1qL5hsvvVkc",
"title": "Feb.",
"year": "2021",
"issueNum": "02",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Feb.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1nTqzVqnWU0",
"doi": "10.1109/TVCG.2020.3030370",
"abstract": "Tax evasion is a serious economic problem for many countries, as it can undermine the government's tax system and lead to an unfair business competition environment. Recent research has applied data analytics techniques to analyze and detect tax evasion behaviors of individual taxpayers. However, they have failed to support the analysis and exploration of the related party transaction tax evasion (RPTTE) behaviors (e.g., transfer pricing), where a group of taxpayers is involved. In this paper, we present TaxThemis, an interactive visual analytics system to help tax officers mine and explore suspicious tax evasion groups through analyzing heterogeneous tax-related data. A taxpayer network is constructed and fused with the respective trade network to detect suspicious RPTTE groups. Rich visualizations are designed to facilitate the exploration and investigation of suspicious transactions between related taxpayers with profit and topological data analysis. Specifically, we propose a calendar heatmap with a carefully-designed encoding scheme to intuitively show the evidence of transferring revenue through related party transactions. We demonstrate the usefulness and effectiveness of TaxThemis through two case studies on real-world tax-related data and interviews with domain experts.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Tax evasion is a serious economic problem for many countries, as it can undermine the government's tax system and lead to an unfair business competition environment. Recent research has applied data analytics techniques to analyze and detect tax evasion behaviors of individual taxpayers. However, they have failed to support the analysis and exploration of the related party transaction tax evasion (RPTTE) behaviors (e.g., transfer pricing), where a group of taxpayers is involved. In this paper, we present TaxThemis, an interactive visual analytics system to help tax officers mine and explore suspicious tax evasion groups through analyzing heterogeneous tax-related data. A taxpayer network is constructed and fused with the respective trade network to detect suspicious RPTTE groups. Rich visualizations are designed to facilitate the exploration and investigation of suspicious transactions between related taxpayers with profit and topological data analysis. Specifically, we propose a calendar heatmap with a carefully-designed encoding scheme to intuitively show the evidence of transferring revenue through related party transactions. We demonstrate the usefulness and effectiveness of TaxThemis through two case studies on real-world tax-related data and interviews with domain experts.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Tax evasion is a serious economic problem for many countries, as it can undermine the government's tax system and lead to an unfair business competition environment. Recent research has applied data analytics techniques to analyze and detect tax evasion behaviors of individual taxpayers. However, they have failed to support the analysis and exploration of the related party transaction tax evasion (RPTTE) behaviors (e.g., transfer pricing), where a group of taxpayers is involved. In this paper, we present TaxThemis, an interactive visual analytics system to help tax officers mine and explore suspicious tax evasion groups through analyzing heterogeneous tax-related data. A taxpayer network is constructed and fused with the respective trade network to detect suspicious RPTTE groups. Rich visualizations are designed to facilitate the exploration and investigation of suspicious transactions between related taxpayers with profit and topological data analysis. Specifically, we propose a calendar heatmap with a carefully-designed encoding scheme to intuitively show the evidence of transferring revenue through related party transactions. We demonstrate the usefulness and effectiveness of TaxThemis through two case studies on real-world tax-related data and interviews with domain experts.",
"title": "<italic>TaxThemis</italic>: Interactive Mining and Exploration of Suspicious Tax Evasion Groups",
"normalizedTitle": "TaxThemis: Interactive Mining and Exploration of Suspicious Tax Evasion Groups",
"fno": "09222068",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Analysis",
"Data Mining",
"Data Visualisation",
"Profitability",
"Taxation",
"Tax Themis",
"Interactive Mining",
"Government",
"Unfair Business Competition Environment",
"Data Analytics",
"Related Party Transaction Tax Evasion",
"Interactive Visual Analytics System",
"Heterogeneous Tax Related Data",
"Taxpayer Network",
"Suspicious RPTTE Groups",
"Suspicious Transactions",
"Related Taxpayers",
"Related Party Transactions",
"Real World Tax Related Data",
"Suspicious Tax Evasion Group Mining",
"Finance",
"Data Visualization",
"Visual Analytics",
"Bars",
"Network Topology",
"Investment",
"Visual Analytics",
"Tax Network",
"Tax Evasion Detection",
"Anomaly Detection",
"Multidimensional Data"
],
"authors": [
{
"givenName": "Yating",
"surname": "Lin",
"fullName": "Yating Lin",
"affiliation": "MOEKLINNS LabXi 'an Jiaotong University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Kamkwai",
"surname": "Wong",
"fullName": "Kamkwai Wong",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yong",
"surname": "Wang",
"fullName": "Yong Wang",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Rong",
"surname": "Zhang",
"fullName": "Rong Zhang",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Bo",
"surname": "Dong",
"fullName": "Bo Dong",
"affiliation": "National Engineering Lab of Big Data Analytics, Xi'an Jiaotong University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Huamin",
"surname": "Qu",
"fullName": "Huamin Qu",
"affiliation": "Hong Kong University of Science and Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Qinghua",
"surname": "Zheng",
"fullName": "Qinghua Zheng",
"affiliation": "MOEKLINNS LabXi 'an Jiaotong University",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "02",
"pubDate": "2021-02-01 00:00:00",
"pubType": "trans",
"pages": "849-859",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icde/2017/6543/0/6543a025",
"title": "Mining suspicious tax evasion groups in big data (extended abstract)",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2017/6543a025/12OmNAFFdHM",
"parentPublication": {
"id": "proceedings/icde/2017/6543/0",
"title": "2017 IEEE 33rd International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2016/10/07487062",
"title": "Mining Suspicious Tax Evasion Groups in Big Data",
"doi": null,
"abstractUrl": "/journal/tk/2016/10/07487062/13rRUwI5Ugv",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi/2018/7325/0/732500a758",
"title": "Regression Analysis towards Estimating Tax Evasion in Goods and Services Tax",
"doi": null,
"abstractUrl": "/proceedings-article/wi/2018/732500a758/17D45WnnFXf",
"parentPublication": {
"id": "proceedings/wi/2018/7325/0",
"title": "2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icedeg/2019/1704/0/08734342",
"title": "Data Mining Techniques Applied in Tax Administrations: A Literature Review",
"doi": null,
"abstractUrl": "/proceedings-article/icedeg/2019/08734342/1aPuUsoWbYs",
"parentPublication": {
"id": "proceedings/icedeg/2019/1704/0",
"title": "2019 Sixth International Conference on eDemocracy & eGovernment (ICEDEG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2019/0858/0/09006325",
"title": "TEDM-PU: A Tax Evasion Detection Method Based on Positive and Unlabeled Learning",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2019/09006325/1hJrIxuILTi",
"parentPublication": {
"id": "proceedings/big-data/2019/0858/0",
"title": "2019 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2019/0858/0/09005656",
"title": "Unsupervised Conditional Adversarial Networks for Tax Evasion Detection",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2019/09005656/1hJrQaOQati",
"parentPublication": {
"id": "proceedings/big-data/2019/0858/0",
"title": "2019 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2020/7303/0/730300a207",
"title": "TTED-PU:A Transferable Tax Evasion Detection Method Based on Positive and Unlabeled Learning",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2020/730300a207/1nkDn8Avtcs",
"parentPublication": {
"id": "proceedings/compsac/2020/7303/0",
"title": "2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2020/7303/0/730300a235",
"title": "A Novel Tax Evasion Detection Framework via Fused Transaction Network Representation",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2020/730300a235/1nkDqdNCmGY",
"parentPublication": {
"id": "proceedings/compsac/2020/7303/0",
"title": "2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2020/6251/0/09378157",
"title": "T-EGAT: A Temporal Edge Enhanced Graph Attention Network for Tax Evasion Detection",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2020/09378157/1s64F8c0RG0",
"parentPublication": {
"id": "proceedings/big-data/2020/6251/0",
"title": "2020 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2023/01/09459507",
"title": "Tax Evasion Detection With FBNE-PU Algorithm Based on PnCGCN and PU Learning",
"doi": null,
"abstractUrl": "/journal/tk/2023/01/09459507/1uvzUgQQnv2",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09228894",
"articleId": "1nYptLKl7by",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09222313",
"articleId": "1nTr29xEpkk",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1qLcUOvzDMI",
"name": "ttg202102-09222068s1-supp1-3030370.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202102-09222068s1-supp1-3030370.mp4",
"extension": "mp4",
"size": "72 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvA1hrW",
"title": "Nov.-Dec.",
"year": "2014",
"issueNum": "06",
"idPrefix": "tb",
"pubType": "journal",
"volume": "11",
"label": "Nov.-Dec.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwwJWEo",
"doi": "10.1109/TCBB.2014.2343977",
"abstract": "Analysis of probability distributions conditional on species trees has demonstrated the existence of anomalous ranked gene trees (ARGTs), ranked gene trees that are more probable than the ranked gene tree that accords with the ranked species tree. Here, to improve the characterization of ARGTs, we study enumerative and probabilistic properties of two classes of ranked labeled species trees, focusing on the presence or avoidance of certain subtree patterns associated with the production of ARGTs. We provide exact enumerations and asymptotic estimates for cardinalities of these sets of trees, showing that as the number of species increases without bound, the fraction of all ranked labeled species trees that are ARGT-producing approaches Z_$1$_Z . This result extends beyond earlier existence results to provide a probabilistic claim about the frequency of ARGTs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Analysis of probability distributions conditional on species trees has demonstrated the existence of anomalous ranked gene trees (ARGTs), ranked gene trees that are more probable than the ranked gene tree that accords with the ranked species tree. Here, to improve the characterization of ARGTs, we study enumerative and probabilistic properties of two classes of ranked labeled species trees, focusing on the presence or avoidance of certain subtree patterns associated with the production of ARGTs. We provide exact enumerations and asymptotic estimates for cardinalities of these sets of trees, showing that as the number of species increases without bound, the fraction of all ranked labeled species trees that are ARGT-producing approaches $1$ . This result extends beyond earlier existence results to provide a probabilistic claim about the frequency of ARGTs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Analysis of probability distributions conditional on species trees has demonstrated the existence of anomalous ranked gene trees (ARGTs), ranked gene trees that are more probable than the ranked gene tree that accords with the ranked species tree. Here, to improve the characterization of ARGTs, we study enumerative and probabilistic properties of two classes of ranked labeled species trees, focusing on the presence or avoidance of certain subtree patterns associated with the production of ARGTs. We provide exact enumerations and asymptotic estimates for cardinalities of these sets of trees, showing that as the number of species increases without bound, the fraction of all ranked labeled species trees that are ARGT-producing approaches - . This result extends beyond earlier existence results to provide a probabilistic claim about the frequency of ARGTs.",
"title": "On the Number of Ranked Species Trees Producing Anomalous Ranked Gene Trees",
"normalizedTitle": "On the Number of Ranked Species Trees Producing Anomalous Ranked Gene Trees",
"fno": "06867321",
"hasPdf": true,
"idPrefix": "tb",
"keywords": [
"Vegetation",
"Tin",
"Labeling",
"Phylogeny",
"IEEE Transactions",
"Computational Biology",
"Bioinformatics",
"Species Trees",
"Enumeration",
"Gene Trees",
"Labeled Histories",
"Mathematical Phylogenetics"
],
"authors": [
{
"givenName": "Filippo",
"surname": "Disanto",
"fullName": "Filippo Disanto",
"affiliation": "Department of Biology, Stanford University, Stanford, CA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Noah A.",
"surname": "Rosenberg",
"fullName": "Noah A. Rosenberg",
"affiliation": "Department of Biology, Stanford University, Stanford, CA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "06",
"pubDate": "2014-11-01 00:00:00",
"pubType": "trans",
"pages": "1229-1238",
"year": "2014",
"issn": "1545-5963",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tb/2016/03/07172469",
"title": "Fast Construction of Near Parsimonious Hybridization Networks for Multiple Phylogenetic Trees",
"doi": null,
"abstractUrl": "/journal/tb/2016/03/07172469/13rRUwfI0Oy",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2016/05/07289362",
"title": "Asymptotic Properties of the Number of Matching Coalescent Histories for Caterpillar-Like Families of Species Trees",
"doi": null,
"abstractUrl": "/journal/tb/2016/05/07289362/13rRUxBJhls",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2014/01/06657669",
"title": "Maximizing Deep Coalescence Cost",
"doi": null,
"abstractUrl": "/journal/tb/2014/01/06657669/13rRUxOdDbh",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2012/06/ttb2012061558",
"title": "A Characterization of the Set of Species Trees that Produce Anomalous Ranked Gene Trees",
"doi": null,
"abstractUrl": "/journal/tb/2012/06/ttb2012061558/13rRUxZzAg7",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2019/03/08244309",
"title": "Credibility of Evolutionary Events in Gene Trees",
"doi": null,
"abstractUrl": "/journal/tb/2019/03/08244309/13rRUy2YLRA",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2018/05/07933200",
"title": "Inferring Gene-Species Assignments in the Presence of Horizontal Gene Transfer",
"doi": null,
"abstractUrl": "/journal/tb/2018/05/07933200/14dcDYg3h6G",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2018/05/08002594",
"title": "Bijective Diameters of Gene Tree Parsimony Costs",
"doi": null,
"abstractUrl": "/journal/tb/2018/05/08002594/14dcEdidYgv",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2019/01/08382181",
"title": "An Integrated Reconciliation Framework for Domain, Gene, and Species Level Evolution",
"doi": null,
"abstractUrl": "/journal/tb/2019/01/08382181/17D45W9KVFu",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2021/01/09093990",
"title": "Using Constrained-<sc>INC</sc> for Large-Scale Gene Tree and Species Tree Estimation",
"doi": null,
"abstractUrl": "/journal/tb/2021/01/09093990/1jP8tj9B2Uw",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/05/09516887",
"title": "A Polynomial-Time Algorithm for Minimizing the Deep Coalescence Cost for Level-1 Species Networks",
"doi": null,
"abstractUrl": "/journal/tb/2022/05/09516887/1watV7JbMJ2",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06853347",
"articleId": "13rRUzpzezj",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06814272",
"articleId": "13rRUwfI0Ow",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNAkWv9L",
"title": "October",
"year": "2008",
"issueNum": "10",
"idPrefix": "tk",
"pubType": "journal",
"volume": "20",
"label": "October",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxASuhY",
"doi": "10.1109/TKDE.2008.96",
"abstract": "Often, it is required to identify anomalous windows reflecting unusual rate of occurrence of a specific event of interest. Spatial scan statistic approach moves scan window over the region and computes the statistic of a parameter(s) of interest, and identifies anomalous windows. While this approach has been successfully employed, earlier proposals suffer from two limitations: (i) In general, the scan window is regular shaped (e.g., circle, rectangle) identifying anomalous windows of fixed shapes only. However, the region of anomaly is not necessarily regular shaped. Recent proposals to identify windows of irregular shapes identify windows larger than the true anomalies, or penalize large windows. (ii) These techniques account for autocorrelation among spatial data, but not spatial heterogeneity often resulting in inaccurate anomalous windows. We propose a random walk based Free-Form Spatial Scan Statistic (FS3). We construct a Weighted Delaunay Nearest Neighbor graph (WDNN) to capture spatial autocorrelation and heterogeneity. Using random walks we identify natural free-form scan windows, not restricted to a predefined shape and prove that they are not random. FS3 on real datasets has shown that it identifies more refined anomalous windows with better likelihood ratio of it being an anomaly as compared to earlier spatial scan statistic approaches.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Often, it is required to identify anomalous windows reflecting unusual rate of occurrence of a specific event of interest. Spatial scan statistic approach moves scan window over the region and computes the statistic of a parameter(s) of interest, and identifies anomalous windows. While this approach has been successfully employed, earlier proposals suffer from two limitations: (i) In general, the scan window is regular shaped (e.g., circle, rectangle) identifying anomalous windows of fixed shapes only. However, the region of anomaly is not necessarily regular shaped. Recent proposals to identify windows of irregular shapes identify windows larger than the true anomalies, or penalize large windows. (ii) These techniques account for autocorrelation among spatial data, but not spatial heterogeneity often resulting in inaccurate anomalous windows. We propose a random walk based Free-Form Spatial Scan Statistic (FS3). We construct a Weighted Delaunay Nearest Neighbor graph (WDNN) to capture spatial autocorrelation and heterogeneity. Using random walks we identify natural free-form scan windows, not restricted to a predefined shape and prove that they are not random. FS3 on real datasets has shown that it identifies more refined anomalous windows with better likelihood ratio of it being an anomaly as compared to earlier spatial scan statistic approaches.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Often, it is required to identify anomalous windows reflecting unusual rate of occurrence of a specific event of interest. Spatial scan statistic approach moves scan window over the region and computes the statistic of a parameter(s) of interest, and identifies anomalous windows. While this approach has been successfully employed, earlier proposals suffer from two limitations: (i) In general, the scan window is regular shaped (e.g., circle, rectangle) identifying anomalous windows of fixed shapes only. However, the region of anomaly is not necessarily regular shaped. Recent proposals to identify windows of irregular shapes identify windows larger than the true anomalies, or penalize large windows. (ii) These techniques account for autocorrelation among spatial data, but not spatial heterogeneity often resulting in inaccurate anomalous windows. We propose a random walk based Free-Form Spatial Scan Statistic (FS3). We construct a Weighted Delaunay Nearest Neighbor graph (WDNN) to capture spatial autocorrelation and heterogeneity. Using random walks we identify natural free-form scan windows, not restricted to a predefined shape and prove that they are not random. FS3 on real datasets has shown that it identifies more refined anomalous windows with better likelihood ratio of it being an anomaly as compared to earlier spatial scan statistic approaches.",
"title": "Random Walks to Identify Anomalous Free-Form Spatial Scan Windows",
"normalizedTitle": "Random Walks to Identify Anomalous Free-Form Spatial Scan Windows",
"fno": "ttk2008101378",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Spatial Databases",
"Spatial Databases And GIS",
"Anomaly Detection",
"Scan Statistics"
],
"authors": [
{
"givenName": "Vandana P.",
"surname": "Janeja",
"fullName": "Vandana P. Janeja",
"affiliation": "University of Maryland Baltimore County, Baltimore",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Vijayalakshmi",
"surname": "Atluri",
"fullName": "Vijayalakshmi Atluri",
"affiliation": "Rutgers University, Newark",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "10",
"pubDate": "2008-10-01 00:00:00",
"pubType": "trans",
"pages": "1378-1392",
"year": "2008",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/apscc/2006/2751/0/27510194",
"title": "Using Statistical Similarity to Identify Corresponding Attributes between Heterogeneous Spatial Databases",
"doi": null,
"abstractUrl": "/proceedings-article/apscc/2006/27510194/12OmNAoUTto",
"parentPublication": {
"id": "proceedings/apscc/2006/2751/0",
"title": "2006 IEEE Asia-Pacific Conference on Services Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wise/2001/1393/2/13932033",
"title": "ISMART(tm) +i-Spatia(tm) - Information Server: Deploying Integrated Web-Based Spatial Applications within an Oracle Database Environment",
"doi": null,
"abstractUrl": "/proceedings-article/wise/2001/13932033/12OmNvjgWX8",
"parentPublication": {
"id": "proceedings/wise/2001/1393/2",
"title": "Web Information Systems Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2014/4274/0/4274b113",
"title": "Video Retrieval Methods Using Geographic Information in Windows Azure Cloud",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2014/4274b113/12OmNzYeANO",
"parentPublication": {
"id": "proceedings/icdmw/2014/4274/0",
"title": "2014 IEEE International Conference on Data Mining Workshop (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/2009/05/ttm2009050622",
"title": "Energy-Efficient Map Interpolation for Sensor Fields Using Kriging",
"doi": null,
"abstractUrl": "/journal/tm/2009/05/ttm2009050622/13rRUNvyatP",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2008/04/ttk2008040433",
"title": "A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets",
"doi": null,
"abstractUrl": "/journal/tk/2008/04/ttk2008040433/13rRUwI5U8g",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/1999/04/k0688",
"title": "Spatial Join Processing Using Corner Transformation",
"doi": null,
"abstractUrl": "/journal/tk/1999/04/k0688/13rRUwIF69v",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2011/12/ttk2011121857",
"title": "Anomalous Window Discovery for Linear Intersecting Paths",
"doi": null,
"abstractUrl": "/journal/tk/2011/12/ttk2011121857/13rRUwjoNxs",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2009/03/ttk2009030366",
"title": "On the Effect of Location Uncertainty in Spatial Querying",
"doi": null,
"abstractUrl": "/journal/tk/2009/03/ttk2009030366/13rRUxASuMR",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2022/8563/0/09859873",
"title": "Detecting Anomalous Events from Unlabeled Videos via Temporal Masked Auto-Encoding",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2022/09859873/1G9E4T1kx7W",
"parentPublication": {
"id": "proceedings/icme/2022/8563/0",
"title": "2022 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttk2008101363",
"articleId": "13rRUwbaqVe",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttk2008101393",
"articleId": "13rRUxD9h5y",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNBqdrij",
"title": "July",
"year": "2019",
"issueNum": "07",
"idPrefix": "tk",
"pubType": "journal",
"volume": "31",
"label": "July",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxBJhG8",
"doi": "10.1109/TKDE.2018.2857766",
"abstract": "We consider multi-label crowdsourcing learning in two scenarios. In the first scenario, we aim at inferring instances' groundtruth given the crowds' annotations. We propose two approaches NAM/RAM (Neighborhood/Relevance Aware Multi-label crowdsourcing) modeling the crowds' expertise and label correlations from different perspectives. Extended from single-label crowdsourcing methods, NAM models the crowds' expertise on individual labels, but based on the idea that for rational workers, their annotations for instances similar in the feature space should also be similar, NAM utilizes information from the feature space and incorporates the local influence of neighborhoods' annotations. Noting that the crowds tend to act in an effort-saving manner while labeling multiple labels, i.e., rather than carefully annotating every proper label, they would prefer scanning and tagging a few most relevant labels, RAM models the crowds' expertise as their ability to distinguish the relevance between label pairs. In the second scenario, we care about cost-efficient crowdsourcing where the labeling and learning process are conducted in tandem. We extend NAM/RAM to the active paradigm and propose instance, label, and worker selection criteria such that the labeling cost is significantly saved compared to passive learning without labeling control. The proposals' effectiveness are validated on simulated and real data.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We consider multi-label crowdsourcing learning in two scenarios. In the first scenario, we aim at inferring instances' groundtruth given the crowds' annotations. We propose two approaches NAM/RAM (Neighborhood/Relevance Aware Multi-label crowdsourcing) modeling the crowds' expertise and label correlations from different perspectives. Extended from single-label crowdsourcing methods, NAM models the crowds' expertise on individual labels, but based on the idea that for rational workers, their annotations for instances similar in the feature space should also be similar, NAM utilizes information from the feature space and incorporates the local influence of neighborhoods' annotations. Noting that the crowds tend to act in an effort-saving manner while labeling multiple labels, i.e., rather than carefully annotating every proper label, they would prefer scanning and tagging a few most relevant labels, RAM models the crowds' expertise as their ability to distinguish the relevance between label pairs. In the second scenario, we care about cost-efficient crowdsourcing where the labeling and learning process are conducted in tandem. We extend NAM/RAM to the active paradigm and propose instance, label, and worker selection criteria such that the labeling cost is significantly saved compared to passive learning without labeling control. The proposals' effectiveness are validated on simulated and real data.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We consider multi-label crowdsourcing learning in two scenarios. In the first scenario, we aim at inferring instances' groundtruth given the crowds' annotations. We propose two approaches NAM/RAM (Neighborhood/Relevance Aware Multi-label crowdsourcing) modeling the crowds' expertise and label correlations from different perspectives. Extended from single-label crowdsourcing methods, NAM models the crowds' expertise on individual labels, but based on the idea that for rational workers, their annotations for instances similar in the feature space should also be similar, NAM utilizes information from the feature space and incorporates the local influence of neighborhoods' annotations. Noting that the crowds tend to act in an effort-saving manner while labeling multiple labels, i.e., rather than carefully annotating every proper label, they would prefer scanning and tagging a few most relevant labels, RAM models the crowds' expertise as their ability to distinguish the relevance between label pairs. In the second scenario, we care about cost-efficient crowdsourcing where the labeling and learning process are conducted in tandem. We extend NAM/RAM to the active paradigm and propose instance, label, and worker selection criteria such that the labeling cost is significantly saved compared to passive learning without labeling control. The proposals' effectiveness are validated on simulated and real data.",
"title": "Multi-Label Learning from Crowds",
"normalizedTitle": "Multi-Label Learning from Crowds",
"fno": "08413163",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Crowdsourcing",
"Learning Artificial Intelligence",
"Crowds",
"Multilabel Crowdsourcing Learning",
"Label Correlations",
"Single Label Crowdsourcing Methods",
"NAM Models",
"Individual Labels",
"Annotations",
"Feature Space",
"Multiple Labels",
"Proper Label",
"Relevant Labels",
"RAM Models",
"Label Pairs",
"Cost Efficient Crowdsourcing",
"Learning Process",
"Labeling Cost",
"Passive Learning",
"Labeling Control",
"Multilabel Learning",
"Inferring Instances Groundtruth",
"Neighborhood Relevance Aware Multilabel Crowdsourcing",
"Labeling",
"Crowdsourcing",
"Task Analysis",
"Correlation",
"Random Access Memory",
"Reliability",
"Tagging",
"Multi Label",
"Crowdsourcing",
"Label Correlation",
"Labeling Cost",
"Active Selection"
],
"authors": [
{
"givenName": "Shao-Yuan",
"surname": "Li",
"fullName": "Shao-Yuan Li",
"affiliation": "National Key Laboratory for Novel Software Technology, Nanjing Univerisity, Nanjing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yuan",
"surname": "Jiang",
"fullName": "Yuan Jiang",
"affiliation": "National Key Laboratory for Novel Software Technology, Nanjing Univerisity, Nanjing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Nitesh V.",
"surname": "Chawla",
"fullName": "Nitesh V. Chawla",
"affiliation": "Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Zhi-Hua",
"surname": "Zhou",
"fullName": "Zhi-Hua Zhou",
"affiliation": "National Key Laboratory for Novel Software Technology, Nanjing Univerisity, Nanjing, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "07",
"pubDate": "2019-07-01 00:00:00",
"pubType": "trans",
"pages": "1369-1382",
"year": "2019",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "trans/tp/2019/10/08423686",
"title": "Max-Margin Majority Voting for Learning from Crowds",
"doi": null,
"abstractUrl": "/journal/tp/2019/10/08423686/13rRUNvyaaq",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2017/12/08008864",
"title": "A Quality-Sensitive Method for Learning from Crowds",
"doi": null,
"abstractUrl": "/journal/tk/2017/12/08008864/13rRUxEhFt8",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2018/9159/0/08594876",
"title": "Multi-label Answer Aggregation Based on Joint Matrix Factorization",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2018/08594876/17D45WODarC",
"parentPublication": {
"id": "proceedings/icdm/2018/9159/0",
"title": "2018 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2019/08/08423205",
"title": "Ensemble Learning from Crowds",
"doi": null,
"abstractUrl": "/journal/tk/2019/08/08423205/17D45WaTknL",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2018/9159/0/08594936",
"title": "Estimating Latent Relative Labeling Importances for Multi-label Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2018/08594936/17D45WrVgdl",
"parentPublication": {
"id": "proceedings/icdm/2018/9159/0",
"title": "2018 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08545329",
"title": "Learning with Latent Label Hierarchy from Incomplete Multi-Label Data",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08545329/17D45Wuc33q",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ex/2022/06/09881795",
"title": "Machine Learning From Crowds Using Candidate Set-Based Labeling",
"doi": null,
"abstractUrl": "/magazine/ex/2022/06/09881795/1Gv92p7fJLi",
"parentPublication": {
"id": "mags/ex",
"title": "IEEE Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cse-euc/2019/1664/0/166400a373",
"title": "A Subjectivity-Aware Algorithm for Label Aggregation in Crowdsourcing",
"doi": null,
"abstractUrl": "/proceedings-article/cse-euc/2019/166400a373/1fHkyswgcX6",
"parentPublication": {
"id": "proceedings/cse-euc/2019/1664/0",
"title": "2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/07/09354590",
"title": "Partial Multi-Label Learning With Noisy Label Identification",
"doi": null,
"abstractUrl": "/journal/tp/2022/07/09354590/1reXib2cwWk",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/12/09573413",
"title": "Adaptive Graph Guided Disambiguation for Partial Label Learning",
"doi": null,
"abstractUrl": "/journal/tp/2022/12/09573413/1xH5E3Yjgek",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07835129",
"articleId": "1aAwKi4sCQM",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08413112",
"articleId": "13rRUypp58c",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNz2TCu1",
"title": "Nov.",
"year": "2017",
"issueNum": "11",
"idPrefix": "tp",
"pubType": "journal",
"volume": "39",
"label": "Nov.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUyfKIEw",
"doi": "10.1109/TPAMI.2016.2637350",
"abstract": "This paper investigates a new annotation technique that reduces significantly the amount of time to annotate training data for gesture recognition. Conventionally, the annotations comprise the start and end times, and the corresponding labels of gestures in sensor recordings. In this work, we propose a one-time point annotation in which labelers do not have to select the start and end time carefully, but just mark a one-time point within the time a gesture is happening. The technique gives more freedom and reduces significantly the burden for labelers. To make the one-time point annotations applicable, we propose a novel BoundarySearch algorithm to find automatically the correct temporal boundaries of gestures by discovering data patterns around their given one-time point annotations. The corrected annotations are then used to train gesture models. We evaluate the method on three applications from wearable gesture recognition with various gesture classes (10-17 classes) recorded with different sensor modalities. The results show that training on the corrected annotations can achieve performances close to a fully supervised training on clean annotations (lower by just up to 5 percent F1-score on average). Furthermore, the BoundarySearch algorithm is also evaluated on the ChaLearn 2014 multi-modal gesture recognition challenge recorded with Kinect sensors from computer vision and achieves similar results.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper investigates a new annotation technique that reduces significantly the amount of time to annotate training data for gesture recognition. Conventionally, the annotations comprise the start and end times, and the corresponding labels of gestures in sensor recordings. In this work, we propose a one-time point annotation in which labelers do not have to select the start and end time carefully, but just mark a one-time point within the time a gesture is happening. The technique gives more freedom and reduces significantly the burden for labelers. To make the one-time point annotations applicable, we propose a novel BoundarySearch algorithm to find automatically the correct temporal boundaries of gestures by discovering data patterns around their given one-time point annotations. The corrected annotations are then used to train gesture models. We evaluate the method on three applications from wearable gesture recognition with various gesture classes (10-17 classes) recorded with different sensor modalities. The results show that training on the corrected annotations can achieve performances close to a fully supervised training on clean annotations (lower by just up to 5 percent F1-score on average). Furthermore, the BoundarySearch algorithm is also evaluated on the ChaLearn 2014 multi-modal gesture recognition challenge recorded with Kinect sensors from computer vision and achieves similar results.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper investigates a new annotation technique that reduces significantly the amount of time to annotate training data for gesture recognition. Conventionally, the annotations comprise the start and end times, and the corresponding labels of gestures in sensor recordings. In this work, we propose a one-time point annotation in which labelers do not have to select the start and end time carefully, but just mark a one-time point within the time a gesture is happening. The technique gives more freedom and reduces significantly the burden for labelers. To make the one-time point annotations applicable, we propose a novel BoundarySearch algorithm to find automatically the correct temporal boundaries of gestures by discovering data patterns around their given one-time point annotations. The corrected annotations are then used to train gesture models. We evaluate the method on three applications from wearable gesture recognition with various gesture classes (10-17 classes) recorded with different sensor modalities. The results show that training on the corrected annotations can achieve performances close to a fully supervised training on clean annotations (lower by just up to 5 percent F1-score on average). Furthermore, the BoundarySearch algorithm is also evaluated on the ChaLearn 2014 multi-modal gesture recognition challenge recorded with Kinect sensors from computer vision and achieves similar results.",
"title": "Supporting One-Time Point Annotations for Gesture Recognition",
"normalizedTitle": "Supporting One-Time Point Annotations for Gesture Recognition",
"fno": "07778186",
"hasPdf": true,
"idPrefix": "tp",
"keywords": [
"Computer Vision",
"Gesture Recognition",
"Learning Artificial Intelligence",
"One Time Point Annotation",
"Annotation Technique",
"Wearable Gesture Recognition",
"Cha Learn 2014 Multimodal Gesture Recognition Challenge",
"Boundary Search Algorithm",
"Gesture Classes",
"Sensor Modalities",
"Kinect Sensors",
"Computer Vision",
"Gesture Recognition",
"Training Data",
"Labeling",
"Streaming Media",
"Training",
"Data Models",
"Time Series Analysis",
"One Time Point Annotation",
"Boundary Correction",
"Weakly Supervised Learning",
"Gesture Spotting",
"Wearable Sensors",
"Kinect Sensors"
],
"authors": [
{
"givenName": "Long-Van",
"surname": "Nguyen-Dinh",
"fullName": "Long-Van Nguyen-Dinh",
"affiliation": "Wearable Computing Lab, Department of Information Technology and Electrical Engineering, ETH Zürich, Switzerland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alberto",
"surname": "Calatroni",
"fullName": "Alberto Calatroni",
"affiliation": "Wearable Computing Lab, Department of Information Technology and Electrical Engineering, ETH Zürich, Switzerland",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Gerhard",
"surname": "Tröster",
"fullName": "Gerhard Tröster",
"affiliation": "Wearable Computing Lab, Department of Information Technology and Electrical Engineering, ETH Zürich, Switzerland",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "11",
"pubDate": "2017-11-01 00:00:00",
"pubType": "trans",
"pages": "2270-2283",
"year": "2017",
"issn": "0162-8828",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/3dui/2016/0842/0/07460046",
"title": "Interpreting 2D gesture annotations in 3D augmented reality",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2016/07460046/12OmNBSSVcS",
"parentPublication": {
"id": "proceedings/3dui/2016/0842/0",
"title": "2016 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2016/0836/0/07504746",
"title": "Anchoring 2D gesture annotations in augmented reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2016/07504746/12OmNBf94W7",
"parentPublication": {
"id": "proceedings/vr/2016/0836/0",
"title": "2016 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/percomw/2013/5075/0/06529449",
"title": "Method of determining training data for gesture recognition considering decay in gesture movements",
"doi": null,
"abstractUrl": "/proceedings-article/percomw/2013/06529449/12OmNxWcHaU",
"parentPublication": {
"id": "proceedings/percomw/2013/5075/0",
"title": "2013 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops 2013)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvri/2011/0054/0/05759659",
"title": "SOM-based hand gesture recognition for virtual interactions",
"doi": null,
"abstractUrl": "/proceedings-article/isvri/2011/05759659/12OmNxd4tor",
"parentPublication": {
"id": "proceedings/isvri/2011/0054/0",
"title": "2011 IEEE International Symposium on VR Innovation (ISVRI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cse/2014/7981/0/7981b096",
"title": "A Real-Time Hand Gesture Recognition Approach Based on Motion Features of Feature Points",
"doi": null,
"abstractUrl": "/proceedings-article/cse/2014/7981b096/12OmNxxvAHv",
"parentPublication": {
"id": "proceedings/cse/2014/7981/0",
"title": "2014 IEEE 17th International Conference on Computational Science and Engineering (CSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2017/03/07484667",
"title": "Bi-convex Optimization to Learn Classifiers from Multiple Biomedical Annotations",
"doi": null,
"abstractUrl": "/journal/tb/2017/03/07484667/13rRUxAATfa",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2021/9489/0/948900a318",
"title": "Moving Trajectory Based Traffic Police Gesture Recognition Via Time Series Classification",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2021/948900a318/1AUpvv5gmqI",
"parentPublication": {
"id": "proceedings/cis/2021/9489/0",
"title": "2021 17th International Conference on Computational Intelligence and Security (CIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tm/5555/01/09774919",
"title": "DSW: One-shot Learning Scheme for Device-free Acoustic Gesture Signals",
"doi": null,
"abstractUrl": "/journal/tm/5555/01/09774919/1Dlifok5mbC",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2019/0089/0/08756548",
"title": "Database of Gesture Attributes: Zero Shot Learning for Gesture Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2019/08756548/1bzYubZfg9q",
"parentPublication": {
"id": "proceedings/fg/2019/0089/0",
"title": "2019 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2019)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800f760",
"title": "An Efficient PointLSTM for Point Clouds Based Gesture Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800f760/1m3nFjzSUCc",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "07779036",
"articleId": "13rRUNvgzba",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07765034",
"articleId": "13rRUwdIOW7",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwFid7w",
"title": "Jan.",
"year": "2019",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "25",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "17D45XDIXWa",
"doi": "10.1109/TVCG.2018.2865027",
"abstract": "We have recently seen many successful applications of recurrent neural networks (RNNs) on electronic medical records (EMRs), which contain histories of patients' diagnoses, medications, and other various events, in order to predict the current and future states of patients. Despite the strong performance of RNNs, it is often challenging for users to understand why the model makes a particular prediction. Such black-box nature of RNNs can impede its wide adoption in clinical practice. Furthermore, we have no established methods to interactively leverage users' domain expertise and prior knowledge as inputs for steering the model. Therefore, our design study aims to provide a visual analytics solution to increase interpretability and interactivity of RNNs via a joint effort of medical experts, artificial intelligence scientists, and visual analytics researchers. Following the iterative design process between the experts, we design, implement, and evaluate a visual analytics tool called RetainVis, which couples a newly improved, interpretable, and interactive RNN-based model called RetainEX and visualizations for users' exploration of EMR data in the context of prediction tasks. Our study shows the effective use of RetainVis for gaining insights into how individual medical codes contribute to making risk predictions, using EMRs of patients with heart failure and cataract symptoms. Our study also demonstrates how we made substantial changes to the state-of-the-art RNN model called RETAIN in order to make use of temporal information and increase interactivity. This study will provide a useful guideline for researchers that aim to design an interpretable and interactive visual analytics tool for RNNs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We have recently seen many successful applications of recurrent neural networks (RNNs) on electronic medical records (EMRs), which contain histories of patients' diagnoses, medications, and other various events, in order to predict the current and future states of patients. Despite the strong performance of RNNs, it is often challenging for users to understand why the model makes a particular prediction. Such black-box nature of RNNs can impede its wide adoption in clinical practice. Furthermore, we have no established methods to interactively leverage users' domain expertise and prior knowledge as inputs for steering the model. Therefore, our design study aims to provide a visual analytics solution to increase interpretability and interactivity of RNNs via a joint effort of medical experts, artificial intelligence scientists, and visual analytics researchers. Following the iterative design process between the experts, we design, implement, and evaluate a visual analytics tool called RetainVis, which couples a newly improved, interpretable, and interactive RNN-based model called RetainEX and visualizations for users' exploration of EMR data in the context of prediction tasks. Our study shows the effective use of RetainVis for gaining insights into how individual medical codes contribute to making risk predictions, using EMRs of patients with heart failure and cataract symptoms. Our study also demonstrates how we made substantial changes to the state-of-the-art RNN model called RETAIN in order to make use of temporal information and increase interactivity. This study will provide a useful guideline for researchers that aim to design an interpretable and interactive visual analytics tool for RNNs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We have recently seen many successful applications of recurrent neural networks (RNNs) on electronic medical records (EMRs), which contain histories of patients' diagnoses, medications, and other various events, in order to predict the current and future states of patients. Despite the strong performance of RNNs, it is often challenging for users to understand why the model makes a particular prediction. Such black-box nature of RNNs can impede its wide adoption in clinical practice. Furthermore, we have no established methods to interactively leverage users' domain expertise and prior knowledge as inputs for steering the model. Therefore, our design study aims to provide a visual analytics solution to increase interpretability and interactivity of RNNs via a joint effort of medical experts, artificial intelligence scientists, and visual analytics researchers. Following the iterative design process between the experts, we design, implement, and evaluate a visual analytics tool called RetainVis, which couples a newly improved, interpretable, and interactive RNN-based model called RetainEX and visualizations for users' exploration of EMR data in the context of prediction tasks. Our study shows the effective use of RetainVis for gaining insights into how individual medical codes contribute to making risk predictions, using EMRs of patients with heart failure and cataract symptoms. Our study also demonstrates how we made substantial changes to the state-of-the-art RNN model called RETAIN in order to make use of temporal information and increase interactivity. This study will provide a useful guideline for researchers that aim to design an interpretable and interactive visual analytics tool for RNNs.",
"title": "RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records",
"normalizedTitle": "RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records",
"fno": "08440842",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Artificial Intelligence",
"Data Analysis",
"Data Visualisation",
"Interactive Systems",
"Medical Information Systems",
"Recurrent Neural Nets",
"Interactive RNN Based Model",
"EMR Data",
"Prediction Tasks",
"Retain Vis",
"Individual Medical Codes",
"Risk Predictions",
"Temporal Information",
"Increase Interactivity",
"Interpretable Analytics Tool",
"Interpretable Networks",
"Interactive Recurrent Neural Networks",
"Electronic Medical Records",
"Black Box Nature",
"Interactively Leverage Users",
"Design Study",
"Visual Analytics Solution",
"Medical Experts",
"Artificial Intelligence Scientists",
"Iterative Design Process",
"Newly Improved RNN Based Model",
"RNN Based Model",
"Visual Analytic Researchers",
"Interactive Visual Analytic Tool",
"Machine Learning",
"Medical Diagnostic Imaging",
"Task Analysis",
"Predictive Models",
"Computational Modeling",
"Visual Analytics",
"Data Models",
"Interactive Artificial Intelligence",
"XAI Explainable Artificial Intelligence",
"Interpretable Deep Learning",
"Healthcare"
],
"authors": [
{
"givenName": "Bum Chul",
"surname": "Kwon",
"fullName": "Bum Chul Kwon",
"affiliation": "IBM T.J. Watson Research CenterKorea University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Min-Je",
"surname": "Choi",
"fullName": "Min-Je Choi",
"affiliation": "Georgia Institute of Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Joanne Taery",
"surname": "Kim",
"fullName": "Joanne Taery Kim",
"affiliation": "Georgia Institute of Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Edward",
"surname": "Choi",
"fullName": "Edward Choi",
"affiliation": "Chung-Ang University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Young Bin",
"surname": "Kim",
"fullName": "Young Bin Kim",
"affiliation": "IBM T.J. Watson Research CenterKorea University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Soonwook",
"surname": "Kwon",
"fullName": "Soonwook Kwon",
"affiliation": "Catholic University, Daegu",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jimeng",
"surname": "Sun",
"fullName": "Jimeng Sun",
"affiliation": "IBM T.J. Watson Research CenterKorea University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jaegul",
"surname": "Choo",
"fullName": "Jaegul Choo",
"affiliation": "Georgia Institute of Technology",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2019-01-01 00:00:00",
"pubType": "trans",
"pages": "299-309",
"year": "2019",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iv/2017/0831/0/0831a422",
"title": "Visual Analytics for Electronic Intelligence: Challenges and Opportunities",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2017/0831a422/12OmNB7LvBm",
"parentPublication": {
"id": "proceedings/iv/2017/0831/0",
"title": "2017 21st International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2014/5669/0/06999214",
"title": "A visual analysis approach to cohort study of electronic patient records",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2014/06999214/12OmNBBQZoW",
"parentPublication": {
"id": "proceedings/bibm/2014/5669/0",
"title": "2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2017/0367/2/0367b230",
"title": "Re-Structuring and Specific Similarity Computation of Electronic Medical Records",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2017/0367b230/12OmNxcvh4o",
"parentPublication": {
"id": "compsac/2017/0367/2",
"title": "2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isspit/2013/4796/0/06781845",
"title": "KnowYourColors: Visual dashboards for blood metrics and healthcare analytics",
"doi": null,
"abstractUrl": "/proceedings-article/isspit/2013/06781845/12OmNzlly1J",
"parentPublication": {
"id": "proceedings/isspit/2013/4796/0",
"title": "2013 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2016/1611/0/07822561",
"title": "Identifying patterns of associated-conditions through topic models of Electronic Medical Records",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2016/07822561/12OmNzmLxMP",
"parentPublication": {
"id": "proceedings/bibm/2016/1611/0",
"title": "2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2017/3163/0/08585721",
"title": "Understanding Hidden Memories of Recurrent Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2017/08585721/17D45XwUAIq",
"parentPublication": {
"id": "proceedings/vast/2017/3163/0",
"title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669603",
"title": "Automatic detection of infectious diarrhea based on electronic medical records",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669603/1A9VezpR2uI",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2020/5697/0/09086238",
"title": "Visual Interpretation of Recurrent Neural Network on Multi-dimensional Time-series Forecast",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2020/09086238/1kuHkB4vMFG",
"parentPublication": {
"id": "proceedings/pacificvis/2020/5697/0",
"title": "2020 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a415",
"title": "Big Data Visualization and Visual Analytics of COVID-19 Data",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a415/1rSRdimCgJG",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2021/0132/0/013200a161",
"title": "Interpretable Phenotyping for Electronic Health Records",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2021/013200a161/1xIOMUQqhq0",
"parentPublication": {
"id": "proceedings/ichi/2021/0132/0",
"title": "2021 IEEE 9th International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08454905",
"articleId": "17D45WnnFYf",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08440049",
"articleId": "17D45WUj91f",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "17ShDTYet4O",
"name": "ttg201901-08440842s1.zip",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg201901-08440842s1.zip",
"extension": "zip",
"size": "67.2 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwFid7w",
"title": "Jan.",
"year": "2019",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "25",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "17D45Xbl4OK",
"doi": "10.1109/TVCG.2018.2864843",
"abstract": "In order to effectively infer correct labels from noisy crowdsourced annotations, learning-from-crowds models have introduced expert validation. However, little research has been done on facilitating the validation procedure. In this paper, we propose an interactive method to assist experts in verifying uncertain instance labels and unreliable workers. Given the instance labels and worker reliability inferred from a learning-from-crowds model, candidate instances and workers are selected for expert validation. The influence of verified results is propagated to relevant instances and workers through the learning-from-crowds model. To facilitate the validation of annotations, we have developed a confusion visualization to indicate the confusing classes for further exploration, a constrained projection method to show the uncertain labels in context, and a scatter-plot-based visualization to illustrate worker reliability. The three visualizations are tightly integrated with the learning-from-crowds model to provide an iterative and progressive environment for data validation. Two case studies were conducted that demonstrate our approach offers an efficient method for validating and improving crowdsourced annotations.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In order to effectively infer correct labels from noisy crowdsourced annotations, learning-from-crowds models have introduced expert validation. However, little research has been done on facilitating the validation procedure. In this paper, we propose an interactive method to assist experts in verifying uncertain instance labels and unreliable workers. Given the instance labels and worker reliability inferred from a learning-from-crowds model, candidate instances and workers are selected for expert validation. The influence of verified results is propagated to relevant instances and workers through the learning-from-crowds model. To facilitate the validation of annotations, we have developed a confusion visualization to indicate the confusing classes for further exploration, a constrained projection method to show the uncertain labels in context, and a scatter-plot-based visualization to illustrate worker reliability. The three visualizations are tightly integrated with the learning-from-crowds model to provide an iterative and progressive environment for data validation. Two case studies were conducted that demonstrate our approach offers an efficient method for validating and improving crowdsourced annotations.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In order to effectively infer correct labels from noisy crowdsourced annotations, learning-from-crowds models have introduced expert validation. However, little research has been done on facilitating the validation procedure. In this paper, we propose an interactive method to assist experts in verifying uncertain instance labels and unreliable workers. Given the instance labels and worker reliability inferred from a learning-from-crowds model, candidate instances and workers are selected for expert validation. The influence of verified results is propagated to relevant instances and workers through the learning-from-crowds model. To facilitate the validation of annotations, we have developed a confusion visualization to indicate the confusing classes for further exploration, a constrained projection method to show the uncertain labels in context, and a scatter-plot-based visualization to illustrate worker reliability. The three visualizations are tightly integrated with the learning-from-crowds model to provide an iterative and progressive environment for data validation. Two case studies were conducted that demonstrate our approach offers an efficient method for validating and improving crowdsourced annotations.",
"title": "An Interactive Method to Improve Crowdsourced Annotations",
"normalizedTitle": "An Interactive Method to Improve Crowdsourced Annotations",
"fno": "08440116",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Artificial Intelligence",
"Belief Networks",
"Interactive Systems",
"Learning Artificial Intelligence",
"Pattern Classification",
"Expert Validation",
"Validation Procedure",
"Interactive Method",
"Uncertain Instance Labels",
"Unreliable Workers",
"Worker Reliability",
"Candidate Instances",
"Relevant Instances",
"Constrained Projection Method",
"Uncertain Labels",
"Data Validation",
"Validating Improving Crowdsourced Annotations",
"Correct Labels",
"Noisy Crowdsourced Annotations",
"Learning From Crowd Model",
"Data Visualization",
"Labeling",
"Data Models",
"Task Analysis",
"Visual Analytics",
"Reliability",
"Crowdsourcing",
"Learning From Crowds",
"Interactive Visualization",
"Focus Context"
],
"authors": [
{
"givenName": "Shixia",
"surname": "Liu",
"fullName": "Shixia Liu",
"affiliation": "School of SoftwareTsinghua University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Changjian",
"surname": "Chen",
"fullName": "Changjian Chen",
"affiliation": "School of SoftwareTsinghua University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Yafeng",
"surname": "Lu",
"fullName": "Yafeng Lu",
"affiliation": "Arizona State University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Fangxin",
"surname": "Ouyang",
"fullName": "Fangxin Ouyang",
"affiliation": "School of SoftwareTsinghua University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Bin",
"surname": "Wang",
"fullName": "Bin Wang",
"affiliation": "School of SoftwareTsinghua University",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2019-01-01 00:00:00",
"pubType": "trans",
"pages": "235-245",
"year": "2019",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icde/2016/2020/0/07498229",
"title": "Crowdsourced POI labelling: Location-aware result inference and Task Assignment",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2016/07498229/12OmNBPtJEZ",
"parentPublication": {
"id": "proceedings/icde/2016/2020/0",
"title": "2016 IEEE 32nd International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2016/1437/0/1437a163",
"title": "Grouper: Optimizing Crowdsourced Face Annotations",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2016/1437a163/12OmNzd7bAt",
"parentPublication": {
"id": "proceedings/cvprw/2016/1437/0",
"title": "2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/passat-socialcom/2011/1931/0/06113206",
"title": "Incremental Relabeling for Active Learning with Noisy Crowdsourced Annotations",
"doi": null,
"abstractUrl": "/proceedings-article/passat-socialcom/2011/06113206/12OmNzdoMTW",
"parentPublication": {
"id": "proceedings/passat-socialcom/2011/1931/0",
"title": "2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust (PASSAT) / 2011 IEEE Third Int'l Conference on Social Computing (SocialCom)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2017/03/07484667",
"title": "Bi-convex Optimization to Learn Classifiers from Multiple Biomedical Annotations",
"doi": null,
"abstractUrl": "/journal/tb/2017/03/07484667/13rRUxAATfa",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2019/07/08413163",
"title": "Multi-Label Learning from Crowds",
"doi": null,
"abstractUrl": "/journal/tk/2019/07/08413163/13rRUxBJhG8",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2017/11/07778186",
"title": "Supporting One-Time Point Annotations for Gesture Recognition",
"doi": null,
"abstractUrl": "/journal/tp/2017/11/07778186/13rRUyfKIEw",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2021/2398/0/239800a539",
"title": "Truth Discovery in Sequence Labels from Crowds",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2021/239800a539/1AqxozQqwNi",
"parentPublication": {
"id": "proceedings/icdm/2021/2398/0",
"title": "2021 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2022/0883/0/088300a938",
"title": "Crowdsourced Fact Validation for Knowledge Bases",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2022/088300a938/1FwBGmelDwI",
"parentPublication": {
"id": "proceedings/icde/2022/0883/0",
"title": "2022 IEEE 38th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2019/7474/0/747400b922",
"title": "Learning Effective Embeddings From Crowdsourced Labels: An Educational Case Study",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2019/747400b922/1aDT16acAOk",
"parentPublication": {
"id": "proceedings/icde/2019/7474/0",
"title": "2019 IEEE 35th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cse-euc/2019/1664/0/166400a373",
"title": "A Subjectivity-Aware Algorithm for Label Aggregation in Crowdsourcing",
"doi": null,
"abstractUrl": "/proceedings-article/cse-euc/2019/166400a373/1fHkyswgcX6",
"parentPublication": {
"id": "proceedings/cse-euc/2019/1664/0",
"title": "2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08440841",
"articleId": "17D45WZZ7Gk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08464305",
"articleId": "17D45Xtvpee",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNrIaecv",
"title": "Sept.-Oct.",
"year": "2019",
"issueNum": "05",
"idPrefix": "cg",
"pubType": "magazine",
"volume": "39",
"label": "Sept.-Oct.",
"downloadables": {
"hasCover": true,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1aNOrENWwXS",
"doi": "10.1109/MCG.2019.2922592",
"abstract": "Interactive model steering helps people incrementally build machine learning models that are tailored to their domain and task. Existing visual analytic tools allow people to steer a single model (e.g., assignment attribute weights used by a dimension reduction model). However, the choice of model is critical in such situations. What if the model chosen is suboptimal for the task, dataset, or question being asked? What if instead of parameterizing and steering this model, a different model provides a better fit? This paper presents a technique to allow users to inspect and steer multiple machine learning models. The technique steers and samples models from a broader set of learning algorithms and model types. We incorporate this technique into a visual analytic prototype, BEAMES, that allows users to perform regression tasks via multimodel steering. This paper demonstrates the effectiveness of BEAMES via a use case, and discusses broader implications for multimodel steering.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Interactive model steering helps people incrementally build machine learning models that are tailored to their domain and task. Existing visual analytic tools allow people to steer a single model (e.g., assignment attribute weights used by a dimension reduction model). However, the choice of model is critical in such situations. What if the model chosen is suboptimal for the task, dataset, or question being asked? What if instead of parameterizing and steering this model, a different model provides a better fit? This paper presents a technique to allow users to inspect and steer multiple machine learning models. The technique steers and samples models from a broader set of learning algorithms and model types. We incorporate this technique into a visual analytic prototype, BEAMES, that allows users to perform regression tasks via multimodel steering. This paper demonstrates the effectiveness of BEAMES via a use case, and discusses broader implications for multimodel steering.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Interactive model steering helps people incrementally build machine learning models that are tailored to their domain and task. Existing visual analytic tools allow people to steer a single model (e.g., assignment attribute weights used by a dimension reduction model). However, the choice of model is critical in such situations. What if the model chosen is suboptimal for the task, dataset, or question being asked? What if instead of parameterizing and steering this model, a different model provides a better fit? This paper presents a technique to allow users to inspect and steer multiple machine learning models. The technique steers and samples models from a broader set of learning algorithms and model types. We incorporate this technique into a visual analytic prototype, BEAMES, that allows users to perform regression tasks via multimodel steering. This paper demonstrates the effectiveness of BEAMES via a use case, and discusses broader implications for multimodel steering.",
"title": "BEAMES: Interactive Multimodel Steering, Selection, and Inspection for Regression Tasks",
"normalizedTitle": "BEAMES: Interactive Multimodel Steering, Selection, and Inspection for Regression Tasks",
"fno": "08735919",
"hasPdf": true,
"idPrefix": "cg",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Learning Artificial Intelligence",
"Regression Analysis",
"Dimension Reduction Model",
"Multiple Machine Learning Models",
"Technique Steers",
"Samples Models",
"Learning Algorithms",
"Model Types",
"Visual Analytic Prototype",
"BEAMES",
"Regression Tasks",
"Interactive Multimodel Steering",
"Inspection",
"Interactive Model Steering",
"Visual Analytic Tools",
"Assignment Attribute Weights",
"Data Models",
"Computational Modeling",
"Analytical Models",
"Task Analysis",
"Visual Analytics",
"Inspection",
"Machine Learning",
"Computer Society",
"IEEE",
"IEE Etran",
"Journal",
"LATEX",
"Paper",
"Template"
],
"authors": [
{
"givenName": "Subhajit",
"surname": "Das",
"fullName": "Subhajit Das",
"affiliation": "Georgia Institute of Technology",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Dylan",
"surname": "Cashman",
"fullName": "Dylan Cashman",
"affiliation": "Tufts University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Remco",
"surname": "Chang",
"fullName": "Remco Chang",
"affiliation": "Tufts University",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Alex",
"surname": "Endert",
"fullName": "Alex Endert",
"affiliation": "Georgia Institute of Technology",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2019-09-01 00:00:00",
"pubType": "mags",
"pages": "20-32",
"year": "2019",
"issn": "0272-1716",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/3dui/2010/6846/0/05444724",
"title": "Revisiting path steering for 3D manipulation tasks",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2010/05444724/12OmNxAlzYX",
"parentPublication": {
"id": "proceedings/3dui/2010/6846/0",
"title": "2010 IEEE Symposium on 3D User Interfaces (3DUI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mascots/2012/2453/0/06298213",
"title": "NetSim-Steer: A Runtime Steering Framework for Network Simulators",
"doi": null,
"abstractUrl": "/proceedings-article/mascots/2012/06298213/12OmNxQOjEx",
"parentPublication": {
"id": "proceedings/mascots/2012/2453/0",
"title": "2012 IEEE 20th International Symposium on Modelling, Analysis & Simulation of Computer and Telecommunication Systems (MASCOTS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cs/2014/02/mcs2014020022",
"title": "User-Steered Energy Generation and Consumption Multimodel Simulation for Pricing and Policy Development",
"doi": null,
"abstractUrl": "/magazine/cs/2014/02/mcs2014020022/13rRUwfqpK8",
"parentPublication": {
"id": "mags/cs",
"title": "Computing in Science & Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2013/04/mcg2013040006",
"title": "Beyond Control Panels: Direct Manipulation for Visual Analytics",
"doi": null,
"abstractUrl": "/magazine/cg/2013/04/mcg2013040006/13rRUwh80Ja",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2014/04/mcg2014040008",
"title": "Semantic Interaction for Visual Analytics: Toward Coupling Cognition and Computation",
"doi": null,
"abstractUrl": "/magazine/cg/2014/04/mcg2014040008/13rRUwwslv3",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875926",
"title": "VASA: Interactive Computational Steering of Large Asynchronous Simulation Pipelines for Societal Infrastructure",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875926/13rRUxly9dU",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08464305",
"title": "RegressionExplorer: Interactive Exploration of Logistic Regression Models with Subgroup Analysis",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08464305/17D45Xtvpee",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2021/02/09222338",
"title": "HyperTendril: Visual Analytics for User-Driven Hyperparameter Optimization of Deep Neural Networks",
"doi": null,
"abstractUrl": "/journal/tg/2021/02/09222338/1nTrGnbsuYg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2020/8014/0/801400a251",
"title": "Visually Analyzing and Steering Zero Shot Learning",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2020/801400a251/1qRNQGu8try",
"parentPublication": {
"id": "proceedings/vis/2020/8014/0",
"title": "2020 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vahc/2021/2067/0/206700a006",
"title": "Communicating Performance of Regression Models Using Visualization in Pharmacovigilance",
"doi": null,
"abstractUrl": "/proceedings-article/vahc/2021/206700a006/1z0ylclGF6E",
"parentPublication": {
"id": "proceedings/vahc/2021/2067/0",
"title": "2021 IEEE Workshop on Visual Analytics in Healthcare (VAHC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08809394",
"articleId": "1cFV5JhG2gU",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08744242",
"articleId": "1cFV5domibu",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNvsDHDY",
"title": "Jan.",
"year": "2020",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "26",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1cHE4Cqo27C",
"doi": "10.1109/TVCG.2019.2934546",
"abstract": "We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, this situation has lead to clinician interest in understanding and predicting RT outcomes based on previously treated similar patients. To enable this type of analysis, we introduce a novel topology-based spatial similarity measure, T-SSIM, and a predictive algorithm based on this similarity measure. We couple the algorithm with a visual steering interface that intertwines visual encodings for the spatial data and statistical results, including a novel parallel-marker encoding that is spatially aware. We report quantitative results on a cohort of 165 patients, as well as a qualitative evaluation with domain experts in radiation oncology, data management, biostatistics, and medical imaging, who are collaborating remotely.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, this situation has lead to clinician interest in understanding and predicting RT outcomes based on previously treated similar patients. To enable this type of analysis, we introduce a novel topology-based spatial similarity measure, T-SSIM, and a predictive algorithm based on this similarity measure. We couple the algorithm with a visual steering interface that intertwines visual encodings for the spatial data and statistical results, including a novel parallel-marker encoding that is spatially aware. We report quantitative results on a cohort of 165 patients, as well as a qualitative evaluation with domain experts in radiation oncology, data management, biostatistics, and medical imaging, who are collaborating remotely.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We describe a visual computing approach to radiation therapy (RT) planning, based on spatial similarity within a patient cohort. In radiotherapy for head and neck cancer treatment, dosage to organs at risk surrounding a tumor is a large cause of treatment toxicity. Along with the availability of patient repositories, this situation has lead to clinician interest in understanding and predicting RT outcomes based on previously treated similar patients. To enable this type of analysis, we introduce a novel topology-based spatial similarity measure, T-SSIM, and a predictive algorithm based on this similarity measure. We couple the algorithm with a visual steering interface that intertwines visual encodings for the spatial data and statistical results, including a novel parallel-marker encoding that is spatially aware. We report quantitative results on a cohort of 165 patients, as well as a qualitative evaluation with domain experts in radiation oncology, data management, biostatistics, and medical imaging, who are collaborating remotely.",
"title": "Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration",
"normalizedTitle": "Cohort-based T-SSIM Visual Computing for Radiation Therapy Prediction and Exploration",
"fno": "08809842",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Biological Organs",
"Cancer",
"Data Visualisation",
"Medical Image Processing",
"Medical Information Systems",
"Radiation Therapy",
"Tumours",
"Neck Cancer Treatment",
"Treatment Toxicity",
"Patient Repositories",
"Treated Similar Patients",
"Novel Topology Based Spatial Similarity Measure",
"Predictive Algorithm",
"Visual Steering Interface",
"Intertwines Visual Encodings",
"Spatial Data",
"Parallel Marker Encoding",
"Radiation Oncology",
"T SSIM Visual Computing",
"Radiation Therapy Prediction",
"Visual Computing Approach",
"Radiation Therapy Planning",
"Patient Cohort",
"Visualization",
"Planning",
"Tumors",
"Biological Systems",
"Data Visualization",
"Prediction Algorithms",
"Biomedical Applications Of Radiation",
"Biomedical And Medical Visualization",
"Spatial Techniques",
"Visual Design",
"High Dimensional Data"
],
"authors": [
{
"givenName": "A.",
"surname": "Wentzel",
"fullName": "A. Wentzel",
"affiliation": "University of Illinois at Chicago",
"__typename": "ArticleAuthorType"
},
{
"givenName": "P.",
"surname": "Hanula",
"fullName": "P. Hanula",
"affiliation": "University of Illinois at Chicago",
"__typename": "ArticleAuthorType"
},
{
"givenName": "T.",
"surname": "Luciani",
"fullName": "T. Luciani",
"affiliation": "University of Illinois at Chicago",
"__typename": "ArticleAuthorType"
},
{
"givenName": "B.",
"surname": "Elgohari",
"fullName": "B. Elgohari",
"affiliation": "MD Anderson Cancer Center, University of Texas",
"__typename": "ArticleAuthorType"
},
{
"givenName": "H.",
"surname": "Elhalawani",
"fullName": "H. Elhalawani",
"affiliation": "MD Anderson Cancer Center, University of Texas",
"__typename": "ArticleAuthorType"
},
{
"givenName": "G.",
"surname": "Canahuate",
"fullName": "G. Canahuate",
"affiliation": "University of Iowa",
"__typename": "ArticleAuthorType"
},
{
"givenName": "D.",
"surname": "Vock",
"fullName": "D. Vock",
"affiliation": "School of Public Health, University of Minnesota",
"__typename": "ArticleAuthorType"
},
{
"givenName": "C.D.",
"surname": "Fuller",
"fullName": "C.D. Fuller",
"affiliation": "MD Anderson Cancer Center, University of Texas",
"__typename": "ArticleAuthorType"
},
{
"givenName": "G.E.",
"surname": "Marai",
"fullName": "G.E. Marai",
"affiliation": "University of Illinois at Chicago",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2020-01-01 00:00:00",
"pubType": "trans",
"pages": "949-959",
"year": "2020",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/caia/1994/5550/0/00323677",
"title": "Roentgen: radiation therapy and case-based reasoning",
"doi": null,
"abstractUrl": "/proceedings-article/caia/1994/00323677/12OmNBbJTpw",
"parentPublication": {
"id": "proceedings/caia/1994/5550/0",
"title": "Proceedings of the Tenth Conference on Artificial Intelligence for Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/snpd/2013/5005/0/5005a225",
"title": "A Reduced Order Memetic Algorithm for Constraint Optimization in Radiation Therapy Treatment Planning",
"doi": null,
"abstractUrl": "/proceedings-article/snpd/2013/5005a225/12OmNx5YvbK",
"parentPublication": {
"id": "proceedings/snpd/2013/5005/0",
"title": "2013 14th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbms/1993/3752/0/00263009",
"title": "Human factors in radiation oncology therapy: some software control interface issues",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/1993/00263009/12OmNxFaLAB",
"parentPublication": {
"id": "proceedings/cbms/1993/3752/0",
"title": "Proceedings of the Sixth Annual 1993 IEEE Symposium Computer-Based Medical Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vbc/1990/2039/0/00109295",
"title": "Volume rendering in radiation treatment planning",
"doi": null,
"abstractUrl": "/proceedings-article/vbc/1990/00109295/12OmNylsZFM",
"parentPublication": {
"id": "proceedings/vbc/1990/2039/0",
"title": "[1990] Proceedings of the First Conference on Visualization in Biomedical Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scamc/1978/9999/0/00679903",
"title": "Computer-Controlled Radiation Therapy",
"doi": null,
"abstractUrl": "/proceedings-article/scamc/1978/00679903/12OmNzSh11D",
"parentPublication": {
"id": "proceedings/scamc/1978/9999/0",
"title": "1978 The Second Annual Symposium on Computer Application in Medical Care",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2018/5488/0/08621266",
"title": "Representing Knowledge for Radiation Therapy Planning with Markov Logic Networks",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2018/08621266/17D45XlyDue",
"parentPublication": {
"id": "proceedings/bibm/2018/5488/0",
"title": "2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669759",
"title": "Dynamic Restricted Column Generation in MIQP for Cancer Radiation Therapy",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669759/1A9VTG2rZbq",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412924",
"title": "A Deep Learning-Based Method for Predicting Volumes of Nasopharyngeal Carcinoma for Adaptive Radiation Therapy Treatment",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412924/1tmj8RakeNa",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csci/2020/7624/0/762400b541",
"title": "Development of Multistage RFE-SVR Model to Predict Radiation Sensitivity",
"doi": null,
"abstractUrl": "/proceedings-article/csci/2020/762400b541/1uGYVJlwsaQ",
"parentPublication": {
"id": "proceedings/csci/2020/7624/0",
"title": "2020 International Conference on Computational Science and Computational Intelligence (CSCI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ipdpsw/2021/3577/0/357700a449",
"title": "Accelerating Radiation Therapy Dose Calculation with Nvidia GPUs",
"doi": null,
"abstractUrl": "/proceedings-article/ipdpsw/2021/357700a449/1uHgPvExC4o",
"parentPublication": {
"id": "proceedings/ipdpsw/2021/3577/0",
"title": "2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08842614",
"articleId": "1doNAP4UOaI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08809843",
"articleId": "1cHEoqU2cj6",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNwGqBql",
"title": "July-Aug.",
"year": "2013",
"issueNum": "04",
"idPrefix": "cg",
"pubType": "magazine",
"volume": "33",
"label": "July-Aug.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwh80Ja",
"doi": "10.1109/MCG.2013.53",
"abstract": "To tackle the onset of big data, visual analytics seeks to marry the human intuition of visualization with mathematical models' analytical horsepower. A critical question is, how will humans interact with and steer these complex models? Initially, users applied direct manipulation to such models the same way they applied it to simpler visualizations in the premodel era--using control panels to directly manipulate model parameters. However, opportunities are arising for direct manipulation of the model outputs, where the users' thought processes take place, rather than the inputs. This article presents this new agenda for direct manipulation for visual analytics.",
"abstracts": [
{
"abstractType": "Regular",
"content": "To tackle the onset of big data, visual analytics seeks to marry the human intuition of visualization with mathematical models' analytical horsepower. A critical question is, how will humans interact with and steer these complex models? Initially, users applied direct manipulation to such models the same way they applied it to simpler visualizations in the premodel era--using control panels to directly manipulate model parameters. However, opportunities are arising for direct manipulation of the model outputs, where the users' thought processes take place, rather than the inputs. This article presents this new agenda for direct manipulation for visual analytics.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "To tackle the onset of big data, visual analytics seeks to marry the human intuition of visualization with mathematical models' analytical horsepower. A critical question is, how will humans interact with and steer these complex models? Initially, users applied direct manipulation to such models the same way they applied it to simpler visualizations in the premodel era--using control panels to directly manipulate model parameters. However, opportunities are arising for direct manipulation of the model outputs, where the users' thought processes take place, rather than the inputs. This article presents this new agenda for direct manipulation for visual analytics.",
"title": "Beyond Control Panels: Direct Manipulation for Visual Analytics",
"normalizedTitle": "Beyond Control Panels: Direct Manipulation for Visual Analytics",
"fno": "mcg2013040006",
"hasPdf": true,
"idPrefix": "cg",
"keywords": [
"Visual Analytics",
"Mathematical Model",
"Analytical Models",
"Visualization",
"Computational Modeling",
"Data Visualization",
"Computer Graphics",
"Visual Analytics",
"Direct Manipulation",
"Visualization"
],
"authors": [
{
"givenName": "A.",
"surname": "Endert",
"fullName": "A. Endert",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "L.",
"surname": "Bradel",
"fullName": "L. Bradel",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "C.",
"surname": "North",
"fullName": "C. North",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "04",
"pubDate": "2013-07-01 00:00:00",
"pubType": "mags",
"pages": "6-13",
"year": "2013",
"issn": "0272-1716",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/pacificvis/2010/6685/0/05429597",
"title": "Adaptive proxy geometry for direct volume manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2010/05429597/12OmNBsue33",
"parentPublication": {
"id": "proceedings/pacificvis/2010/6685/0",
"title": "2010 IEEE Pacific Visualization Symposium (PacificVis 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/1996/7240/0/72400208",
"title": "Tioga-2: A Direct Manipulation Database Visualization Environment",
"doi": null,
"abstractUrl": "/proceedings-article/icde/1996/72400208/12OmNCgrCUP",
"parentPublication": {
"id": "proceedings/icde/1996/7240/0",
"title": "Proceedings of the Twelfth International Conference on Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pacificvis/2014/2874/0/2874a352",
"title": "Visualization for Visual Analytics: Micro-visualization, Abstraction, and Physical Appeal",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2014/2874a352/12OmNySG3Oy",
"parentPublication": {
"id": "proceedings/pacificvis/2014/2874/0",
"title": "2014 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2010/04/mcg2010040042",
"title": "Direct Manipulation Blendshapes",
"doi": null,
"abstractUrl": "/magazine/cg/2010/04/mcg2010040042/13rRUB6Sq4P",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/12/06875967",
"title": "Knowledge Generation Model for Visual Analytics",
"doi": null,
"abstractUrl": "/journal/tg/2014/12/06875967/13rRUILLkvt",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2014/02/mcg2014020026",
"title": "DIVE: A Graph-Based Visual-Analytics Framework for Big Data",
"doi": null,
"abstractUrl": "/magazine/cg/2014/02/mcg2014020026/13rRUwh80Jb",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/co/2013/07/mco2013070030",
"title": "Visual Analytics Support for Intelligence Analysis",
"doi": null,
"abstractUrl": "/magazine/co/2013/07/mco2013070030/13rRUxD9h0P",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2009/02/mcg2009020084",
"title": "Demystifying Visual Analytics",
"doi": null,
"abstractUrl": "/magazine/cg/2009/02/mcg2009020084/13rRUy3gn3z",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi/2018/7325/0/732500a342",
"title": "Visual Analytics Interface for Time Series Data Based on Trajectory Manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/wi/2018/732500a342/17D45WODasq",
"parentPublication": {
"id": "proceedings/wi/2018/7325/0",
"title": "2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/01/08805443",
"title": "MetricsVis: A Visual Analytics System for Evaluating Employee Performance in Public Safety Agencies",
"doi": null,
"abstractUrl": "/journal/tg/2020/01/08805443/1cG4Fr9ck2A",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "mcg2013040004",
"articleId": "13rRUwInvMO",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "mcg2013040014",
"articleId": "13rRUxOveci",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNAHW0IV",
"title": "May",
"year": "2008",
"issueNum": "05",
"idPrefix": "tk",
"pubType": "journal",
"volume": "20",
"label": "May",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUxjQyvH",
"doi": "10.1109/TKDE.2007.190734",
"abstract": "We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities. It is based on decomposition of a model's predictions on individual contributions of each attribute. Our method works for so called black box models such as support vector machines, neural networks, and nearest neighbor algorithms as well as for ensemble methods, such as boosting and random forests. We demonstrate that the generated explanations closely follow the learned models and present a visualization technique which shows the utility of our approach and enables the comparison of different prediction methods.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities. It is based on decomposition of a model's predictions on individual contributions of each attribute. Our method works for so called black box models such as support vector machines, neural networks, and nearest neighbor algorithms as well as for ensemble methods, such as boosting and random forests. We demonstrate that the generated explanations closely follow the learned models and present a visualization technique which shows the utility of our approach and enables the comparison of different prediction methods.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities. It is based on decomposition of a model's predictions on individual contributions of each attribute. Our method works for so called black box models such as support vector machines, neural networks, and nearest neighbor algorithms as well as for ensemble methods, such as boosting and random forests. We demonstrate that the generated explanations closely follow the learned models and present a visualization technique which shows the utility of our approach and enables the comparison of different prediction methods.",
"title": "Explaining Classifications For Individual Instances",
"normalizedTitle": "Explaining Classifications For Individual Instances",
"fno": "ttk2008050589",
"hasPdf": true,
"idPrefix": "tk",
"keywords": [
"Machine Learning",
"Data Mining",
"Data And Knowledge Visualization",
"Visualization Techniques And Methodologies"
],
"authors": [
{
"givenName": "Marko",
"surname": "Robnik-Šikonja",
"fullName": "Marko Robnik-Šikonja",
"affiliation": null,
"__typename": "ArticleAuthorType"
},
{
"givenName": "Igor",
"surname": "Kononenko",
"fullName": "Igor Kononenko",
"affiliation": null,
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "05",
"pubDate": "2008-05-01 00:00:00",
"pubType": "trans",
"pages": "589-600",
"year": "2008",
"issn": "1041-4347",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icdmw/2008/3503/0/3503a036",
"title": "Online Reliability Estimates for Individual Predictions in Data Streams",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2008/3503a036/12OmNqGRGoP",
"parentPublication": {
"id": "proceedings/icdmw/2008/3503/0",
"title": "2008 IEEE International Conference on Data Mining Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2009/03/ttg2009030424",
"title": "Visualization of Simulated Urban Spaces: Inferring Parameterized Generation of Streets, Parcels, and Aerial Imagery",
"doi": null,
"abstractUrl": "/journal/tg/2009/03/ttg2009030424/13rRUNvgzix",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2009/01/ttg2009010106",
"title": "Asymmetric Tensor Analysis for Flow Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2009/01/ttg2009010106/13rRUwjoNwW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2009/05/ttg2009050759",
"title": "A Survey of Radial Methods for Information Visualization",
"doi": null,
"abstractUrl": "/journal/tg/2009/05/ttg2009050759/13rRUx0xPZv",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ts/2008/02/tts2008020260",
"title": "Software Architecture Visualization: An Evaluation Framework and Its Application",
"doi": null,
"abstractUrl": "/journal/ts/2008/02/tts2008020260/13rRUxAAT9m",
"parentPublication": {
"id": "trans/ts",
"title": "IEEE Transactions on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2012/01/ttg2012010160",
"title": "The Topological Effects of Smoothing",
"doi": null,
"abstractUrl": "/journal/tg/2012/01/ttg2012010160/13rRUxASuGg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2005/05/v0497",
"title": "Advanced Virtual Endoscopic Pituitary Surgery",
"doi": null,
"abstractUrl": "/journal/tg/2005/05/v0497/13rRUxNmPDJ",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2006/06/v1399",
"title": "Graph Signatures for Visual Analytics",
"doi": null,
"abstractUrl": "/journal/tg/2006/06/v1399/13rRUxYrbUv",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icde/2019/7474/0/747400c086",
"title": "Towards Explaining the Effects of Data Preprocessing on Machine Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icde/2019/747400c086/1aDSW5g2MH6",
"parentPublication": {
"id": "proceedings/icde/2019/7474/0",
"title": "2019 IEEE 35th International Conference on Data Engineering (ICDE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/msst/2019/3920/0/392000a193",
"title": "DFPE: Explaining Predictive Models for Disk Failure Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/msst/2019/392000a193/1eEULT9sLUA",
"parentPublication": {
"id": "proceedings/msst/2019/3920/0",
"title": "2019 35th Symposium on Mass Storage Systems and Technologies (MSST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "ttk2008050577",
"articleId": "13rRUxOvea1",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "ttk2008050601",
"articleId": "13rRUyfKIIb",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1wznUTxaKsw",
"title": "Oct.",
"year": "2021",
"issueNum": "10",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Oct.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1jQNru4p18k",
"doi": "10.1109/TVCG.2020.2995100",
"abstract": "Hierarchical clustering is an important technique to organize big data for exploratory data analysis. However, existing one-size-fits-all hierarchical clustering methods often fail to meet the diverse needs of different users. To address this challenge, we present an interactive steering method to visually supervise constrained hierarchical clustering by utilizing both public knowledge (e.g., Wikipedia) and private knowledge from users. The novelty of our approach includes 1) automatically constructing constraints for hierarchical clustering using knowledge (knowledge-driven) and intrinsic data distribution (data-driven), and 2) enabling the interactive steering of clustering through a visual interface (user-driven). Our method first maps each data item to the most relevant items in a knowledge base. An initial constraint tree is then extracted using the ant colony optimization algorithm. The algorithm balances the tree width and depth and covers the data items with high confidence. Given the constraint tree, the data items are hierarchically clustered using evolutionary Bayesian rose tree. To clearly convey the hierarchical clustering results, an uncertainty-aware tree visualization has been developed to enable users to quickly locate the most uncertain sub-hierarchies and interactively improve them. The quantitative evaluation and case study demonstrate that the proposed approach facilitates the building of customized clustering trees in an efficient and effective manner.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Hierarchical clustering is an important technique to organize big data for exploratory data analysis. However, existing one-size-fits-all hierarchical clustering methods often fail to meet the diverse needs of different users. To address this challenge, we present an interactive steering method to visually supervise constrained hierarchical clustering by utilizing both public knowledge (e.g., Wikipedia) and private knowledge from users. The novelty of our approach includes 1) automatically constructing constraints for hierarchical clustering using knowledge (knowledge-driven) and intrinsic data distribution (data-driven), and 2) enabling the interactive steering of clustering through a visual interface (user-driven). Our method first maps each data item to the most relevant items in a knowledge base. An initial constraint tree is then extracted using the ant colony optimization algorithm. The algorithm balances the tree width and depth and covers the data items with high confidence. Given the constraint tree, the data items are hierarchically clustered using evolutionary Bayesian rose tree. To clearly convey the hierarchical clustering results, an uncertainty-aware tree visualization has been developed to enable users to quickly locate the most uncertain sub-hierarchies and interactively improve them. The quantitative evaluation and case study demonstrate that the proposed approach facilitates the building of customized clustering trees in an efficient and effective manner.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Hierarchical clustering is an important technique to organize big data for exploratory data analysis. However, existing one-size-fits-all hierarchical clustering methods often fail to meet the diverse needs of different users. To address this challenge, we present an interactive steering method to visually supervise constrained hierarchical clustering by utilizing both public knowledge (e.g., Wikipedia) and private knowledge from users. The novelty of our approach includes 1) automatically constructing constraints for hierarchical clustering using knowledge (knowledge-driven) and intrinsic data distribution (data-driven), and 2) enabling the interactive steering of clustering through a visual interface (user-driven). Our method first maps each data item to the most relevant items in a knowledge base. An initial constraint tree is then extracted using the ant colony optimization algorithm. The algorithm balances the tree width and depth and covers the data items with high confidence. Given the constraint tree, the data items are hierarchically clustered using evolutionary Bayesian rose tree. To clearly convey the hierarchical clustering results, an uncertainty-aware tree visualization has been developed to enable users to quickly locate the most uncertain sub-hierarchies and interactively improve them. The quantitative evaluation and case study demonstrate that the proposed approach facilitates the building of customized clustering trees in an efficient and effective manner.",
"title": "Interactive Steering of Hierarchical Clustering",
"normalizedTitle": "Interactive Steering of Hierarchical Clustering",
"fno": "09094378",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Evolutionary Computation",
"Optimisation",
"Pattern Clustering",
"Trees Mathematics",
"Big Data",
"Exploratory Data Analysis",
"Interactive Steering Method",
"Knowledge Driven",
"Intrinsic Data Distribution",
"Method First Maps Each Data Item",
"Data Items",
"Hierarchical Clustering Results",
"Customized Clustering Trees",
"Clustering Algorithms",
"Visualization",
"Data Visualization",
"Buildings",
"Clustering Methods",
"Bayes Methods",
"Measurement",
"Hierarchical Clustering",
"Constrained Clustering",
"Exploratory Data Analysis",
"Tree Visualization"
],
"authors": [
{
"givenName": "Weikai",
"surname": "Yang",
"fullName": "Weikai Yang",
"affiliation": "School of Software, BNRist, Tsinghua University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Xiting",
"surname": "Wang",
"fullName": "Xiting Wang",
"affiliation": "Microsoft Research, Beijing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Jie",
"surname": "Lu",
"fullName": "Jie Lu",
"affiliation": "School of Software, BNRist, Tsinghua University, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Wenwen",
"surname": "Dou",
"fullName": "Wenwen Dou",
"affiliation": "University of North Carolina at Charlotte, Charlotte, NC, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shixia",
"surname": "Liu",
"fullName": "Shixia Liu",
"affiliation": "School of Software, BNRist, Tsinghua University, China",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "10",
"pubDate": "2021-10-01 00:00:00",
"pubType": "trans",
"pages": "3953-3967",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iciibms/2015/8562/0/07439517",
"title": "A new hierarchical clustering algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/iciibms/2015/07439517/12OmNALUoyY",
"parentPublication": {
"id": "proceedings/iciibms/2015/8562/0",
"title": "2015 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/geoprocessing/2010/3951/0/3951a033",
"title": "Vizualizing Large Spatial Datasets in Interactive Maps",
"doi": null,
"abstractUrl": "/proceedings-article/geoprocessing/2010/3951a033/12OmNAYGlzo",
"parentPublication": {
"id": "proceedings/geoprocessing/2010/3951/0",
"title": "2010 Second International Conference on Advanced Geographic Information Systems, Applications, and Services",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wkdd/2010/5397/0/05432668",
"title": "Hierarchical Agglomerative Clustering with Ordering Constraints",
"doi": null,
"abstractUrl": "/proceedings-article/wkdd/2010/05432668/12OmNBhHt7c",
"parentPublication": {
"id": "proceedings/wkdd/2010/5397/0",
"title": "2010 3rd International Conference on Knowledge Discovery and Data Mining (WKDD 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2011/4408/0/4408a982",
"title": "Semi-supervised Hierarchical Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2011/4408a982/12OmNwBjP6u",
"parentPublication": {
"id": "proceedings/icdm/2011/4408/0",
"title": "2011 IEEE 11th International Conference on Data Mining",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi/2006/2747/0/04061364",
"title": "Personalized Hierarchical Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/wi/2006/04061364/12OmNxaw5c9",
"parentPublication": {
"id": "proceedings/wi/2006/2747/0",
"title": "2006 IEEE/WIC/ACM International Conference on Web Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2015/9504/0/9504a310",
"title": "Parallel Hierarchical Clustering in Linearithmic Time for Large-Scale Sequence Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2015/9504a310/12OmNxvwoRM",
"parentPublication": {
"id": "proceedings/icdm/2015/9504/0",
"title": "2015 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2010/4300/0/4300a873",
"title": "Map-TreeMaps: A New Approach for Hierarchical and Topological Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2010/4300a873/12OmNyRg4eb",
"parentPublication": {
"id": "proceedings/icmla/2010/4300/0",
"title": "Machine Learning and Applications, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bdcat/2018/5502/0/550200a191",
"title": "A Hierarchical Multi-Metric Framework for Item Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/bdcat/2018/550200a191/17D45Wuc3aD",
"parentPublication": {
"id": "proceedings/bdcat/2018/5502/0",
"title": "2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2021/3902/0/09671953",
"title": "IDEA: Integrating Divisive and Ensemble-Agglomerate hierarchical clustering framework for arbitrary shape data",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2021/09671953/1A8hoj8SPpS",
"parentPublication": {
"id": "proceedings/big-data/2021/3902/0",
"title": "2021 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnisc/2018/6956/0/695600a208",
"title": "MSTI: A New Clustering Validity Index for Hierarchical Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/icnisc/2018/695600a208/1dUo0ii89hu",
"parentPublication": {
"id": "proceedings/icnisc/2018/6956/0",
"title": "2018 4th Annual International Conference on Network and Information Systems for Computers (ICNISC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "09094379",
"articleId": "1jQNs0xudBS",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09095367",
"articleId": "1jVMiYPPf0I",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "1p1cntpQSWc",
"title": "Jan.",
"year": "2021",
"issueNum": "01",
"idPrefix": "tg",
"pubType": "journal",
"volume": "27",
"label": "Jan.",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1lFEXEfCDg4",
"doi": "10.1109/TVCG.2020.3011155",
"abstract": "High-dimensional labeled data widely exists in many real-world applications such as classification and clustering. One main task in analyzing such datasets is to explore class separations and class boundaries derived from machine learning models. Dimension reduction techniques are commonly applied to support analysts in exploring the underlying decision boundary structures by depicting a low-dimensional representation of the data distributions from multiple classes. However, such projection-based analyses are limited due to their lack of ability to show separations in complex non-linear decision boundary structures and can suffer from heavy distortion and low interpretability. To overcome these issues of separability and interpretability, we propose a visual analysis approach that utilizes the power of explainability from linear projections to support analysts when exploring non-linear separation structures. Our approach is to extract a set of locally linear segments that approximate the original non-linear separations. Unlike traditional projection-based analysis where the data instances are mapped to a single scatterplot, our approach supports the exploration of complex class separations through multiple local projection results. We conduct case studies on two labeled datasets to demonstrate the effectiveness of our approach.",
"abstracts": [
{
"abstractType": "Regular",
"content": "High-dimensional labeled data widely exists in many real-world applications such as classification and clustering. One main task in analyzing such datasets is to explore class separations and class boundaries derived from machine learning models. Dimension reduction techniques are commonly applied to support analysts in exploring the underlying decision boundary structures by depicting a low-dimensional representation of the data distributions from multiple classes. However, such projection-based analyses are limited due to their lack of ability to show separations in complex non-linear decision boundary structures and can suffer from heavy distortion and low interpretability. To overcome these issues of separability and interpretability, we propose a visual analysis approach that utilizes the power of explainability from linear projections to support analysts when exploring non-linear separation structures. Our approach is to extract a set of locally linear segments that approximate the original non-linear separations. Unlike traditional projection-based analysis where the data instances are mapped to a single scatterplot, our approach supports the exploration of complex class separations through multiple local projection results. We conduct case studies on two labeled datasets to demonstrate the effectiveness of our approach.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "High-dimensional labeled data widely exists in many real-world applications such as classification and clustering. One main task in analyzing such datasets is to explore class separations and class boundaries derived from machine learning models. Dimension reduction techniques are commonly applied to support analysts in exploring the underlying decision boundary structures by depicting a low-dimensional representation of the data distributions from multiple classes. However, such projection-based analyses are limited due to their lack of ability to show separations in complex non-linear decision boundary structures and can suffer from heavy distortion and low interpretability. To overcome these issues of separability and interpretability, we propose a visual analysis approach that utilizes the power of explainability from linear projections to support analysts when exploring non-linear separation structures. Our approach is to extract a set of locally linear segments that approximate the original non-linear separations. Unlike traditional projection-based analysis where the data instances are mapped to a single scatterplot, our approach supports the exploration of complex class separations through multiple local projection results. We conduct case studies on two labeled datasets to demonstrate the effectiveness of our approach.",
"title": "Visual Analysis of Class Separations With Locally Linear Segments",
"normalizedTitle": "Visual Analysis of Class Separations With Locally Linear Segments",
"fno": "09146191",
"hasPdf": true,
"idPrefix": "tg",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Learning Artificial Intelligence",
"Pattern Classification",
"Nonlinear Decision Boundary Structures",
"Interpretability",
"Separability",
"Visual Analysis",
"Locally Linear Segments",
"Class Boundaries",
"Machine Learning",
"Dimension Reduction",
"Low Dimensional Representation",
"Data Distributions",
"Projection Based Analyses",
"Class Separations",
"Nonlinear Separation Structures",
"High Dimensional Labeled Data",
"Dimensionality Reduction",
"Data Visualization",
"Visualization",
"Analytical Models",
"Manifolds",
"Data Models",
"Support Vector Machines",
"Visual Analysis",
"Dimension Reduction",
"Class Separation"
],
"authors": [
{
"givenName": "Yuxin",
"surname": "Ma",
"fullName": "Yuxin Ma",
"affiliation": "School of Computing, Informatics & Decision Systems Engineering, Arizona State University, Tempe, AZ, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ross",
"surname": "Maciejewski",
"fullName": "Ross Maciejewski",
"affiliation": "School of Computing, Informatics & Decision Systems Engineering, Arizona State University, Tempe, AZ, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": {
"isEnabled": true,
"codeDownloadUrl": "https://github.com/wintericie/visual-analysis-class-boundary.git",
"codeRepositoryUrl": "https://github.com/wintericie/visual-analysis-class-boundary",
"__typename": "ArticleReplicabilityType"
},
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "01",
"pubDate": "2021-01-01 00:00:00",
"pubType": "trans",
"pages": "241-253",
"year": "2021",
"issn": "1077-2626",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/iita/2009/3859/3/3859c031",
"title": "Supervised Locally Linear Embedding in Tensor Space",
"doi": null,
"abstractUrl": "/proceedings-article/iita/2009/3859c031/12OmNARRYpM",
"parentPublication": {
"id": "proceedings/iita/2009/3859/3",
"title": "2009 Third International Symposium on Intelligent Information Technology Application",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/gcis/2009/3571/2/3571b509",
"title": "A New Method for Linear Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/gcis/2009/3571b509/12OmNqFrGrQ",
"parentPublication": {
"id": "proceedings/gcis/2009/3571/2",
"title": "2009 WRI Global Congress on Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/his/2004/2291/0/22910260",
"title": "Improvement of Non-Linear Mapping Computation for Dimensionality Reduction in Data Visualization and Classification",
"doi": null,
"abstractUrl": "/proceedings-article/his/2004/22910260/12OmNvkpl6Z",
"parentPublication": {
"id": "proceedings/his/2004/2291/0",
"title": "Hybrid Intelligent Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/crv/2005/2319/0/23190290",
"title": "Face Recognition with Weighted Locally Linear Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/crv/2005/23190290/12OmNweBUPT",
"parentPublication": {
"id": "proceedings/crv/2005/2319/0",
"title": "The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cisp/2008/3119/2/3119b039",
"title": "Multi-pose Ear Recognition Based on Improved Locally Linear Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/cisp/2008/3119b039/12OmNyoiZck",
"parentPublication": {
"id": "proceedings/cisp/2008/3119/3",
"title": "Image and Signal Processing, Congress on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2018/0169/0/016900a378",
"title": "An Improved Weighted Local Linear Embedding Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2018/016900a378/17D45WgziSI",
"parentPublication": {
"id": "proceedings/cis/2018/0169/0",
"title": "2018 14th International Conference on Computational Intelligence and Security (CIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2019/01/08440820",
"title": "DimReader: Axis lines that explain non-linear projections",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440820/17D45Xtvp8C",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/01/09903343",
"title": "RankAxis: Towards a Systematic Combination of Projection and Ranking in Multi-Attribute Data Exploration",
"doi": null,
"abstractUrl": "/journal/tg/2023/01/09903343/1GZooOkjYzK",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2022/05/09128033",
"title": "Interpretation of Structural Preservation in Low-Dimensional Embeddings",
"doi": null,
"abstractUrl": "/journal/tk/2022/05/09128033/1l3u8JV5SP6",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vis/2021/3335/0/333500a026",
"title": "Semantic Explanation of Interactive Dimensionality Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/vis/2021/333500a026/1yXuftZECbe",
"parentPublication": {
"id": "proceedings/vis/2021/3335/0",
"title": "2021 IEEE Visualization Conference (VIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08765801",
"articleId": "1bLypqX0rwA",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09145719",
"articleId": "1lE0g1AYf28",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [
{
"id": "1p1cslaAy2s",
"name": "ttg202101-09146191s1-supp1-3011155.mp4",
"location": "https://www.computer.org/csdl/api/v1/extra/ttg202101-09146191s1-supp1-3011155.mp4",
"extension": "mp4",
"size": "88.6 MB",
"__typename": "WebExtraType"
}
],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNCau3ce",
"title": "April-June",
"year": "2015",
"issueNum": "02",
"idPrefix": "lt",
"pubType": "journal",
"volume": "8",
"label": "April-June",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "13rRUwfZC2q",
"doi": "10.1109/TLT.2014.2378786",
"abstract": "Engagement is critical to the success of learning activities such as writing, and can be promoted with appropriate feedback. Current engagement measures rely mostly on data collected by observers or self-reported by the participants. In this paper, we describe a learning analytic system called Tracer, which derives behavioral engagement measures and creates visualizations of behavioral patterns of students writing on a cloud-based application. The tool records the intermediate stages of document development and uses this data to measure learners' behavioral engagement and derive three visualizations. Writers (N= 23 University students) participated in a controlled one-hour writing session in which they post-facto self-reported their level of behavioral engagement. Results show that the level of behavioral engagement automatically estimated by the system correlates with the level reported by the participants. Additionally, users stated that the visualizations were coherent with their writing activity and were useful to help them reflect on the writing process.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Engagement is critical to the success of learning activities such as writing, and can be promoted with appropriate feedback. Current engagement measures rely mostly on data collected by observers or self-reported by the participants. In this paper, we describe a learning analytic system called Tracer, which derives behavioral engagement measures and creates visualizations of behavioral patterns of students writing on a cloud-based application. The tool records the intermediate stages of document development and uses this data to measure learners' behavioral engagement and derive three visualizations. Writers (N= 23 University students) participated in a controlled one-hour writing session in which they post-facto self-reported their level of behavioral engagement. Results show that the level of behavioral engagement automatically estimated by the system correlates with the level reported by the participants. Additionally, users stated that the visualizations were coherent with their writing activity and were useful to help them reflect on the writing process.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Engagement is critical to the success of learning activities such as writing, and can be promoted with appropriate feedback. Current engagement measures rely mostly on data collected by observers or self-reported by the participants. In this paper, we describe a learning analytic system called Tracer, which derives behavioral engagement measures and creates visualizations of behavioral patterns of students writing on a cloud-based application. The tool records the intermediate stages of document development and uses this data to measure learners' behavioral engagement and derive three visualizations. Writers (N= 23 University students) participated in a controlled one-hour writing session in which they post-facto self-reported their level of behavioral engagement. Results show that the level of behavioral engagement automatically estimated by the system correlates with the level reported by the participants. Additionally, users stated that the visualizations were coherent with their writing activity and were useful to help them reflect on the writing process.",
"title": "Measuring and Visualizing Students’ Behavioral Engagement in Writing Activities",
"normalizedTitle": "Measuring and Visualizing Students’ Behavioral Engagement in Writing Activities",
"fno": "06979251",
"hasPdf": true,
"idPrefix": "lt",
"keywords": [
"Writing",
"Data Visualization",
"Educational Institutions",
"Clustering Algorithms",
"Atmospheric Measurements",
"Particle Measurements",
"Context",
"Learning Analytics And Writing Assessment",
"E Learning Tools",
"Computers And Education",
"Visualization"
],
"authors": [
{
"givenName": "Ming",
"surname": "Liu",
"fullName": "Ming Liu",
"affiliation": "School of Computer and Information Science, Southwest University, Chongqing, China",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Rafael A.",
"surname": "Calvo",
"fullName": "Rafael A. Calvo",
"affiliation": "School of Electrical and Information Engineering, The University of Sydney, Sydney, Australia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Abelardo",
"surname": "Pardo",
"fullName": "Abelardo Pardo",
"affiliation": "School of Electrical and Information Engineering, The University of Sydney, Australia",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Andrew",
"surname": "Martin",
"fullName": "Andrew Martin",
"affiliation": "School of Education, University of New South Wales, Sydney, NSW, Australia",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": false,
"showRecommendedArticles": true,
"isOpenAccess": true,
"issueNum": "02",
"pubDate": "2015-04-01 00:00:00",
"pubType": "trans",
"pages": "215-224",
"year": "2015",
"issn": "1939-1382",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/icdar/2013/4999/0/06628786",
"title": "Mental Workload Classification via Online Writing Features",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2013/06628786/12OmNBp52ue",
"parentPublication": {
"id": "proceedings/icdar/2013/4999/0",
"title": "2013 12th International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2013/5009/0/5009a421",
"title": "Tracer: A Tool to Measure and Visualize Student Engagement in Writing Activities",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2013/5009a421/12OmNCgrCW6",
"parentPublication": {
"id": "proceedings/icalt/2013/5009/0",
"title": "2013 IEEE 13th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2015/9953/0/07344575",
"title": "Predicting students' happiness from physiology, phone, mobility, and behavioral data",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2015/07344575/12OmNvk7JRg",
"parentPublication": {
"id": "proceedings/acii/2015/9953/0",
"title": "2015 International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2015/9953/0/07344688",
"title": "Definitions of engagement in human-agent interaction",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2015/07344688/12OmNwEJ0Pk",
"parentPublication": {
"id": "proceedings/acii/2015/9953/0",
"title": "2015 International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iset/2017/3031/0/08005384",
"title": "Student Engagement in Online Learning: A Review",
"doi": null,
"abstractUrl": "/proceedings-article/iset/2017/08005384/12OmNyQYtr2",
"parentPublication": {
"id": "proceedings/iset/2017/3031/0",
"title": "2017 International Symposium on Educational Technology (ISET)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2016/1790/0/07757733",
"title": "Measuring cognitive engagement through interactive, constructive, active and passive learning activities",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2016/07757733/12OmNzZWbFG",
"parentPublication": {
"id": "proceedings/fie/2016/1790/0",
"title": "2016 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2016/1790/0/07757545",
"title": "Determining progress in writing competency by assessing students' argumentation",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2016/07757545/12OmNzZmZxj",
"parentPublication": {
"id": "proceedings/fie/2016/1790/0",
"title": "2016 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2022/6244/0/09962406",
"title": "Impact on Second Language Writing via an Intelligent Writing Assistant and Metacognitive Training",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2022/09962406/1IHohtYOxzO",
"parentPublication": {
"id": "proceedings/fie/2022/6244/0",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/percom-workshops/2019/9151/0/08730722",
"title": "Development of a Psychological-Behavioral Model of Behavioral Change",
"doi": null,
"abstractUrl": "/proceedings-article/percom-workshops/2019/08730722/1aDSH6iTDgs",
"parentPublication": {
"id": "proceedings/percom-workshops/2019/9151/0",
"title": "2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2019/1746/0/09028617",
"title": "Tracking learning engagement at the student level",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2019/09028617/1iffvuh5J3G",
"parentPublication": {
"id": "proceedings/fie/2019/1746/0",
"title": "2019 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "06936358",
"articleId": "13rRUx0xPBp",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06897963",
"articleId": "13rRUxE04q2",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
{
"issue": {
"id": "12OmNBhpS2L",
"title": "March",
"year": "2020",
"issueNum": "03",
"idPrefix": "tc",
"pubType": "journal",
"volume": "69",
"label": "March",
"downloadables": {
"hasCover": false,
"__typename": "PeriodicalIssueDownloadablesType"
},
"__typename": "PeriodicalIssue"
},
"article": {
"id": "1emyiZCrIJ2",
"doi": "10.1109/TC.2019.2949042",
"abstract": "A Generative Adversarial Network (GAN) is an adversarial learning approach which empowers conventional deep learning methods by alleviating the demands of massive labeled datasets. However, GAN training can be computationally-intensive limiting its feasibility in resource-limited edge devices. In this paper, we propose an approximate GAN (ApGAN) for accelerating GANs from both algorithm and hardware implementation perspectives. First, inspired by the binary pattern feature extraction method along with binarized representation entropy, the existing Deep Convolutional GAN (DCGAN) algorithm is modified by binarizing the weights for a specific portion of layers within both the generator and discriminator models. Further reduction in storage and computation resources is achieved by leveraging a novel hardware-configurable in-memory addition scheme, which can operate in the accurate and approximate modes. Finally, a memristor-based processing-in-memory accelerator for ApGAN is developed. The performance of the ApGAN accelerator on different data-sets such as Fashion-MNIST, CIFAR-10, STL-10, and celeb-A is evaluated and compared with recent GAN accelerator designs. With almost the same Inception Score (IS) to the baseline GAN, the ApGAN accelerator can increase the energy-efficiency by ~28.6× achieving 35-fold speedup compared with a baseline GPU platform. Additionally, it shows 2.5× and 5.8× higher energy-efficiency and speedup over CMOS-ASIC accelerator subject to an 11 percent reduction in IS.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A Generative Adversarial Network (GAN) is an adversarial learning approach which empowers conventional deep learning methods by alleviating the demands of massive labeled datasets. However, GAN training can be computationally-intensive limiting its feasibility in resource-limited edge devices. In this paper, we propose an approximate GAN (ApGAN) for accelerating GANs from both algorithm and hardware implementation perspectives. First, inspired by the binary pattern feature extraction method along with binarized representation entropy, the existing Deep Convolutional GAN (DCGAN) algorithm is modified by binarizing the weights for a specific portion of layers within both the generator and discriminator models. Further reduction in storage and computation resources is achieved by leveraging a novel hardware-configurable in-memory addition scheme, which can operate in the accurate and approximate modes. Finally, a memristor-based processing-in-memory accelerator for ApGAN is developed. The performance of the ApGAN accelerator on different data-sets such as Fashion-MNIST, CIFAR-10, STL-10, and celeb-A is evaluated and compared with recent GAN accelerator designs. With almost the same Inception Score (IS) to the baseline GAN, the ApGAN accelerator can increase the energy-efficiency by ~28.6× achieving 35-fold speedup compared with a baseline GPU platform. Additionally, it shows 2.5× and 5.8× higher energy-efficiency and speedup over CMOS-ASIC accelerator subject to an 11 percent reduction in IS.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A Generative Adversarial Network (GAN) is an adversarial learning approach which empowers conventional deep learning methods by alleviating the demands of massive labeled datasets. However, GAN training can be computationally-intensive limiting its feasibility in resource-limited edge devices. In this paper, we propose an approximate GAN (ApGAN) for accelerating GANs from both algorithm and hardware implementation perspectives. First, inspired by the binary pattern feature extraction method along with binarized representation entropy, the existing Deep Convolutional GAN (DCGAN) algorithm is modified by binarizing the weights for a specific portion of layers within both the generator and discriminator models. Further reduction in storage and computation resources is achieved by leveraging a novel hardware-configurable in-memory addition scheme, which can operate in the accurate and approximate modes. Finally, a memristor-based processing-in-memory accelerator for ApGAN is developed. The performance of the ApGAN accelerator on different data-sets such as Fashion-MNIST, CIFAR-10, STL-10, and celeb-A is evaluated and compared with recent GAN accelerator designs. With almost the same Inception Score (IS) to the baseline GAN, the ApGAN accelerator can increase the energy-efficiency by ~28.6× achieving 35-fold speedup compared with a baseline GPU platform. Additionally, it shows 2.5× and 5.8× higher energy-efficiency and speedup over CMOS-ASIC accelerator subject to an 11 percent reduction in IS.",
"title": "ApGAN: Approximate GAN for Robust Low Energy Learning From Imprecise Components",
"normalizedTitle": "ApGAN: Approximate GAN for Robust Low Energy Learning From Imprecise Components",
"fno": "08880521",
"hasPdf": true,
"idPrefix": "tc",
"keywords": [
"Feature Extraction",
"Learning Artificial Intelligence",
"Memristors",
"Neural Nets",
"Robust Low Energy Learning",
"Adversarial Learning Approach",
"Conventional Deep Learning Methods",
"Massive Labeled Datasets",
"Resource Limited Edge Devices",
"Hardware Implementation Perspectives",
"Binary Pattern Feature Extraction Method",
"Binarized Representation Entropy",
"Discriminator Models",
"Memristor Based Processing In Memory Accelerator",
"Ap GAN Accelerator",
"CMOS ASIC Accelerator Subject",
"Hardware Configurable In Memory Addition Scheme",
"Deep Convolutional GAN Algorithm",
"Approximate GAN",
"Fashion MNIST",
"CIFAR 10",
"STL 10",
"Celeb A",
"Inception Score",
"Gallium Nitride",
"Training",
"Generative Adversarial Networks",
"Random Access Memory",
"Hardware",
"Generators",
"Computational Modeling",
"Generative Adversarial Network",
"In Memory Processing Platform",
"Neural Network Acceleration",
"Hardware Mapping"
],
"authors": [
{
"givenName": "Arman",
"surname": "Roohi",
"fullName": "Arman Roohi",
"affiliation": "Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shadi",
"surname": "Sheikhfaal",
"fullName": "Shadi Sheikhfaal",
"affiliation": "Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Shaahin",
"surname": "Angizi",
"fullName": "Shaahin Angizi",
"affiliation": "Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Deliang",
"surname": "Fan",
"fullName": "Deliang Fan",
"affiliation": "Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
},
{
"givenName": "Ronald F",
"surname": "DeMara",
"fullName": "Ronald F DeMara",
"affiliation": "Department of Electrical and Computer Engineering, University of Central Florida, Orlando, FL, USA",
"__typename": "ArticleAuthorType"
}
],
"replicability": null,
"showBuyMe": true,
"showRecommendedArticles": true,
"isOpenAccess": false,
"issueNum": "03",
"pubDate": "2020-03-01 00:00:00",
"pubType": "trans",
"pages": "349-360",
"year": "2020",
"issn": "0018-9340",
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"recommendedArticles": [
{
"id": "proceedings/micro/2018/6240/0/624000a669",
"title": "LerGAN: A Zero-Free, Low Data Movement and PIM-Based GAN Architecture",
"doi": null,
"abstractUrl": "/proceedings-article/micro/2018/624000a669/17D45WrVgb6",
"parentPublication": {
"id": "proceedings/micro/2018/6240/0",
"title": "2018 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccd/2018/8477/0/847700a266",
"title": "PIM-TGAN: A Processing-in-Memory Accelerator for Ternary Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/iccd/2018/847700a266/17D45Wt3Ewc",
"parentPublication": {
"id": "proceedings/iccd/2018/8477/0",
"title": "2018 IEEE 36th International Conference on Computer Design (ICCD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2018/3788/0/08545081",
"title": "GP-GAN: Gender Preserving GAN for Synthesizing Faces from Landmarks",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2018/08545081/17D45XDIXOU",
"parentPublication": {
"id": "proceedings/icpr/2018/3788/0",
"title": "2018 24th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000a821",
"title": "FaceID-GAN: Learning a Symmetry Three-Player GAN for Identity-Preserving Face Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000a821/17D45Xh13pk",
"parentPublication": {
"id": "proceedings/cvpr/2018/6420/0",
"title": "2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300e501",
"title": "Seeing What a GAN Cannot Generate",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300e501/1hVlGKg2532",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093525",
"title": "FX-GAN: Self-Supervised GAN Learning via Feature Exchange",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093525/1jPbxvOsk6s",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asonam/2019/6868/0/09073134",
"title": "Opioid Relapse Prediction with GAN",
"doi": null,
"abstractUrl": "/proceedings-article/asonam/2019/09073134/1jjAccqe2pW",
"parentPublication": {
"id": "proceedings/asonam/2019/6868/0",
"title": "2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/2021/09/09146333",
"title": "LrGAN: A Compact and Energy Efficient PIM-Based Architecture for GAN Training",
"doi": null,
"abstractUrl": "/journal/tc/2021/09/09146333/1lFF1jOOaEU",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2020/9360/0/09151060",
"title": "Triple-GAN: Progressive Face Aging with Triple Translation Loss",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2020/09151060/1lPHg6ccqac",
"parentPublication": {
"id": "proceedings/cvprw/2020/9360/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800a469",
"title": "Transformation GAN for Unsupervised Image Synthesis and Representation Learning",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800a469/1m3nzGAm5qg",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"adjacentArticles": {
"previous": {
"fno": "08877747",
"articleId": "1hkwxSjJ9HG",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08880507",
"articleId": "1emyih38HsY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"webExtras": [],
"articleVideos": []
}
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.