data
dict |
|---|
{
"proceeding": {
"id": "17D45VtKir9",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"acronym": "iv",
"groupId": "1000370",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45XvMcd7",
"doi": "10.1109/iV.2018.00027",
"title": "Radial Calendar of Consumption",
"normalizedTitle": "Radial Calendar of Consumption",
"abstract": "In the analysis of time-series, it is common to focus on the identification of changing behaviours and patterns that repeat over time. In this article, we propose a visualisation model based on a radial calendar to analyse the Portuguese's consumption data. The model is intended to assist the analysts within a Portuguese Retail Company in the identification of periodic patterns and deviations from the normal consumption values. Our main contributions are: (i) the representation and characterisation of the Portuguese's consumption behaviour over time; (ii) a radial visualisation model to identify consumption patterns and their deviations; and (iii) a user case study to compare this visualisation model to a regular calendar layout. Our model has as main requirement the representation of the maximum amount of data in one single space. As such, it is ideal for analysts without prior knowledge of the data, since it provides an effective and efficient qualitative overview of the Portuguese's consumption.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In the analysis of time-series, it is common to focus on the identification of changing behaviours and patterns that repeat over time. In this article, we propose a visualisation model based on a radial calendar to analyse the Portuguese's consumption data. The model is intended to assist the analysts within a Portuguese Retail Company in the identification of periodic patterns and deviations from the normal consumption values. Our main contributions are: (i) the representation and characterisation of the Portuguese's consumption behaviour over time; (ii) a radial visualisation model to identify consumption patterns and their deviations; and (iii) a user case study to compare this visualisation model to a regular calendar layout. Our model has as main requirement the representation of the maximum amount of data in one single space. As such, it is ideal for analysts without prior knowledge of the data, since it provides an effective and efficient qualitative overview of the Portuguese's consumption.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In the analysis of time-series, it is common to focus on the identification of changing behaviours and patterns that repeat over time. In this article, we propose a visualisation model based on a radial calendar to analyse the Portuguese's consumption data. The model is intended to assist the analysts within a Portuguese Retail Company in the identification of periodic patterns and deviations from the normal consumption values. Our main contributions are: (i) the representation and characterisation of the Portuguese's consumption behaviour over time; (ii) a radial visualisation model to identify consumption patterns and their deviations; and (iii) a user case study to compare this visualisation model to a regular calendar layout. Our model has as main requirement the representation of the maximum amount of data in one single space. As such, it is ideal for analysts without prior knowledge of the data, since it provides an effective and efficient qualitative overview of the Portuguese's consumption.",
"fno": "720200a096",
"keywords": [
"Consumer Behaviour",
"Data Visualisation",
"Retail Data Processing",
"Time Series",
"Consumption Patterns",
"Radial Calendar",
"Time Series",
"Periodic Patterns",
"Radial Visualisation Model",
"Portuguese Consumption Behaviour",
"Portuguese Retail Company",
"Portuguese Consumption Data",
"Calendar Layout",
"Data Visualization",
"Spirals",
"Data Models",
"Task Analysis",
"Analytical Models",
"Layout",
"Time Series",
"Information Visualisation",
"Radial Calendar",
"Consumption"
],
"authors": [
{
"affiliation": null,
"fullName": "Catarina Maçãs",
"givenName": "Catarina",
"surname": "Maçãs",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Penousal Machado",
"givenName": "Penousal",
"surname": "Machado",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-07-01T00:00:00",
"pubType": "proceedings",
"pages": "96-102",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-7202-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "720200a091",
"articleId": "17D45VtKivI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "720200a103",
"articleId": "17D45VTRot3",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/maee/2013/4975/0/4975a101",
"title": "Study on Flow Field Structure in Axisymmetric Radial Flow",
"doi": null,
"abstractUrl": "/proceedings-article/maee/2013/4975a101/12OmNAle6TF",
"parentPublication": {
"id": "proceedings/maee/2013/4975/0",
"title": "2013 International Conference on Mechanical and Automation Engineering (MAEE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mass/2010/7488/0/05663990",
"title": "Interactionless calendar-based training for 802.11 localization",
"doi": null,
"abstractUrl": "/proceedings-article/mass/2010/05663990/12OmNBVrjpS",
"parentPublication": {
"id": "proceedings/mass/2010/7488/0",
"title": "2010 IEEE 7th International Conference on Mobile Ad-Hoc and Sensor Systems (MASS 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-infovis/1999/0431/0/04310004",
"title": "Cluster and Calendar Based Visualization of Time Series Data",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-infovis/1999/04310004/12OmNrAv3Rm",
"parentPublication": {
"id": "proceedings/ieee-infovis/1999/0431/0",
"title": "Information Visualization, IEEE Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2004/2158/1/01315049",
"title": "Perceptual organization of radial symmetries",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2004/01315049/12OmNxdm4xh",
"parentPublication": {
"id": "proceedings/cvpr/2004/2158/1",
"title": "Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2015/8391/0/8391c345",
"title": "On the Equivalence of Moving Entrance Pupil and Radial Distortion for Camera Calibration",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391c345/12OmNyshmIc",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2007/03/v0583",
"title": "A Radial Adaptation of the Sugiyama Framework for Visualizing Hierarchical Information",
"doi": null,
"abstractUrl": "/journal/tg/2007/03/v0583/13rRUyY28Ym",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icitbs/2019/1307/0/130700a161",
"title": "An Energy Consumption Control Scheme Based on Radial Basis Function in Wireless Sensor Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icitbs/2019/130700a161/18AuUXwAQI8",
"parentPublication": {
"id": "proceedings/icitbs/2019/1307/0",
"title": "2019 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09814874",
"title": "Target Netgrams: An Annulus-Constrained Stress Model for Radial Graph Visualization",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09814874/1EJBn7YxwGY",
"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/pacificvis/2020/5697/0/09086215",
"title": "A Radial Visualisation for Model Comparison and Feature Identification",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2020/09086215/1kuHmVbD56w",
"parentPublication": {
"id": "proceedings/pacificvis/2020/5697/0",
"title": "2020 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1rSR7vfukX6",
"title": "2020 24th International Conference Information Visualisation (IV)",
"acronym": "iv",
"groupId": "1000370",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1rSRd8jh960",
"doi": "10.1109/IV51561.2020.00072",
"title": "Optimizing a radial visualization with a genetic algorithm",
"normalizedTitle": "Optimizing a radial visualization with a genetic algorithm",
"abstract": "We consider in this paper a radial visualization called POIViz as a starting point to be improved with an optimization procedure. In our previous work, we studied POIViz and showed that it was able to represent multidimensional data in 2D within a few seconds, even for datasets with millions of records. We provided a simple heuristic to select the Points Of Interest (POIs), i.e., the 2D anchors that determine the layout of the data. In this paper, we extend POIViz to Gen-POIViz by proposing a genetic algorithm (GA) that can greatly optimize the quality of the visualization. The GA searches for a set of POIs that minimizes a cost function that is based on Kruskal's stress. Furthermore, Gen-POIViz can find relevant POIs with a small sample of the data only, and thus it can compute a projection of the complete data in a very short time. We provide comparative results with standard methods in data projection. Gen-POIViz obtains results with a quality that is between force-directed Multidimensional Scaling (MDS) and Principal Components Analysis (PCA). On larger datasets, we show the advantage of our method when it works on a data sample. It can be much faster than MDS, and it can be run with even larger datasets for which other methods fail.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We consider in this paper a radial visualization called POIViz as a starting point to be improved with an optimization procedure. In our previous work, we studied POIViz and showed that it was able to represent multidimensional data in 2D within a few seconds, even for datasets with millions of records. We provided a simple heuristic to select the Points Of Interest (POIs), i.e., the 2D anchors that determine the layout of the data. In this paper, we extend POIViz to Gen-POIViz by proposing a genetic algorithm (GA) that can greatly optimize the quality of the visualization. The GA searches for a set of POIs that minimizes a cost function that is based on Kruskal's stress. Furthermore, Gen-POIViz can find relevant POIs with a small sample of the data only, and thus it can compute a projection of the complete data in a very short time. We provide comparative results with standard methods in data projection. Gen-POIViz obtains results with a quality that is between force-directed Multidimensional Scaling (MDS) and Principal Components Analysis (PCA). On larger datasets, we show the advantage of our method when it works on a data sample. It can be much faster than MDS, and it can be run with even larger datasets for which other methods fail.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We consider in this paper a radial visualization called POIViz as a starting point to be improved with an optimization procedure. In our previous work, we studied POIViz and showed that it was able to represent multidimensional data in 2D within a few seconds, even for datasets with millions of records. We provided a simple heuristic to select the Points Of Interest (POIs), i.e., the 2D anchors that determine the layout of the data. In this paper, we extend POIViz to Gen-POIViz by proposing a genetic algorithm (GA) that can greatly optimize the quality of the visualization. The GA searches for a set of POIs that minimizes a cost function that is based on Kruskal's stress. Furthermore, Gen-POIViz can find relevant POIs with a small sample of the data only, and thus it can compute a projection of the complete data in a very short time. We provide comparative results with standard methods in data projection. Gen-POIViz obtains results with a quality that is between force-directed Multidimensional Scaling (MDS) and Principal Components Analysis (PCA). On larger datasets, we show the advantage of our method when it works on a data sample. It can be much faster than MDS, and it can be run with even larger datasets for which other methods fail.",
"fno": "913400a409",
"keywords": [
"Computational Geometry",
"Data Visualisation",
"Genetic Algorithms",
"Minimisation",
"Principal Component Analysis",
"Radial Visualization",
"Genetic Algorithm",
"Multidimensional Data",
"GA",
"Data Projection",
"Data Sample",
"Force Directed Multidimensional Scaling",
"Gen POI Viz",
"Principal Components Analysis",
"Visualization",
"Two Dimensional Displays",
"Layout",
"Data Visualization",
"Stress",
"Genetic Algorithms",
"Principal Component Analysis",
"Visual Data Mining",
"Large Datasets",
"Data Projection"
],
"authors": [
{
"affiliation": "University of Tours,LIFAT,France,EA6300",
"fullName": "F. Bouali",
"givenName": "F.",
"surname": "Bouali",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Tours,LIFAT,France,EA6300",
"fullName": "B. Serres",
"givenName": "B.",
"surname": "Serres",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Tours,LIFAT,France,EA6300",
"fullName": "C. Guinot",
"givenName": "C.",
"surname": "Guinot",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Tours,LIFAT,France,EA6300",
"fullName": "G. Venturini",
"givenName": "G.",
"surname": "Venturini",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-09-01T00:00:00",
"pubType": "proceedings",
"pages": "409-414",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-9134-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "913400a403",
"articleId": "1rSR9s5dmXS",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "913400a415",
"articleId": "1rSRdimCgJG",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/visual/1993/3940/0/00398872",
"title": "Towards a texture naming system: Identifying relevant dimensions of texture",
"doi": null,
"abstractUrl": "/proceedings-article/visual/1993/00398872/12OmNAWYKKq",
"parentPublication": {
"id": "proceedings/visual/1993/3940/0",
"title": "Proceedings Visualization '93",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2013/5099/0/5099a008",
"title": "Feature Learning by Multidimensional Scaling and Its Applications in Object Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2013/5099a008/12OmNAkWvwV",
"parentPublication": {
"id": "proceedings/sibgrapi/2013/5099/0",
"title": "2013 XXVI Conference on Graphics, Patterns and Images",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieee-vis/2002/7498/0/7498jayarama",
"title": "A Radial Focus+Context Visualization for Multi-Dimensional Functions",
"doi": null,
"abstractUrl": "/proceedings-article/ieee-vis/2002/7498jayarama/12OmNCw3z94",
"parentPublication": {
"id": "proceedings/ieee-vis/2002/7498/0",
"title": "Visualization Conference, IEEE",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigdata-congress/2014/5057/0/06906829",
"title": "A Combinatorial Approach to Multidimensional Scaling",
"doi": null,
"abstractUrl": "/proceedings-article/bigdata-congress/2014/06906829/12OmNwfb6Sm",
"parentPublication": {
"id": "proceedings/bigdata-congress/2014/5057/0",
"title": "2014 IEEE International Congress on Big Data (BigData Congress)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2016/9005/0/07841022",
"title": "TSmap3D: Browser visualization of high dimensional time series data",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2016/07841022/12OmNx0A7EU",
"parentPublication": {
"id": "proceedings/big-data/2016/9005/0",
"title": "2016 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2000/0743/0/07430277",
"title": "A Browsing System for a Database Using Visualization of User Preferences",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2000/07430277/12OmNxVDuV1",
"parentPublication": {
"id": "proceedings/iv/2000/0743/0",
"title": "2000 IEEE Conference on Information Visualization. An International Conference on Computer Visualization and Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2015/8391/0/8391c255",
"title": "Classical Scaling Revisited",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391c255/12OmNzUgcXm",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08447558",
"title": "Immersive Visualization of Abstract Information: An Evaluation on Dimensionally-Reduced Data Scatterplots",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08447558/13bd1tMztYK",
"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/2019/01/08440845",
"title": "Shape-preserving Star Coordinates",
"doi": null,
"abstractUrl": "/journal/tg/2019/01/08440845/17D45WYQJ9Z",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2006/2602/0/01648341",
"title": "POLARMAP - Efficient Visualisation of High Dimensional Data",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2006/01648341/1h0NRnrJIOc",
"parentPublication": {
"id": "proceedings/iv/2006/2602/0",
"title": "Tenth International Conference on Information Visualisation (IV'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNCbU3aC",
"title": "Parallel and Distributed Systems, International Conference on",
"acronym": "icpads",
"groupId": "1000534",
"volume": "0",
"displayVolume": "0",
"year": "2009",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyS6RAw",
"doi": "10.1109/ICPADS.2009.21",
"title": "Modified Simultaneous Algebraic Reconstruction Technique and its Parallelization in Cryo-electron Tomography",
"normalizedTitle": "Modified Simultaneous Algebraic Reconstruction Technique and its Parallelization in Cryo-electron Tomography",
"abstract": "Three-dimensional reconstruction of cryo-electron tomography (cryo-ET) has emerged as the leading technique in analyzing structures of complex pleomorphic cellulars. A classical iterative method, simultaneous algebraic reconstruction technique (SART), has been employed to reconstruct volume images in cryo-ET. However, SART starts with an arbitrary approximation and takes into account only a weighted factor when updating density value in every error-correction iterative procedure, thus limits the improvement of the reconstruction resolution. Facing these problems, we present a modified simultaneous algebraic reconstruction technique (MSART) which applies several key techniques, a back projection technique (BPT) and an adaptive adjustment of corrections. Experimental results show that MSART can improve significantly the quality of reconstruction. Additionally, in order to address the computational requirements demanded by the reconstruction of large volumes, we have presented and implanted a strategy to parallel the MSART algorithm on DAWNING 4000H cluster system, and obtained a good computational performance.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Three-dimensional reconstruction of cryo-electron tomography (cryo-ET) has emerged as the leading technique in analyzing structures of complex pleomorphic cellulars. A classical iterative method, simultaneous algebraic reconstruction technique (SART), has been employed to reconstruct volume images in cryo-ET. However, SART starts with an arbitrary approximation and takes into account only a weighted factor when updating density value in every error-correction iterative procedure, thus limits the improvement of the reconstruction resolution. Facing these problems, we present a modified simultaneous algebraic reconstruction technique (MSART) which applies several key techniques, a back projection technique (BPT) and an adaptive adjustment of corrections. Experimental results show that MSART can improve significantly the quality of reconstruction. Additionally, in order to address the computational requirements demanded by the reconstruction of large volumes, we have presented and implanted a strategy to parallel the MSART algorithm on DAWNING 4000H cluster system, and obtained a good computational performance.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Three-dimensional reconstruction of cryo-electron tomography (cryo-ET) has emerged as the leading technique in analyzing structures of complex pleomorphic cellulars. A classical iterative method, simultaneous algebraic reconstruction technique (SART), has been employed to reconstruct volume images in cryo-ET. However, SART starts with an arbitrary approximation and takes into account only a weighted factor when updating density value in every error-correction iterative procedure, thus limits the improvement of the reconstruction resolution. Facing these problems, we present a modified simultaneous algebraic reconstruction technique (MSART) which applies several key techniques, a back projection technique (BPT) and an adaptive adjustment of corrections. Experimental results show that MSART can improve significantly the quality of reconstruction. Additionally, in order to address the computational requirements demanded by the reconstruction of large volumes, we have presented and implanted a strategy to parallel the MSART algorithm on DAWNING 4000H cluster system, and obtained a good computational performance.",
"fno": "3900a384",
"keywords": [
"Cryo Electron Tomography",
"3 D Reconstruction",
"Iterative Method",
"Modified Simultaneous Algebraic Reconstruction Technique MSART",
"Parallel Algorithm"
],
"authors": [
{
"affiliation": null,
"fullName": "Xiaohua Wan",
"givenName": "Xiaohua",
"surname": "Wan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Fa Zhang",
"givenName": "Fa",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Zhiyong Liu",
"givenName": "Zhiyong",
"surname": "Liu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icpads",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2009-12-01T00:00:00",
"pubType": "proceedings",
"pages": "384-390",
"year": "2009",
"issn": "1521-9097",
"isbn": "978-0-7695-3900-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3900a376",
"articleId": "12OmNvmXJ5N",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3900a391",
"articleId": "12OmNqBtj8u",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icip/1998/8821/2/882120706",
"title": "Reconstruction problems in 3D for viral cryo electron microscopy",
"doi": null,
"abstractUrl": "/proceedings-article/icip/1998/882120706/12OmNBpEeWP",
"parentPublication": {
"id": "proceedings/icip/1998/8821/3",
"title": "Image Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnc/2009/3736/6/3736f387",
"title": "Improving Algebraic Reconstruction Techniques with Nonlinear Iterating Algorithms",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2009/3736f387/12OmNBsLPdR",
"parentPublication": {
"id": "proceedings/icnc/2009/3736/6",
"title": "2009 Fifth International Conference on Natural Computation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ic3/2016/3251/0/07880219",
"title": "Regularization based simultaneous algebraic reconstruction techniques for computed tomography",
"doi": null,
"abstractUrl": "/proceedings-article/ic3/2016/07880219/12OmNC1oT6i",
"parentPublication": {
"id": "proceedings/ic3/2016/3251/0",
"title": "2016 Ninth International Conference on Contemporary Computing (IC3)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/case/2009/3728/0/3728a242",
"title": "Image Reconstruction Algorithm Based on Algebraic Neural Network for Electrical Resistance Tomography",
"doi": null,
"abstractUrl": "/proceedings-article/case/2009/3728a242/12OmNCcKQwq",
"parentPublication": {
"id": "proceedings/case/2009/3728/0",
"title": "2009 IITA International Conference on Control, Automation and Systems Engineering, CASE 2009",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnc/2008/3304/3/3304c215",
"title": "Improving on Algebraic Reconstruction Technique",
"doi": null,
"abstractUrl": "/proceedings-article/icnc/2008/3304c215/12OmNrIJqAW",
"parentPublication": {
"id": "proceedings/icnc/2008/3304/3",
"title": "2008 Fourth International Conference on Natural Computation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cmc/2010/3989/2/3989b047",
"title": "Super Converging Speed of Our Nonlinear Auto-adapted Iterative Reconstructing Technique",
"doi": null,
"abstractUrl": "/proceedings-article/cmc/2010/3989b047/12OmNviZlqm",
"parentPublication": {
"id": "proceedings/cmc/2010/3989/2",
"title": "Communications and Mobile Computing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/micai/2011/4605/0/4605a129",
"title": "Algebraic Models for Accurate LFS Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/micai/2011/4605a129/12OmNwDj19n",
"parentPublication": {
"id": "proceedings/micai/2011/4605/0",
"title": "2011 10th Mexican International Conference on Artificial Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2012/4896/0/4896a132",
"title": "TV OS-SART with Fractional Order Integral Filtering",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2012/4896a132/12OmNxxdZz5",
"parentPublication": {
"id": "proceedings/cis/2012/4896/0",
"title": "2012 Eighth International Conference on Computational Intelligence and Security",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/2.812E41",
"title": "Self-Supervised Cryo-Electron Tomography Volumetric Image Restoration from Single Noisy Volume with Sparsity Constraint",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/2.812E41/1BmL53XVH0c",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aipr/2021/2471/0/09762209",
"title": "Practical Analysis of Macromolecule Identity from Cryo-electron Tomography Images using Deep Learning",
"doi": null,
"abstractUrl": "/proceedings-article/aipr/2021/09762209/1CT9aP80A1i",
"parentPublication": {
"id": "proceedings/aipr/2021/2471/0",
"title": "2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "17D45VtKisC",
"title": "2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "1001586",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45XoXP4S",
"doi": "10.1109/BIBM.2018.8621363",
"title": "Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms",
"normalizedTitle": "Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms",
"abstract": "Electron Cryo-Tomography (ECT) allows 3D visualization of subcellular structures at the submolecular resolution in close to the native state. However, due to the high degree of structural complexity and imaging limits, the automatic segmentation of cellular components from ECT images is very difficult. To complement and speed up existing segmentation methods, it is desirable to develop a generic cell component segmentation method that is 1) not specific to particular types of cellular components, 2) able to segment unknown cellular components, 3) fully unsupervised and does not rely on the availability of training data. As an important step towards this goal, in this paper, we propose a saliency detection method that computes the likelihood that a subregion in a tomogram stands out from the background. Our method consists of four steps: supervoxel over-segmentation, feature extraction, feature matrix decomposition, and computation of saliency. The method produces a distribution map that represents the regions’ saliency in tomograms. Our experiments show that our method can successfully label most salient regions detected by a human observer, and able to filter out regions not containing cellular components. Therefore, our method can remove the majority of the background region, and significantly speed up the subsequent processing of segmentation and recognition of cellular components captured by ECT.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Electron Cryo-Tomography (ECT) allows 3D visualization of subcellular structures at the submolecular resolution in close to the native state. However, due to the high degree of structural complexity and imaging limits, the automatic segmentation of cellular components from ECT images is very difficult. To complement and speed up existing segmentation methods, it is desirable to develop a generic cell component segmentation method that is 1) not specific to particular types of cellular components, 2) able to segment unknown cellular components, 3) fully unsupervised and does not rely on the availability of training data. As an important step towards this goal, in this paper, we propose a saliency detection method that computes the likelihood that a subregion in a tomogram stands out from the background. Our method consists of four steps: supervoxel over-segmentation, feature extraction, feature matrix decomposition, and computation of saliency. The method produces a distribution map that represents the regions’ saliency in tomograms. Our experiments show that our method can successfully label most salient regions detected by a human observer, and able to filter out regions not containing cellular components. Therefore, our method can remove the majority of the background region, and significantly speed up the subsequent processing of segmentation and recognition of cellular components captured by ECT.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Electron Cryo-Tomography (ECT) allows 3D visualization of subcellular structures at the submolecular resolution in close to the native state. However, due to the high degree of structural complexity and imaging limits, the automatic segmentation of cellular components from ECT images is very difficult. To complement and speed up existing segmentation methods, it is desirable to develop a generic cell component segmentation method that is 1) not specific to particular types of cellular components, 2) able to segment unknown cellular components, 3) fully unsupervised and does not rely on the availability of training data. As an important step towards this goal, in this paper, we propose a saliency detection method that computes the likelihood that a subregion in a tomogram stands out from the background. Our method consists of four steps: supervoxel over-segmentation, feature extraction, feature matrix decomposition, and computation of saliency. The method produces a distribution map that represents the regions’ saliency in tomograms. Our experiments show that our method can successfully label most salient regions detected by a human observer, and able to filter out regions not containing cellular components. Therefore, our method can remove the majority of the background region, and significantly speed up the subsequent processing of segmentation and recognition of cellular components captured by ECT.",
"fno": "08621363",
"keywords": [
"Saliency Detection",
"Electron Cryo Tomography",
"Super Voxel Segmentation",
"3 D Gabor Filter",
"Robust PCA"
],
"authors": [
{
"affiliation": "School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA",
"fullName": "Bo Zhou",
"givenName": "Bo",
"surname": "Zhou",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Biochemistry, Max Planck Institute, Martinsried, Germany",
"fullName": "Qiang Guo",
"givenName": "Qiang",
"surname": "Guo",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA",
"fullName": "Kaiwen Wang",
"givenName": "Kaiwen",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA",
"fullName": "Xiangrui Zeng",
"givenName": "Xiangrui",
"surname": "Zeng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA",
"fullName": "Xin Gao",
"givenName": "Xin",
"surname": "Gao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computer, Electrical and Mathematical Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia",
"fullName": "Min Xu",
"givenName": "Min",
"surname": "Xu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-12-01T00:00:00",
"pubType": "proceedings",
"pages": "2467-2473",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-5488-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08621333",
"articleId": "17D45WrVgeH",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08621137",
"articleId": "17D45VObpNS",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icme/2017/6067/0/08019413",
"title": "Segmentation guided local proposal fusion for co-saliency detection",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2017/08019413/12OmNqFJhSz",
"parentPublication": {
"id": "proceedings/icme/2017/6067/0",
"title": "2017 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209c305",
"title": "Implicit Rank-Sparsity Decomposition: Applications to Saliency/Co-saliency Detection",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209c305/12OmNrNh0AT",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2007/1179/0/04269998",
"title": "Image Matching via Saliency Region Correspondences",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2007/04269998/12OmNwNOaSS",
"parentPublication": {
"id": "proceedings/cvpr/2007/1179/0",
"title": "2007 IEEE Conference on Computer Vision and Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2012/2216/0/06460408",
"title": "Corner-surround Contrast for saliency detection",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460408/12OmNyOHG2r",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2015/7082/0/07177414",
"title": "Saliency and co-saliency detection by low-rank multiscale fusion",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2015/07177414/12OmNzC5T1t",
"parentPublication": {
"id": "proceedings/icme/2015/7082/0",
"title": "2015 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2021/3734/0/373400a107",
"title": "Comprehensive Saliency Fusion for Object Co-segmentation",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2021/373400a107/1A3j3vR5W2k",
"parentPublication": {
"id": "proceedings/ism/2021/3734/0",
"title": "2021 IEEE International Symposium on Multimedia (ISM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669370",
"title": "TomoSim: Simulation of Filamentous Cryo-Electron Tomograms",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669370/1A9VM8k3cWs",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2019/4284/0/428400a244",
"title": "RGBD Saliency Object Detection via Regional Feature Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2019/428400a244/1hQqKVqUOwU",
"parentPublication": {
"id": "proceedings/icicta/2019/4284/0",
"title": "2019 12th International Conference on Intelligent Computation Technology and Automation (ICICTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300h222",
"title": "Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300h222/1hVlnMJ8S9G",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2019/1867/0/08982954",
"title": "Regularized Adversarial Training (RAT) for Robust Cellular Electron Cryo Tomograms Classification",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2019/08982954/1hgukgM2cRa",
"parentPublication": {
"id": "proceedings/bibm/2019/1867/0",
"title": "2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1A9VchbY4Mw",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "1001586",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1A9VqrWnZPG",
"doi": "10.1109/BIBM52615.2021.9669318",
"title": "Tracing Filaments in Simulated 3D Cryo-Electron Tomography Maps Using a Fast Dynamic Programming Algorithm",
"normalizedTitle": "Tracing Filaments in Simulated 3D Cryo-Electron Tomography Maps Using a Fast Dynamic Programming Algorithm",
"abstract": "We propose a fast, dynamic programming-based framework for tracing actin filaments in 3D maps of subcellular components in cryo-electron tomography. The approach can identify high-density filament segments in various orientations, but it takes advantage of the arrangement of actin filaments within cells into more or less tightly aligned bundles. Assuming that the tomogram can be rotated such that the filaments can be oriented to be directed in a dominant direction (i.e., the X, Y, or Z axis), the proposed framework first identifies local seed points that form the origin of candidate filament segments (CFSs), which are then grown from the seeds using a fast dynamic programming algorithm. The CFS length l can be tuned to the nominal resolution of the tomogram or the separation of desired features, or it can be used to restrict the curvature of filaments that deviate from the overall bundle direction. In subsequent steps, the CFSs are filtered based on backward tracing and path density analysis. Finally, neighboring CFSs are fused based on a collinearity criterion to bridge any noise artifacts in the 3D map that would otherwise fractionalize the tracing. We validate our proposed framework on simulated tomograms that closely mimic the features and appearance of experimental maps.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose a fast, dynamic programming-based framework for tracing actin filaments in 3D maps of subcellular components in cryo-electron tomography. The approach can identify high-density filament segments in various orientations, but it takes advantage of the arrangement of actin filaments within cells into more or less tightly aligned bundles. Assuming that the tomogram can be rotated such that the filaments can be oriented to be directed in a dominant direction (i.e., the X, Y, or Z axis), the proposed framework first identifies local seed points that form the origin of candidate filament segments (CFSs), which are then grown from the seeds using a fast dynamic programming algorithm. The CFS length l can be tuned to the nominal resolution of the tomogram or the separation of desired features, or it can be used to restrict the curvature of filaments that deviate from the overall bundle direction. In subsequent steps, the CFSs are filtered based on backward tracing and path density analysis. Finally, neighboring CFSs are fused based on a collinearity criterion to bridge any noise artifacts in the 3D map that would otherwise fractionalize the tracing. We validate our proposed framework on simulated tomograms that closely mimic the features and appearance of experimental maps.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose a fast, dynamic programming-based framework for tracing actin filaments in 3D maps of subcellular components in cryo-electron tomography. The approach can identify high-density filament segments in various orientations, but it takes advantage of the arrangement of actin filaments within cells into more or less tightly aligned bundles. Assuming that the tomogram can be rotated such that the filaments can be oriented to be directed in a dominant direction (i.e., the X, Y, or Z axis), the proposed framework first identifies local seed points that form the origin of candidate filament segments (CFSs), which are then grown from the seeds using a fast dynamic programming algorithm. The CFS length l can be tuned to the nominal resolution of the tomogram or the separation of desired features, or it can be used to restrict the curvature of filaments that deviate from the overall bundle direction. In subsequent steps, the CFSs are filtered based on backward tracing and path density analysis. Finally, neighboring CFSs are fused based on a collinearity criterion to bridge any noise artifacts in the 3D map that would otherwise fractionalize the tracing. We validate our proposed framework on simulated tomograms that closely mimic the features and appearance of experimental maps.",
"fno": "09669318",
"keywords": [
"Biological Techniques",
"Cellular Biophysics",
"Computerised Tomography",
"Dynamic Programming",
"Electron Microscopy",
"Image Reconstruction",
"Image Segmentation",
"Medical Image Processing",
"Proteins",
"Experimental Maps",
"Fast Dynamic Programming Algorithm",
"Subcellular Components",
"High Density Filament Segments",
"Tightly Aligned Bundles",
"Dominant Direction",
"Local Seed Points",
"Candidate Filament Segments",
"CFS",
"Bundle Direction",
"Backward Tracing",
"Simulated Tomograms",
"Simulated 3 D Cryo Electron Tomography Maps",
"Actin Filament Tracing",
"Collinearity Criterion",
"Noise Artifacts",
"Bridges",
"Three Dimensional Displays",
"Heuristic Algorithms",
"Conferences",
"Tomography",
"Filtering Algorithms",
"Dynamic Programming"
],
"authors": [
{
"affiliation": "Old Dominion University,Department of Computer Science,Norfolk,VA,23529",
"fullName": "Salim Sazzed",
"givenName": "Salim",
"surname": "Sazzed",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Old Dominion University,Department of Computer Science,Norfolk,VA,23529",
"fullName": "Peter Scheible",
"givenName": "Peter",
"surname": "Scheible",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Old Dominion University,Department of Computer Science,Norfolk,VA,23529",
"fullName": "Jing He",
"givenName": "Jing",
"surname": "He",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Old Dominion University,Department of Mechanical and Aerospace Engineering,Norfolk,VA,23529",
"fullName": "Willy Wriggers",
"givenName": "Willy",
"surname": "Wriggers",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-12-01T00:00:00",
"pubType": "proceedings",
"pages": "2553-2559",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-0126-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09669538",
"articleId": "1A9VG7FhOp2",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09669370",
"articleId": "1A9VM8k3cWs",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibe/2015/7983/0/07367674",
"title": "Coupling finite element and huxley models in multiscale muscle modeling",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2015/07367674/12OmNB1NVPV",
"parentPublication": {
"id": "proceedings/bibe/2015/7983/0",
"title": "2015 IEEE 15th International Conference on Bioinformatics and Bioengineering (BIBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cisw/2007/3073/0/30730910",
"title": "The Research of Broken Filaments Detection Device on Viscose Filament Yarn",
"doi": null,
"abstractUrl": "/proceedings-article/cisw/2007/30730910/12OmNC3FG8T",
"parentPublication": {
"id": "proceedings/cisw/2007/3073/0",
"title": "Computational Intelligence and Security Workshops, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dicta/2005/2467/0/01587681",
"title": "Image Analysis for Electron Microscopy of Muscle Fibers",
"doi": null,
"abstractUrl": "/proceedings-article/dicta/2005/01587681/12OmNzvz6Lp",
"parentPublication": {
"id": "proceedings/dicta/2005/2467/0",
"title": "Digital Image Computing: Techniques and Applications (DICTA'05)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2015/03/06963495",
"title": "Extraction of Individual Filaments from 2D Confocal Microscopy Images of Flat Cells",
"doi": null,
"abstractUrl": "/journal/tb/2015/03/06963495/13rRUwIF6jt",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2016/06/07150427",
"title": "Felix: A Topology Based Framework for Visual Exploration of Cosmic Filaments",
"doi": null,
"abstractUrl": "/journal/tg/2016/06/07150427/13rRUwbs20Y",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2012/03/06095508",
"title": "Quantitative Analysis of the Self-Assembly Strategies of Intermediate Filaments from Tetrameric Vimentin",
"doi": null,
"abstractUrl": "/journal/tb/2012/03/06095508/13rRUx0xPtQ",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2009/04/ttg2009040670",
"title": "Hardware Accelerated Segmentation of Complex Volumetric Filament Networks",
"doi": null,
"abstractUrl": "/journal/tg/2009/04/ttg2009040670/13rRUxjQyp9",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669370",
"title": "TomoSim: Simulation of Filamentous Cryo-Electron Tomograms",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669370/1A9VM8k3cWs",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09994861",
"title": "Tracing Randomly Oriented Filaments in a Simulated Actin Network Tomogram",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09994861/1JC3cw50n3q",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2022/6495/0/649500a289",
"title": "Perceived Effects of Reflective Translucency in 3D Printing Filaments",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2022/649500a289/1MeoJ3k8ewE",
"parentPublication": {
"id": "proceedings/sitis/2022/6495/0",
"title": "2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1B12DGrwoyQ",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"acronym": "wacv",
"groupId": "1000040",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1B13OFswsow",
"doi": "10.1109/WACV51458.2022.00332",
"title": "Weakly Supervised Learning for Joint Image Denoising and Protein Localization in Cryo-Electron Microscopy",
"normalizedTitle": "Weakly Supervised Learning for Joint Image Denoising and Protein Localization in Cryo-Electron Microscopy",
"abstract": "Deep learning-based object detection methods have shown promising results in various fields ranging from autonomous driving to video surveillance where input images have relatively high signal-to-noise ratios (SNR). On low SNR images such as biological electron microscopy (EM) data, however, the performance of these algorithms is significantly lower. Moreover, biological data typically lacks standardized annotations further complicating the training of detection algorithms. Accurate identification of proteins from EM images is a critical task, as the detected positions serve as inputs for the downstream 3D structure determination process. To overcome the low SNR and lack of image annotations, we propose a joint weakly-supervised learning framework that performs image denoising while detecting objects of interest. By leveraging per-pixel soft segmentation and consistency regularization, our framework denoises images without the need of clean images and is able to detect particles of interest even when less than 0.5% of the data are labeled. We validate our approach on real single-particle cryo-EM and cryo-electron tomography (ET) images which are known to suffer from extremely low SNR, and show that our strategy outperforms existing stateof-the-art (SofA) methods used in the cryo-EM field by a significant margin. We also evaluate the performance of our algorithm under decreasing SNR conditions and show that our method is more robust to noise than competing methods.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Deep learning-based object detection methods have shown promising results in various fields ranging from autonomous driving to video surveillance where input images have relatively high signal-to-noise ratios (SNR). On low SNR images such as biological electron microscopy (EM) data, however, the performance of these algorithms is significantly lower. Moreover, biological data typically lacks standardized annotations further complicating the training of detection algorithms. Accurate identification of proteins from EM images is a critical task, as the detected positions serve as inputs for the downstream 3D structure determination process. To overcome the low SNR and lack of image annotations, we propose a joint weakly-supervised learning framework that performs image denoising while detecting objects of interest. By leveraging per-pixel soft segmentation and consistency regularization, our framework denoises images without the need of clean images and is able to detect particles of interest even when less than 0.5% of the data are labeled. We validate our approach on real single-particle cryo-EM and cryo-electron tomography (ET) images which are known to suffer from extremely low SNR, and show that our strategy outperforms existing stateof-the-art (SofA) methods used in the cryo-EM field by a significant margin. We also evaluate the performance of our algorithm under decreasing SNR conditions and show that our method is more robust to noise than competing methods.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Deep learning-based object detection methods have shown promising results in various fields ranging from autonomous driving to video surveillance where input images have relatively high signal-to-noise ratios (SNR). On low SNR images such as biological electron microscopy (EM) data, however, the performance of these algorithms is significantly lower. Moreover, biological data typically lacks standardized annotations further complicating the training of detection algorithms. Accurate identification of proteins from EM images is a critical task, as the detected positions serve as inputs for the downstream 3D structure determination process. To overcome the low SNR and lack of image annotations, we propose a joint weakly-supervised learning framework that performs image denoising while detecting objects of interest. By leveraging per-pixel soft segmentation and consistency regularization, our framework denoises images without the need of clean images and is able to detect particles of interest even when less than 0.5% of the data are labeled. We validate our approach on real single-particle cryo-EM and cryo-electron tomography (ET) images which are known to suffer from extremely low SNR, and show that our strategy outperforms existing stateof-the-art (SofA) methods used in the cryo-EM field by a significant margin. We also evaluate the performance of our algorithm under decreasing SNR conditions and show that our method is more robust to noise than competing methods.",
"fno": "091500d260",
"keywords": [
"Biology Computing",
"Electron Microscopy",
"Image Denoising",
"Image Segmentation",
"Molecular Biophysics",
"Object Detection",
"Proteins",
"Supervised Learning",
"Tomography",
"Video Surveillance",
"Joint Image Denoising",
"Protein Localization",
"Cryo Electron Microscopy",
"Deep Learning",
"Detection Methods",
"Autonomous Driving",
"Video Surveillance",
"Signal To Noise Ratios",
"SNR Images",
"Biological Electron Microscopy Data",
"Biological Data",
"Detection Algorithms",
"EM Images",
"Image Annotations",
"Weakly Supervised Learning Framework",
"Single Particle Cryo EM",
"Cryo Electron Tomography Images",
"Cryo EM Field",
"SNR Conditions",
"Proteins",
"Training",
"Image Segmentation",
"Three Dimensional Displays",
"Tomography",
"Video Surveillance",
"Biology",
"Medical Imaging Imaging For Bioinformatics Biological And Cell Microscopy Segmentation",
"Grouping And Shape"
],
"authors": [
{
"affiliation": "Duke University",
"fullName": "Qinwen Huang",
"givenName": "Qinwen",
"surname": "Huang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Duke University",
"fullName": "Ye Zhou",
"givenName": "Ye",
"surname": "Zhou",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Duke University",
"fullName": "Hsuan-Fu Liu",
"givenName": "Hsuan-Fu",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Duke University",
"fullName": "Alberto Bartesaghi",
"givenName": "Alberto",
"surname": "Bartesaghi",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wacv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-01-01T00:00:00",
"pubType": "proceedings",
"pages": "3260-3269",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-0915-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1B13OBl3tks",
"name": "pwacv202209150-09706970s1-mm_091500d260.zip",
"size": "9.43 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pwacv202209150-09706970s1-mm_091500d260.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "091500d250",
"articleId": "1B13qQowkE0",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "091500d270",
"articleId": "1B13g5lsga4",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icip/1998/8821/2/882120706",
"title": "Reconstruction problems in 3D for viral cryo electron microscopy",
"doi": null,
"abstractUrl": "/proceedings-article/icip/1998/882120706/12OmNBpEeWP",
"parentPublication": {
"id": "proceedings/icip/1998/8821/3",
"title": "Image Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2016/1611/0/07822490",
"title": "Deep convolutional neural networks for detecting secondary structures in protein density maps from cryo-electron microscopy",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2016/07822490/12OmNyL0TCI",
"parentPublication": {
"id": "proceedings/bibm/2016/1611/0",
"title": "2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aipr/2021/2471/0/09762098",
"title": "Joint Model for Image Denoising and Detection of Proteins Imaged by Cryo-EM",
"doi": null,
"abstractUrl": "/proceedings-article/aipr/2021/09762098/1CT9aGTDO9i",
"parentPublication": {
"id": "proceedings/aipr/2021/2471/0",
"title": "2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2022/6124/0/612400a417",
"title": "Representing Steerable Bases for cryo-EM in ASPIRE",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2022/612400a417/1J6hty1xTDG",
"parentPublication": {
"id": "proceedings/e-science/2022/6124/0",
"title": "2022 IEEE 18th International Conference on e-Science (e-Science)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09994879",
"title": "DeepTracer-Denoising: Deep Learning for 3D Electron Density Map Denoising",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09994879/1JC247wbYSQ",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995208",
"title": "Unsupervised Heterogeneous Cryo-EM Projection Image Classification Using Autoencoder",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995208/1JC2JjfzgJy",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2020/9360/0/09150810",
"title": "Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2020/09150810/1lPHcyiKALu",
"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/bibm/2020/6215/0/09313180",
"title": "An Unsupervised Iterative Model for Single-Particle Cryo-EM Image Denoising Based on Siamese Neural Network",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313180/1qmfINMKxTW",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313185",
"title": "Efficient Cryo-Electron Tomogram Simulation of Macromolecular Crowding with Application to SARS-CoV-2",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313185/1qmfUw4iPgA",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/1.91E53",
"title": "CryoPoseNet: End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/1.91E53/1yNiiRwCikM",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1BmEezmpGrm",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"acronym": "iccv",
"groupId": "1000149",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1BmL53XVH0c",
"doi": "10.1109/ICCV48922.2021.00402",
"title": "Self-Supervised Cryo-Electron Tomography Volumetric Image Restoration from Single Noisy Volume with Sparsity Constraint",
"normalizedTitle": "Self-Supervised Cryo-Electron Tomography Volumetric Image Restoration from Single Noisy Volume with Sparsity Constraint",
"abstract": "Cryo-Electron Tomography (cryo-ET) is a powerful tool for 3D cellular visualization. Due to instrumental limitations, cryo-ET images and their volumetric reconstruction suffer from extremely low signal-to-noise ratio. In this paper, we propose a novel end-to-end self-supervised learning model, the Sparsity Constrained Network (SC-Net), to restore volumetric image from single noisy data in cryo-ET. The proposed method only requires a single noisy data as training input and no ground-truth is needed in the whole training procedure. A new target function is proposed to preserve both local smoothness and detailed structure. Additionally, a novel procedure for the simulation of electron tomographic photographing is designed to help the evaluation of methods. Experiments are done on three simulated data and four real-world data. The results show that our method could produce a strong enhancement for a single very noisy cryo-ET volumetric data, which is much better than the state-of-the-art Noise2Void, and with a competitive performance comparing with Noise2Noise. Code is available at https://github.com/icthrm/SC-Net.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Cryo-Electron Tomography (cryo-ET) is a powerful tool for 3D cellular visualization. Due to instrumental limitations, cryo-ET images and their volumetric reconstruction suffer from extremely low signal-to-noise ratio. In this paper, we propose a novel end-to-end self-supervised learning model, the Sparsity Constrained Network (SC-Net), to restore volumetric image from single noisy data in cryo-ET. The proposed method only requires a single noisy data as training input and no ground-truth is needed in the whole training procedure. A new target function is proposed to preserve both local smoothness and detailed structure. Additionally, a novel procedure for the simulation of electron tomographic photographing is designed to help the evaluation of methods. Experiments are done on three simulated data and four real-world data. The results show that our method could produce a strong enhancement for a single very noisy cryo-ET volumetric data, which is much better than the state-of-the-art Noise2Void, and with a competitive performance comparing with Noise2Noise. Code is available at https://github.com/icthrm/SC-Net.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Cryo-Electron Tomography (cryo-ET) is a powerful tool for 3D cellular visualization. Due to instrumental limitations, cryo-ET images and their volumetric reconstruction suffer from extremely low signal-to-noise ratio. In this paper, we propose a novel end-to-end self-supervised learning model, the Sparsity Constrained Network (SC-Net), to restore volumetric image from single noisy data in cryo-ET. The proposed method only requires a single noisy data as training input and no ground-truth is needed in the whole training procedure. A new target function is proposed to preserve both local smoothness and detailed structure. Additionally, a novel procedure for the simulation of electron tomographic photographing is designed to help the evaluation of methods. Experiments are done on three simulated data and four real-world data. The results show that our method could produce a strong enhancement for a single very noisy cryo-ET volumetric data, which is much better than the state-of-the-art Noise2Void, and with a competitive performance comparing with Noise2Noise. Code is available at https://github.com/icthrm/SC-Net.",
"fno": "2.812E41",
"keywords": [
"Training",
"Three Dimensional Displays",
"Instruments",
"Noise Reduction",
"Data Visualization",
"Tomography",
"Image Restoration",
"Medical",
"Biological",
"And Cell Microscopy",
"Computational Photography",
"Low Level And Physics Based Vision",
"Optimization And Learning Methods",
"Transfer Low Shot Semi Unsupervised Learning",
"Vision Applications And Systems"
],
"authors": [
{
"affiliation": "ICT, CAS,High Performance Computer Research Center",
"fullName": "Zhidong Yang",
"givenName": "Zhidong",
"surname": "Yang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "ICT, CAS,High Performance Computer Research Center",
"fullName": "Fa Zhang",
"givenName": "Fa",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Shandong University,Research Center for Mathematics and Interdisciplinary Sciences",
"fullName": "Renmin Han",
"givenName": "Renmin",
"surname": "Han",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-10-01T00:00:00",
"pubType": "proceedings",
"pages": "4036-4045",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-2812-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "2.812E31",
"articleId": "1BmG9N1h9de",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "2.812E51",
"articleId": "1BmHvSDILUA",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icpads/2009/3900/0/3900a384",
"title": "Modified Simultaneous Algebraic Reconstruction Technique and its Parallelization in Cryo-electron Tomography",
"doi": null,
"abstractUrl": "/proceedings-article/icpads/2009/3900a384/12OmNyS6RAw",
"parentPublication": {
"id": "proceedings/icpads/2009/3900/0",
"title": "Parallel and Distributed Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669370",
"title": "TomoSim: Simulation of Filamentous Cryo-Electron Tomograms",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669370/1A9VM8k3cWs",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/091500d260",
"title": "Weakly Supervised Learning for Joint Image Denoising and Protein Localization in Cryo-Electron Microscopy",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500d260/1B13OFswsow",
"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/aipr/2021/2471/0/09762209",
"title": "Practical Analysis of Macromolecule Identity from Cryo-electron Tomography Images using Deep Learning",
"doi": null,
"abstractUrl": "/proceedings-article/aipr/2021/09762209/1CT9aP80A1i",
"parentPublication": {
"id": "proceedings/aipr/2021/2471/0",
"title": "2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09806341",
"title": "Finding Nano-Ötzi: Cryo-Electron Tomography Visualization Guided by Learned Segmentation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09806341/1Et0iwB480M",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09994879",
"title": "DeepTracer-Denoising: Deep Learning for 3D Electron Density Map Denoising",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09994879/1JC247wbYSQ",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2020/9360/0/09150810",
"title": "Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2020/09150810/1lPHcyiKALu",
"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/bibm/2020/6215/0/09313185",
"title": "Efficient Cryo-Electron Tomogram Simulation of Macromolecular Crowding with Application to SARS-CoV-2",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313185/1qmfUw4iPgA",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/01/09380401",
"title": "Macromolecules Structural Classification With a 3D Dilated Dense Network in Cryo-Electron Tomography",
"doi": null,
"abstractUrl": "/journal/tb/2022/01/09380401/1s2FZRmSST6",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/1.91E53",
"title": "CryoPoseNet: End-to-End Simultaneous Learning of Single-particle Orientation and 3D Map Reconstruction from Cryo-electron Microscopy Data",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/1.91E53/1yNiiRwCikM",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1CT95OLD2nK",
"title": "2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)",
"acronym": "aipr",
"groupId": "1000046",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1CT9aP80A1i",
"doi": "10.1109/AIPR52630.2021.9762209",
"title": "Practical Analysis of Macromolecule Identity from Cryo-electron Tomography Images using Deep Learning",
"normalizedTitle": "Practical Analysis of Macromolecule Identity from Cryo-electron Tomography Images using Deep Learning",
"abstract": "Cellular electron cryo-tomography (cryo-ET) has made possible the systematic 3D visualization of the near-native structures and spatial-organizations of large macromolecules (represented as subtomograms) and their interactions with or-ganelles inside single cells. It has emerged as a major tool for in situ structural biology. However, the systematic identification of such macromolecules from cryo-ET images is very difficult due to structural complexity and imaging limits. In particular, conventional methods are too slow to process millions of highly structurally heterogeneous macromolecules fastly imaged using cryo-ET. Since 2017, supervised deep learning has become an important tool for facilitating high-throughput analysis of cryo-ET data. However, supervised learning based approaches depends on manual data annotation by biologists, which is an extremely time-consuming and burdensome process. Therefore, none of these methods are practical to use. In order to facilitate deep learning for practical identification of macromolecules from cryo-ET images, in this paper, we demonstrate the pathway towards unsupervised learning for fast and high-throughput identification of macromolecules from cryo-ET images. To this end, we demonstrate the use of three selected recent macromolecule identification methods on several commonly used benchmark crvo-E'T datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Cellular electron cryo-tomography (cryo-ET) has made possible the systematic 3D visualization of the near-native structures and spatial-organizations of large macromolecules (represented as subtomograms) and their interactions with or-ganelles inside single cells. It has emerged as a major tool for in situ structural biology. However, the systematic identification of such macromolecules from cryo-ET images is very difficult due to structural complexity and imaging limits. In particular, conventional methods are too slow to process millions of highly structurally heterogeneous macromolecules fastly imaged using cryo-ET. Since 2017, supervised deep learning has become an important tool for facilitating high-throughput analysis of cryo-ET data. However, supervised learning based approaches depends on manual data annotation by biologists, which is an extremely time-consuming and burdensome process. Therefore, none of these methods are practical to use. In order to facilitate deep learning for practical identification of macromolecules from cryo-ET images, in this paper, we demonstrate the pathway towards unsupervised learning for fast and high-throughput identification of macromolecules from cryo-ET images. To this end, we demonstrate the use of three selected recent macromolecule identification methods on several commonly used benchmark crvo-E'T datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Cellular electron cryo-tomography (cryo-ET) has made possible the systematic 3D visualization of the near-native structures and spatial-organizations of large macromolecules (represented as subtomograms) and their interactions with or-ganelles inside single cells. It has emerged as a major tool for in situ structural biology. However, the systematic identification of such macromolecules from cryo-ET images is very difficult due to structural complexity and imaging limits. In particular, conventional methods are too slow to process millions of highly structurally heterogeneous macromolecules fastly imaged using cryo-ET. Since 2017, supervised deep learning has become an important tool for facilitating high-throughput analysis of cryo-ET data. However, supervised learning based approaches depends on manual data annotation by biologists, which is an extremely time-consuming and burdensome process. Therefore, none of these methods are practical to use. In order to facilitate deep learning for practical identification of macromolecules from cryo-ET images, in this paper, we demonstrate the pathway towards unsupervised learning for fast and high-throughput identification of macromolecules from cryo-ET images. To this end, we demonstrate the use of three selected recent macromolecule identification methods on several commonly used benchmark crvo-E'T datasets.",
"fno": "09762209",
"keywords": [
"Cellular Biophysics",
"Computerised Tomography",
"Deep Learning Artificial Intelligence",
"Electron Microscopy",
"Image Classification",
"Image Reconstruction",
"Macromolecules",
"Supervised Learning",
"Unsupervised Learning",
"Cryo Electron Tomography Images",
"Cellular Electron Cryo Tomography",
"Systematic 3 D Visualization",
"Near Native Structures",
"In Situ Structural Biology",
"Systematic Identification",
"Cryo ET Images",
"Structural Complexity",
"Supervised Deep Learning",
"Cryo ET Data",
"Practical Identification",
"Unsupervised Learning",
"Macromolecule Identification Methods",
"Structurally Heterogeneous Macromolecules",
"Manual Data Annotation",
"Deep Learning",
"Three Dimensional Displays",
"Systematics",
"Annotations",
"Supervised Learning",
"Tomography",
"Benchmark Testing",
"Bioimage Informatics",
"Image Classification",
"Cryo Electron Tomography",
"Unsupervised Learning"
],
"authors": [
{
"affiliation": "Carnegie Mellon University,Computational Biology Department,Pittsburgh,PA,USA",
"fullName": "Mostofa Rafid Uddin",
"givenName": "Mostofa Rafid",
"surname": "Uddin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Bangladesh University of Engineering & Technology,Dept. of Computer Science and Engineering,Dhaka,Bangladesh",
"fullName": "Ajmain Yasar Ahmed",
"givenName": "Ajmain Yasar",
"surname": "Ahmed",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Independent Researcher,Dhaka,Bangladesh",
"fullName": "Kafi Khan",
"givenName": "Kafi",
"surname": "Khan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Bangladesh University of Engineering & Technology,Dept. of Computer Science and Engineering,Dhaka,Bangladesh",
"fullName": "Md Shahrar Fatemi",
"givenName": "Md Shahrar",
"surname": "Fatemi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University,Computational Biology Department,Pittsburgh,PA,USA",
"fullName": "Xiangrui Zeng",
"givenName": "Xiangrui",
"surname": "Zeng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University,Computational Biology Department,Pittsburgh,PA,USA",
"fullName": "Min Xu",
"givenName": "Min",
"surname": "Xu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "aipr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-10-01T00:00:00",
"pubType": "proceedings",
"pages": "1-9",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-2471-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09762222",
"articleId": "1CT9aevbBra",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09762171",
"articleId": "1CT99I07d3a",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2016/1611/0/07822490",
"title": "Deep convolutional neural networks for detecting secondary structures in protein density maps from cryo-electron microscopy",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2016/07822490/12OmNyL0TCI",
"parentPublication": {
"id": "proceedings/bibm/2016/1611/0",
"title": "2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpads/2009/3900/0/3900a384",
"title": "Modified Simultaneous Algebraic Reconstruction Technique and its Parallelization in Cryo-electron Tomography",
"doi": null,
"abstractUrl": "/proceedings-article/icpads/2009/3900a384/12OmNyS6RAw",
"parentPublication": {
"id": "proceedings/icpads/2009/3900/0",
"title": "Parallel and Distributed Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669370",
"title": "TomoSim: Simulation of Filamentous Cryo-Electron Tomograms",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669370/1A9VM8k3cWs",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669318",
"title": "Tracing Filaments in Simulated 3D Cryo-Electron Tomography Maps Using a Fast Dynamic Programming Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669318/1A9VqrWnZPG",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/091500d260",
"title": "Weakly Supervised Learning for Joint Image Denoising and Protein Localization in Cryo-Electron Microscopy",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500d260/1B13OFswsow",
"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/iccv/2021/2812/0/2.812E41",
"title": "Self-Supervised Cryo-Electron Tomography Volumetric Image Restoration from Single Noisy Volume with Sparsity Constraint",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/2.812E41/1BmL53XVH0c",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09806341",
"title": "Finding Nano-Ötzi: Cryo-Electron Tomography Visualization Guided by Learned Segmentation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09806341/1Et0iwB480M",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995208",
"title": "Unsupervised Heterogeneous Cryo-EM Projection Image Classification Using Autoencoder",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995208/1JC2JjfzgJy",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313185",
"title": "Efficient Cryo-Electron Tomogram Simulation of Macromolecular Crowding with Application to SARS-CoV-2",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313185/1qmfUw4iPgA",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2022/01/09380401",
"title": "Macromolecules Structural Classification With a 3D Dilated Dense Network in Cryo-Electron Tomography",
"doi": null,
"abstractUrl": "/journal/tb/2022/01/09380401/1s2FZRmSST6",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1JC1F8KcINO",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "9994793",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1JC247wbYSQ",
"doi": "10.1109/BIBM55620.2022.9994879",
"title": "DeepTracer-Denoising: Deep Learning for 3D Electron Density Map Denoising",
"normalizedTitle": "DeepTracer-Denoising: Deep Learning for 3D Electron Density Map Denoising",
"abstract": "Cryo-electron microscopy (Cryo-EM) is widely used in molecular structure determination and drug discovery. Experimental cryo-EM images suffer from the noises introduced by electron beam dose and sample preparation. Although many approaches have been proposed to improve the signal-to-noise ratio (SNR) for cryo-EM image denoising, the noises are still presented after 3D reconstruction and can obstruct the analysis and visualization of the 3D density map. Here we present DeepTracer-Denoising, a method for 3D electron density map denoising. We employ a 3D Neural Network to learn the pattern of noises and the biological structure from density maps. Our method is designed to work on medium to high-resolution maps ranging from 2.5 A to 10.0A. It is configurated with two modes to tackle both background noise and structural noise in a 3D density map. Our method can correctly identify 97.70% background noise while preserving 96.46% density of the native structure. For the maps that contain structural noise, DeepTracer-Denoising achieves an overall accuracy of 98.95%.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Cryo-electron microscopy (Cryo-EM) is widely used in molecular structure determination and drug discovery. Experimental cryo-EM images suffer from the noises introduced by electron beam dose and sample preparation. Although many approaches have been proposed to improve the signal-to-noise ratio (SNR) for cryo-EM image denoising, the noises are still presented after 3D reconstruction and can obstruct the analysis and visualization of the 3D density map. Here we present DeepTracer-Denoising, a method for 3D electron density map denoising. We employ a 3D Neural Network to learn the pattern of noises and the biological structure from density maps. Our method is designed to work on medium to high-resolution maps ranging from 2.5 A to 10.0A. It is configurated with two modes to tackle both background noise and structural noise in a 3D density map. Our method can correctly identify 97.70% background noise while preserving 96.46% density of the native structure. For the maps that contain structural noise, DeepTracer-Denoising achieves an overall accuracy of 98.95%.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Cryo-electron microscopy (Cryo-EM) is widely used in molecular structure determination and drug discovery. Experimental cryo-EM images suffer from the noises introduced by electron beam dose and sample preparation. Although many approaches have been proposed to improve the signal-to-noise ratio (SNR) for cryo-EM image denoising, the noises are still presented after 3D reconstruction and can obstruct the analysis and visualization of the 3D density map. Here we present DeepTracer-Denoising, a method for 3D electron density map denoising. We employ a 3D Neural Network to learn the pattern of noises and the biological structure from density maps. Our method is designed to work on medium to high-resolution maps ranging from 2.5 A to 10.0A. It is configurated with two modes to tackle both background noise and structural noise in a 3D density map. Our method can correctly identify 97.70% background noise while preserving 96.46% density of the native structure. For the maps that contain structural noise, DeepTracer-Denoising achieves an overall accuracy of 98.95%.",
"fno": "09994879",
"keywords": [
"Deep Learning Artificial Intelligence",
"Drugs",
"Electron Microscopy",
"Image Denoising",
"Image Reconstruction",
"Macromolecules",
"Medical Image Processing",
"Molecular Biophysics",
"Molecular Configurations",
"3 D Density Map",
"3 D Electron Density Map Denoising",
"3 D Neural Network",
"3 D Reconstruction",
"Cryo Electron Microscopy",
"Cryo EM Image Denoising",
"Deep Learning",
"Deep Tracer Denoising",
"Density Maps",
"Drug Discovery",
"Electron Beam Dose",
"High Resolution Maps",
"Molecular Structure Determination",
"Signal To Noise Ratio",
"Structural Noise",
"Training",
"Visualization",
"Three Dimensional Displays",
"Noise Reduction",
"Distance Measurement",
"Background Noise",
"Convolutional Neural Networks",
"Cryo EM",
"3 D Electron Density Map",
"Deep Learning",
"3 D CN Ns",
"Denoising"
],
"authors": [
{
"affiliation": "New York University,Center of Data Science,New York City,US",
"fullName": "Haowen Guan",
"givenName": "Haowen",
"surname": "Guan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Washington Bothell,Division of Computing and Software Systems,Bothell,US",
"fullName": "Dong Si",
"givenName": "Dong",
"surname": "Si",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-12-01T00:00:00",
"pubType": "proceedings",
"pages": "2080-2087",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6819-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09995097",
"articleId": "1JC1KdEaltm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09994949",
"articleId": "1JC2CorUU6Y",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdmw/2016/5910/0/07836672",
"title": "Medical Image Denoising Using Convolutional Denoising Autoencoders",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2016/07836672/12OmNxd4tmw",
"parentPublication": {
"id": "proceedings/icdmw/2016/5910/0",
"title": "2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2007/1016/0/04285054",
"title": "Maximum a Posteriori Based (MAP-Based) Video Denoising VIA Rate Distortion Optimization",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2007/04285054/12OmNyQ7FDN",
"parentPublication": {
"id": "proceedings/icme/2007/1016/0",
"title": "2007 International Conference on Multimedia & Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/091500d260",
"title": "Weakly Supervised Learning for Joint Image Denoising and Protein Localization in Cryo-Electron Microscopy",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500d260/1B13OFswsow",
"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/iccv/2021/2812/0/281200b739",
"title": "Unsupervised Deep Video Denoising",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200b739/1BmG28ha6je",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/2.812E41",
"title": "Self-Supervised Cryo-Electron Tomography Volumetric Image Restoration from Single Noisy Volume with Sparsity Constraint",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/2.812E41/1BmL53XVH0c",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300d943",
"title": "A Simple and Robust Deep Convolutional Approach to Blind Image Denoising",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300d943/1i5mJoM5jYk",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300d804",
"title": "Removing Imaging Artifacts in Electron Microscopy using an Asymmetrically Cyclic Adversarial Network without Paired Training Data",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300d804/1i5mtTLGsU0",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2020/9274/0/927400a101",
"title": "Image Denoising using Attention-Residual Convolutional Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2020/927400a101/1p2VAdnEvLi",
"parentPublication": {
"id": "proceedings/sibgrapi/2020/9274/0",
"title": "2020 33rd SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313180",
"title": "An Unsupervised Iterative Model for Single-Particle Cryo-EM Image Denoising Based on Siamese Neural Network",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313180/1qmfINMKxTW",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicas/2020/9085/0/908500a337",
"title": "On the use of higher-density wavelet packet neighboring coefficient to improve SNR for signal denoising",
"doi": null,
"abstractUrl": "/proceedings-article/icicas/2020/908500a337/1sZ2Y8LbwVq",
"parentPublication": {
"id": "proceedings/icicas/2020/9085/0",
"title": "2020 International Conference on Intelligent Computing, Automation and Systems (ICICAS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1qmfHK8AjMQ",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "1001586",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1qmfINMKxTW",
"doi": "10.1109/BIBM49941.2020.9313180",
"title": "An Unsupervised Iterative Model for Single-Particle Cryo-EM Image Denoising Based on Siamese Neural Network",
"normalizedTitle": "An Unsupervised Iterative Model for Single-Particle Cryo-EM Image Denoising Based on Siamese Neural Network",
"abstract": "Cryo-electron microscopy (cryo-EM) has become an important technology in the field of structural biology. Through the continuous development and improvement of hardware and software, more and more molecular biological structures close to atomic resolution have been resolved. In order to obtain accurate and reliable three-dimensional structure, clustering analysis of cryo-EM images is a very important and critical step.Different from traditional images, cryo-EM images have very high noise, in which the particles have random horizontal position and rotation directions. Most of the existing cryo-EM image processing tools implement traditional clustering methods, which do not perform well in such a highly-noisy scenario. In this paper, combined with the traditional K-means clustering algorithm, a new iterative clustering algorithm based on the unsupervised generative model is proposed. The iterative algorithm is mainly based on the idea of siamese network. First, we use K-means algorithm and Resnet to extract pre-labels for unlabeled data, and then in each subsequent iteration, we use siamese network to continuously extract and update the feature matrix of each image. After each epoch, K-means is adopted to cluster the image data based on the new feature representations. The contrastive loss is used as the loss function. The experimental results show that our method significantly improves the signal-to-noise ratio of images, and has better clustering performance compared with traditional methods.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Cryo-electron microscopy (cryo-EM) has become an important technology in the field of structural biology. Through the continuous development and improvement of hardware and software, more and more molecular biological structures close to atomic resolution have been resolved. In order to obtain accurate and reliable three-dimensional structure, clustering analysis of cryo-EM images is a very important and critical step.Different from traditional images, cryo-EM images have very high noise, in which the particles have random horizontal position and rotation directions. Most of the existing cryo-EM image processing tools implement traditional clustering methods, which do not perform well in such a highly-noisy scenario. In this paper, combined with the traditional K-means clustering algorithm, a new iterative clustering algorithm based on the unsupervised generative model is proposed. The iterative algorithm is mainly based on the idea of siamese network. First, we use K-means algorithm and Resnet to extract pre-labels for unlabeled data, and then in each subsequent iteration, we use siamese network to continuously extract and update the feature matrix of each image. After each epoch, K-means is adopted to cluster the image data based on the new feature representations. The contrastive loss is used as the loss function. The experimental results show that our method significantly improves the signal-to-noise ratio of images, and has better clustering performance compared with traditional methods.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Cryo-electron microscopy (cryo-EM) has become an important technology in the field of structural biology. Through the continuous development and improvement of hardware and software, more and more molecular biological structures close to atomic resolution have been resolved. In order to obtain accurate and reliable three-dimensional structure, clustering analysis of cryo-EM images is a very important and critical step.Different from traditional images, cryo-EM images have very high noise, in which the particles have random horizontal position and rotation directions. Most of the existing cryo-EM image processing tools implement traditional clustering methods, which do not perform well in such a highly-noisy scenario. In this paper, combined with the traditional K-means clustering algorithm, a new iterative clustering algorithm based on the unsupervised generative model is proposed. The iterative algorithm is mainly based on the idea of siamese network. First, we use K-means algorithm and Resnet to extract pre-labels for unlabeled data, and then in each subsequent iteration, we use siamese network to continuously extract and update the feature matrix of each image. After each epoch, K-means is adopted to cluster the image data based on the new feature representations. The contrastive loss is used as the loss function. The experimental results show that our method significantly improves the signal-to-noise ratio of images, and has better clustering performance compared with traditional methods.",
"fno": "09313180",
"keywords": [
"Electron Microscopy",
"Image Classification",
"Image Denoising",
"Image Representation",
"Iterative Methods",
"Medical Image Processing",
"Pattern Clustering",
"Unsupervised Learning",
"Unsupervised Iterative Model",
"Siamese Neural Network",
"Cryo Electron Microscopy",
"Structural Biology",
"Continuous Development",
"Molecular Biological Structures",
"Three Dimensional Structure",
"Random Horizontal Position",
"Rotation Directions",
"Highly Noisy Scenario",
"Iterative Clustering Algorithm",
"Unsupervised Generative Model",
"Image Data",
"Clustering Performance",
"Single Particle Cryo EM Image Denoising",
"Feature Extraction",
"Noise Reduction",
"Software",
"Electron Microscopy",
"Deep Learning",
"Clustering Algorithms",
"Proteins",
"Siamese Network",
"Cryo EM",
"Image Denoising",
"Clustering",
"Unsupervised Learning"
],
"authors": [
{
"affiliation": "Shanghai Jiaotong University,The Department of Bioinformatics and Biostatistics,Shanghai,China,200240",
"fullName": "Wangjie Zheng",
"givenName": "Wangjie",
"surname": "Zheng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Shanghai Jiaotong University,The Department of Computer Science and Engineering,Shanghai,China,200240",
"fullName": "Yang Yang",
"givenName": "Yang",
"surname": "Yang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-12-01T00:00:00",
"pubType": "proceedings",
"pages": "2390-2394",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-6215-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09313577",
"articleId": "1qmg4gW516g",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09313347",
"articleId": "1qmfXeYu12M",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "trans/tb/2007/01/n0028",
"title": "EMatch: Discovery of High Resolution Structural Homologues of Protein Domains in Intermediate Resolution Cryo-EM Maps",
"doi": null,
"abstractUrl": "/journal/tb/2007/01/n0028/13rRUyogGyF",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2018/5488/0/08621474",
"title": "IterVM: An Iterative Model for Single-Particle Cryo-EM Image Clustering Based on Variational Autoencoder and Multi-Reference Alignment",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2018/08621474/17D45Xh13u3",
"parentPublication": {
"id": "proceedings/bibm/2018/5488/0",
"title": "2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669394",
"title": "Heterogeneous Cryo-EM Projection Image Classification Based on Common Lines",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669394/1A9VWNxLUQg",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/2.812E51",
"title": "CryoDRGN2: Ab initio neural reconstruction of 3D protein structures from real cryo-EM images",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/2.812E51/1BmHvSDILUA",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aipr/2021/2471/0/09762098",
"title": "Joint Model for Image Denoising and Detection of Proteins Imaged by Cryo-EM",
"doi": null,
"abstractUrl": "/proceedings-article/aipr/2021/09762098/1CT9aGTDO9i",
"parentPublication": {
"id": "proceedings/aipr/2021/2471/0",
"title": "2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2022/9062/0/09956051",
"title": "NoiseFlow: Learning Optical Flow from Low SNR Cryo-EM Movie",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2022/09956051/1IHpoFKk9Ko",
"parentPublication": {
"id": "proceedings/icpr/2022/9062/0",
"title": "2022 26th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/e-science/2022/6124/0/612400a417",
"title": "Representing Steerable Bases for cryo-EM in ASPIRE",
"doi": null,
"abstractUrl": "/proceedings-article/e-science/2022/612400a417/1J6hty1xTDG",
"parentPublication": {
"id": "proceedings/e-science/2022/6124/0",
"title": "2022 IEEE 18th International Conference on e-Science (e-Science)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995208",
"title": "Unsupervised Heterogeneous Cryo-EM Projection Image Classification Using Autoencoder",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995208/1JC2JjfzgJy",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995469",
"title": "The Combined Focal Cross Entropy and Dice Loss Function for Segmentation of Protein Secondary Structures from Cryo-EM 3D Density maps",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995469/1JC2iCaNNuw",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2020/6215/0/09313189",
"title": "NiuEM: A Nested-iterative Unsupervised Learning Model for Single-particle Cryo-EM Image Processing",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2020/09313189/1qmg67iIQjS",
"parentPublication": {
"id": "proceedings/bibm/2020/6215/0",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1qmfHK8AjMQ",
"title": "2020 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"acronym": "bibm",
"groupId": "1001586",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1qmfUw4iPgA",
"doi": "10.1109/BIBM49941.2020.9313185",
"title": "Efficient Cryo-Electron Tomogram Simulation of Macromolecular Crowding with Application to SARS-CoV-2",
"normalizedTitle": "Efficient Cryo-Electron Tomogram Simulation of Macromolecular Crowding with Application to SARS-CoV-2",
"abstract": "We propose an efficient method for simulating a cryo-Electron Tomography (cryo-ET) image of a target macromolecule with several neighbor macromolecules packed to achieve a realistic crowded cytoplasm content. The simulated results are subtomograms with corresponding noise-free 3D density maps and pre-specified labels (PDB ID, center locations, and orientations) to assist bioimage analysis. They can serve as benchmark datasets for testing developing cryo-ET analysis algorithms and as training datasets with readily available ground truth labels for learning neural network models. The COVID-19 pandemic has sparked a global health crisis that severely impacting lives worldwide. As an important application, we simulated the scene of SARS-CoV-2 interacting with the host cell. The simulated cryo-ET images clearly showed the binding domain of the virus and the host cell to facilitate the research of SARS-CoV-2' infection. We also trained two different classification models to demonstrate that our simulated cryo-ET data is able to assist the cryo-ET analysis task and to validate the performance between different methods.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose an efficient method for simulating a cryo-Electron Tomography (cryo-ET) image of a target macromolecule with several neighbor macromolecules packed to achieve a realistic crowded cytoplasm content. The simulated results are subtomograms with corresponding noise-free 3D density maps and pre-specified labels (PDB ID, center locations, and orientations) to assist bioimage analysis. They can serve as benchmark datasets for testing developing cryo-ET analysis algorithms and as training datasets with readily available ground truth labels for learning neural network models. The COVID-19 pandemic has sparked a global health crisis that severely impacting lives worldwide. As an important application, we simulated the scene of SARS-CoV-2 interacting with the host cell. The simulated cryo-ET images clearly showed the binding domain of the virus and the host cell to facilitate the research of SARS-CoV-2' infection. We also trained two different classification models to demonstrate that our simulated cryo-ET data is able to assist the cryo-ET analysis task and to validate the performance between different methods.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose an efficient method for simulating a cryo-Electron Tomography (cryo-ET) image of a target macromolecule with several neighbor macromolecules packed to achieve a realistic crowded cytoplasm content. The simulated results are subtomograms with corresponding noise-free 3D density maps and pre-specified labels (PDB ID, center locations, and orientations) to assist bioimage analysis. They can serve as benchmark datasets for testing developing cryo-ET analysis algorithms and as training datasets with readily available ground truth labels for learning neural network models. The COVID-19 pandemic has sparked a global health crisis that severely impacting lives worldwide. As an important application, we simulated the scene of SARS-CoV-2 interacting with the host cell. The simulated cryo-ET images clearly showed the binding domain of the virus and the host cell to facilitate the research of SARS-CoV-2' infection. We also trained two different classification models to demonstrate that our simulated cryo-ET data is able to assist the cryo-ET analysis task and to validate the performance between different methods.",
"fno": "09313185",
"keywords": [
"Cellular Biophysics",
"Diseases",
"Electron Microscopy",
"Image Classification",
"Macromolecules",
"Medical Image Processing",
"Microorganisms",
"Molecular Biophysics",
"Neural Nets",
"Macromolecular Crowding",
"Macromolecule",
"Cytoplasm Content",
"Bioimage Analysis",
"COVID 19 Pandemic",
"SARS Co V 2 Infection",
"Cryo ET Analysis Task",
"Cryo ET Image",
"Learning Neural Network Model",
"Noise Free 3 D Density Maps",
"Cryo Electron Tomogram Simulation",
"Cryo Electron Tomography Image",
"Binding Domain",
"Proteins",
"Viruses Medical",
"COVID 19",
"Tomography",
"Three Dimensional Displays",
"Data Models",
"Pandemics",
"Cryo Electron Tomogram",
"Macromolecular Crowding",
"Intercelluar Simulation",
"SARS Co V 2 Simulation"
],
"authors": [
{
"affiliation": "Institute of Artificial Intelligence, University of Science and Technology Beijing,Beijing Advanced Innovation Center for Materials Genome Engineering,Beijing,China",
"fullName": "Sinuo Liu",
"givenName": "Sinuo",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Beihang University,School of Computer Science,Beijing,China",
"fullName": "Yan Ma",
"givenName": "Yan",
"surname": "Ma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Science and Technology Beijing,Beijing Key Laboratory of Knowledge Engineering for Materials Science,Beijing,China",
"fullName": "Xiaojuan Ban",
"givenName": "Xiaojuan",
"surname": "Ban",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University,Computational Biology Department,Pittsburgh,USA",
"fullName": "Xiangrui Zeng",
"givenName": "Xiangrui",
"surname": "Zeng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Birla Institute of Technology and Science,Department of Computer Science and Information Systems,Hyderabad,India",
"fullName": "Vamsi Nallapareddy",
"givenName": "Vamsi",
"surname": "Nallapareddy",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Vishwakarma Institute of Technology,Computer Engineering Department,Pune,India",
"fullName": "Ajinkya Chaudhari",
"givenName": "Ajinkya",
"surname": "Chaudhari",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University,Computational Biology Department,Pittsburgh,USA",
"fullName": "Min Xu",
"givenName": "Min",
"surname": "Xu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": true,
"showRecommendedArticles": true,
"showBuyMe": false,
"hasPdf": true,
"pubDate": "2020-12-01T00:00:00",
"pubType": "proceedings",
"pages": "80-87",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-6215-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09313184",
"articleId": "1qmgdjM2R1u",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09313475",
"articleId": "1qmfVKcutfq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2021/0126/0/09669705",
"title": "Discovering SARS-CoV-2 genes and mutations adapted for humans in 2594 genomes",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669705/1A9VD9EXxE4",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669402",
"title": "RNA Secondary Structure Database, Analysis Tool-Set, and Case-Study Results on SARS-CoV-2",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669402/1A9VO93U4Ug",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669438",
"title": "Allosteric Modulation of Small Molecule Drugs on ACE2 Conformational Change upon Binding to SARS-CoV-2 Spike Protein",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669438/1A9WjUyxH20",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ithings-greencom-cpscom-smartdata-cybermatics/2021/1762/0/176200a365",
"title": "May SARS-CoV-2 be prevented by an indoor air monitoring smart data service?",
"doi": null,
"abstractUrl": "/proceedings-article/ithings-greencom-cpscom-smartdata-cybermatics/2021/176200a365/1AIMCaKI3Sw",
"parentPublication": {
"id": "proceedings/ithings-greencom-cpscom-smartdata-cybermatics/2021/1762/0",
"title": "2021 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdh/2022/8149/0/814900a117",
"title": "Surveillance of SARS-CoV-2 in Urban Wastewater in Italy",
"doi": null,
"abstractUrl": "/proceedings-article/icdh/2022/814900a117/1G6jHz7zHJS",
"parentPublication": {
"id": "proceedings/icdh/2022/8149/0",
"title": "2022 IEEE International Conference on Digital Health (ICDH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2022/6819/0/09995291",
"title": "Evolution Of SARS-CoV-2 In The Presence Of Vaccines",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2022/09995291/1JC21EIBCHC",
"parentPublication": {
"id": "proceedings/bibm/2022/6819/0",
"title": "2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2021/04/09291403",
"title": "High-Throughput Screening and Quantum Mechanics for Identifying Potent Inhibitors Against Mac1 Domain of SARS-CoV-2 Nsp3",
"doi": null,
"abstractUrl": "/journal/tb/2021/04/09291403/1ptq88RlWPm",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isctt/2020/8575/0/857500a624",
"title": "The Role of China Rail Network in SARS-CoV-2 Transmission and Intervention",
"doi": null,
"abstractUrl": "/proceedings-article/isctt/2020/857500a624/1rHeOX0qJNu",
"parentPublication": {
"id": "proceedings/isctt/2020/8575/0",
"title": "2020 5th International Conference on Information Science, Computer Technology and Transportation (ISCTT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icphds/2020/8571/0/857100a001",
"title": "From Evolution to Solution: Battling SARS-CoV-2",
"doi": null,
"abstractUrl": "/proceedings-article/icphds/2020/857100a001/1rxhtjna06c",
"parentPublication": {
"id": "proceedings/icphds/2020/8571/0",
"title": "2020 International Conference on Public Health and Data Science (ICPHDS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2021/0132/0/013200a451",
"title": "SARS-CoV-2 Ribosomal Frameshifting Pseudoknot: Detection of Inter-viral Structural Similarity",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2021/013200a451/1xIORaFrhRK",
"parentPublication": {
"id": "proceedings/ichi/2021/0132/0",
"title": "2021 IEEE 9th International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1H1gVMlkl32",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1H0Kwo5tABi",
"doi": "10.1109/CVPR52688.2022.00177",
"title": "LAKe-Net: Topology-Aware Point Cloud Completion by Localizing Aligned Keypoints",
"normalizedTitle": "LAKe-Net: Topology-Aware Point Cloud Completion by Localizing Aligned Keypoints",
"abstract": "Point cloud completion aims at completing geometric and topological shapes from a partial observation. However, some topology of the original shape is missing, existing methods directly predict the location of complete points, without predicting structured and topological information of the complete shape, which leads to inferior performance. To better tackle the missing topology part, we propose LAKe-Net, a novel topology-aware point cloud completion model by localizing aligned keypoints, with a novel Keypoints-Skeleton-Shape prediction manner. Specifically, our method completes missing topology using three steps: 1) Aligned Keypoint Localization. An asymmetric keypoint locator, including an unsupervised multi-scale keypoint detector and a complete keypoint generator, is proposed for localizing aligned keypoints from complete and partial point clouds. We theoretically prove that the detector can capture aligned keypoints for objects within a sub-category. 2) Surface-skeleton Generation. A new type of skeleton, named Surface-skeleton, is generated from keypoints based on geometric priors to fully represent the topological information captured from keypoints and better recover the local details. 3) Shape Refinement. We design a refinement subnet where multi-scale surface-skeletons are fed into each recursive skeleton-assisted refinement module to assist the completion process. Experimental results show that our method achieves the state-of-the-art performance on point cloud completion.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Point cloud completion aims at completing geometric and topological shapes from a partial observation. However, some topology of the original shape is missing, existing methods directly predict the location of complete points, without predicting structured and topological information of the complete shape, which leads to inferior performance. To better tackle the missing topology part, we propose LAKe-Net, a novel topology-aware point cloud completion model by localizing aligned keypoints, with a novel Keypoints-Skeleton-Shape prediction manner. Specifically, our method completes missing topology using three steps: 1) Aligned Keypoint Localization. An asymmetric keypoint locator, including an unsupervised multi-scale keypoint detector and a complete keypoint generator, is proposed for localizing aligned keypoints from complete and partial point clouds. We theoretically prove that the detector can capture aligned keypoints for objects within a sub-category. 2) Surface-skeleton Generation. A new type of skeleton, named Surface-skeleton, is generated from keypoints based on geometric priors to fully represent the topological information captured from keypoints and better recover the local details. 3) Shape Refinement. We design a refinement subnet where multi-scale surface-skeletons are fed into each recursive skeleton-assisted refinement module to assist the completion process. Experimental results show that our method achieves the state-of-the-art performance on point cloud completion.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Point cloud completion aims at completing geometric and topological shapes from a partial observation. However, some topology of the original shape is missing, existing methods directly predict the location of complete points, without predicting structured and topological information of the complete shape, which leads to inferior performance. To better tackle the missing topology part, we propose LAKe-Net, a novel topology-aware point cloud completion model by localizing aligned keypoints, with a novel Keypoints-Skeleton-Shape prediction manner. Specifically, our method completes missing topology using three steps: 1) Aligned Keypoint Localization. An asymmetric keypoint locator, including an unsupervised multi-scale keypoint detector and a complete keypoint generator, is proposed for localizing aligned keypoints from complete and partial point clouds. We theoretically prove that the detector can capture aligned keypoints for objects within a sub-category. 2) Surface-skeleton Generation. A new type of skeleton, named Surface-skeleton, is generated from keypoints based on geometric priors to fully represent the topological information captured from keypoints and better recover the local details. 3) Shape Refinement. We design a refinement subnet where multi-scale surface-skeletons are fed into each recursive skeleton-assisted refinement module to assist the completion process. Experimental results show that our method achieves the state-of-the-art performance on point cloud completion.",
"fno": "694600b716",
"keywords": [
"Computational Geometry",
"Feature Extraction",
"Image Matching",
"Image Representation",
"Object Detection",
"Object Recognition",
"Solid Modelling",
"Missing Topology Part",
"Novel Topology Aware Point Cloud Completion Model",
"Aligned Keypoints",
"Novel Keypoints Skeleton Shape Prediction Manner",
"Aligned Keypoint Localization",
"Asymmetric Keypoint Locator",
"Multiscale Keypoint Detector",
"Complete Keypoint Generator",
"Complete Point Clouds",
"Partial Point Clouds",
"Surface Skeleton Generation",
"Topological Information",
"Multiscale Surface Skeletons",
"Completion Process",
"Geometric Shapes",
"Topological Shapes",
"Complete Points",
"Complete Shape",
"Point Cloud Compression",
"Location Awareness",
"Three Dimensional Displays",
"Shape",
"Detectors",
"Predictive Models",
"Skeleton"
],
"authors": [
{
"affiliation": "Shanghai Jiao Tong University",
"fullName": "Junshu Tang",
"givenName": "Junshu",
"surname": "Tang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Shanghai Jiao Tong University",
"fullName": "Zhijun Gong",
"givenName": "Zhijun",
"surname": "Gong",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Shanghai Jiao Tong University",
"fullName": "Ran Yi",
"givenName": "Ran",
"surname": "Yi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "East China Normal University",
"fullName": "Yuan Xie",
"givenName": "Yuan",
"surname": "Xie",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Shanghai Jiao Tong University",
"fullName": "Lizhuang Ma",
"givenName": "Lizhuang",
"surname": "Ma",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-06-01T00:00:00",
"pubType": "proceedings",
"pages": "1716-1725",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6946-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1H0KwkNXcl2",
"name": "pcvpr202269460-09879253s1-mm_694600b716.zip",
"size": "4.07 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pcvpr202269460-09879253s1-mm_694600b716.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "694600b705",
"articleId": "1H1mAxBxizm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "694600b726",
"articleId": "1H1ipLazQyc",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/2014/5118/0/5118d582",
"title": "Using k-Poselets for Detecting People and Localizing Their Keypoints",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2014/5118d582/12OmNqyUUKS",
"parentPublication": {
"id": "proceedings/cvpr/2014/5118/0",
"title": "2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200p5984",
"title": "P2-Net: Joint Description and Detection of Local Features for Pixel and Point Matching",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200p5984/1BmKGU5fuOk",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09804851",
"title": "Point Cloud Completion Via Skeleton-Detail Transformer",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09804851/1ErlpBk8JBS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600t9394",
"title": "Few-shot Keypoint Detection with Uncertainty Learning for Unseen Species",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600t9394/1H0MTpARbri",
"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/cvpr/2022/6946/0/694600b172",
"title": "OSKDet: Orientation-sensitive Keypoint Localization for Rotated Object Detection",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600b172/1H1hQvRYcbm",
"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/2023/9346/0/934600b196",
"title": "Centroid Distance Keypoint Detector for Colored Point Clouds",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600b196/1LiO8nAtFok",
"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/iccvw/2019/5023/0/502300b251",
"title": "Falls Prediction Based on Body Keypoints and Seq2Seq Architecture",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300b251/1i5mBIg7vJm",
"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/2021/0477/0/047700d439",
"title": "Conditional Link Prediction of Category-Implicit Keypoint Detection",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700d439/1uqGCNddYu4",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/019100b602",
"title": "Localizing Human Keypoints beyond the Bounding Box",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100b602/1yNhStFbi0w",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900a043",
"title": "Skeleton Merger: an Unsupervised Aligned Keypoint Detector",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900a043/1yeKLLprk4w",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1yeHGyRsuys",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1yeLNkSQJX2",
"doi": "10.1109/CVPR46437.2021.00842",
"title": "Variational Relational Point Completion Network",
"normalizedTitle": "Variational Relational Point Completion Network",
"abstract": "Real-scanned point clouds are often incomplete due to viewpoint, occlusion, and noise. Existing point cloud completion methods tend to generate global shape skeletons and hence lack fine local details. Furthermore, they mostly learn a deterministic partial-to-complete mapping, but overlook structural relations in man-made objects. To tackle these challenges, this paper proposes a variational framework, Variational Relational point Completion network (VRC-Net) with two appealing properties: 1) Probabilistic Modeling. In particular, we propose a dual-path architecture to enable principled probabilistic modeling across partial and complete clouds. One path consumes complete point clouds for reconstruction by learning a point VAE. The other path generates complete shapes for partial point clouds, whose embedded distribution is guided by distribution obtained from the reconstruction path during training. 2) Relational Enhancement. Specifically, we carefully design point self-attention kernel and point selective kernel module to exploit relational point features, which refines local shape de tails conditioned on the coarse completion. In addition, we contribute a multi-view partial point cloud dataset (MVP dataset) containing over 100,000 high-quality scans, which renders partial 3D shapes from 26 uniformly distributed camera poses for each 3D CAD model. Extensive experiments demonstrate that VRCNet outperforms state-of-the-art methods on all standard point cloud completion benchmarks. Notably, VRCNet shows great generalizability and robustness on real-world point cloud scans.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Real-scanned point clouds are often incomplete due to viewpoint, occlusion, and noise. Existing point cloud completion methods tend to generate global shape skeletons and hence lack fine local details. Furthermore, they mostly learn a deterministic partial-to-complete mapping, but overlook structural relations in man-made objects. To tackle these challenges, this paper proposes a variational framework, Variational Relational point Completion network (VRC-Net) with two appealing properties: 1) Probabilistic Modeling. In particular, we propose a dual-path architecture to enable principled probabilistic modeling across partial and complete clouds. One path consumes complete point clouds for reconstruction by learning a point VAE. The other path generates complete shapes for partial point clouds, whose embedded distribution is guided by distribution obtained from the reconstruction path during training. 2) Relational Enhancement. Specifically, we carefully design point self-attention kernel and point selective kernel module to exploit relational point features, which refines local shape de tails conditioned on the coarse completion. In addition, we contribute a multi-view partial point cloud dataset (MVP dataset) containing over 100,000 high-quality scans, which renders partial 3D shapes from 26 uniformly distributed camera poses for each 3D CAD model. Extensive experiments demonstrate that VRCNet outperforms state-of-the-art methods on all standard point cloud completion benchmarks. Notably, VRCNet shows great generalizability and robustness on real-world point cloud scans.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Real-scanned point clouds are often incomplete due to viewpoint, occlusion, and noise. Existing point cloud completion methods tend to generate global shape skeletons and hence lack fine local details. Furthermore, they mostly learn a deterministic partial-to-complete mapping, but overlook structural relations in man-made objects. To tackle these challenges, this paper proposes a variational framework, Variational Relational point Completion network (VRC-Net) with two appealing properties: 1) Probabilistic Modeling. In particular, we propose a dual-path architecture to enable principled probabilistic modeling across partial and complete clouds. One path consumes complete point clouds for reconstruction by learning a point VAE. The other path generates complete shapes for partial point clouds, whose embedded distribution is guided by distribution obtained from the reconstruction path during training. 2) Relational Enhancement. Specifically, we carefully design point self-attention kernel and point selective kernel module to exploit relational point features, which refines local shape de tails conditioned on the coarse completion. In addition, we contribute a multi-view partial point cloud dataset (MVP dataset) containing over 100,000 high-quality scans, which renders partial 3D shapes from 26 uniformly distributed camera poses for each 3D CAD model. Extensive experiments demonstrate that VRCNet outperforms state-of-the-art methods on all standard point cloud completion benchmarks. Notably, VRCNet shows great generalizability and robustness on real-world point cloud scans.",
"fno": "450900i520",
"keywords": [
"Computational Geometry",
"Feature Extraction",
"Image Reconstruction",
"Image Representation",
"Learning Artificial Intelligence",
"Object Detection",
"Probability",
"Stereo Image Processing",
"Point VAE",
"Point Self Attention Kernel",
"Point Selective Kernel Module",
"Relational Point Features",
"Multiview Partial Point Cloud Dataset",
"Partial 3 D Shapes",
"Partial To Complete Mapping",
"Variational Relational Point Completion Network",
"VRC Net",
"Probabilistic Modeling",
"Training",
"Solid Modeling",
"Three Dimensional Displays",
"Shape",
"Probabilistic Logic",
"Skeleton",
"Robustness"
],
"authors": [
{
"affiliation": "Nanyang Technological University,S-Lab",
"fullName": "Liang Pan",
"givenName": "Liang",
"surname": "Pan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Nanyang Technological University,S-Lab",
"fullName": "Xinyi Chen",
"givenName": "Xinyi",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "SenseTime Research",
"fullName": "Zhongang Cai",
"givenName": "Zhongang",
"surname": "Cai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Nanyang Technological University,S-Lab",
"fullName": "Junzhe Zhang",
"givenName": "Junzhe",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "SenseTime Research",
"fullName": "Haiyu Zhao",
"givenName": "Haiyu",
"surname": "Zhao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "SenseTime Research",
"fullName": "Shuai Yi",
"givenName": "Shuai",
"surname": "Yi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Nanyang Technological University,S-Lab",
"fullName": "Ziwei Liu",
"givenName": "Ziwei",
"surname": "Liu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-06-01T00:00:00",
"pubType": "proceedings",
"pages": "8520-8529",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-4509-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1yeLNhzCKUo",
"name": "pcvpr202145090-09577912s1-mm_450900i520.zip",
"size": "1.5 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pcvpr202145090-09577912s1-mm_450900i520.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "450900i510",
"articleId": "1yeKDuxY4bm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "450900i530",
"articleId": "1yeJhQdQUYE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/3dv/2018/8425/0/842500a728",
"title": "PCN: Point Completion Network",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2018/842500a728/17D45VTRoAx",
"parentPublication": {
"id": "proceedings/3dv/2018/8425/0",
"title": "2018 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200f806",
"title": "3D Shape Generation and Completion through Point-Voxel Diffusion",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200f806/1BmHiEgI4q4",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2022/8563/0/09859918",
"title": "PDP-NET: Patch-Based Dual-Path Network for Point Cloud Completion",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2022/09859918/1G9DLvbZp60",
"parentPublication": {
"id": "proceedings/icme/2022/8563/0",
"title": "2022 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600f533",
"title": "Learning a Structured Latent Space for Unsupervised Point Cloud Completion",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600f533/1H0KOsU2FZC",
"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/cvpr/2022/6946/0/694600b716",
"title": "LAKe-Net: Topology-Aware Point Cloud Completion by Localizing Aligned Keypoints",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600b716/1H0Kwo5tABi",
"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/tp/5555/01/10106495",
"title": "Variational Relational Point Completion Network for Robust 3D Classification",
"doi": null,
"abstractUrl": "/journal/tp/5555/01/10106495/1MwAn9y4Ozu",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800a787",
"title": "Cascaded Refinement Network for Point Cloud Completion",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800a787/1m3np9z0Xu0",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2021/03/09376105",
"title": "An End-to-End Shape-Preserving Point Completion Network",
"doi": null,
"abstractUrl": "/magazine/cg/2021/03/09376105/1rSNcLl15gA",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/11/09525242",
"title": "Cascaded Refinement Network for Point Cloud Completion With Self-Supervision",
"doi": null,
"abstractUrl": "/journal/tp/2022/11/09525242/1wuoUy0AvN6",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpbd&is/2021/1327/0/09658452",
"title": "2D-3DMatchingNet: Multimodal Point Completion with 2D Geometry Matching",
"doi": null,
"abstractUrl": "/proceedings-article/hpbd&is/2021/09658452/1zRFmc9ALyo",
"parentPublication": {
"id": "proceedings/hpbd&is/2021/1327/0",
"title": "2021 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNBV9Icc",
"title": "Proceedings. The 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology",
"acronym": "iat",
"groupId": "1000386",
"volume": "0",
"displayVolume": "0",
"year": "2005",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBd9T2b",
"doi": "10.1109/IAT.2005.123",
"title": "Role-based Rights in Arti.cial Social Systems",
"normalizedTitle": "Role-based Rights in Arti.cial Social Systems",
"abstract": "In this paper we use normative systems to introduce roles and rights in the game-theoretic artificial social systems developed by Shoham and Tennenholtz. We model normative systems as socially constructed agents whose behavior is determined by a set of role playing agents. Roles are again modeled as socially constructed agents, and the roles? behavior is the ideal behavior of agents playing the roles. In our approach, the strategies of the role correspond to the rights that can be exercised by the role. In other words, rights are powers extending the set of strategies of an agent - not constraining them! - due to the new opportunities to exercise rights. We consider the role assignment problem of how to assign agents to roles such that the role playing agent is expected to behave like the ideal behavior of the role. We also consider how the normative system controls the behavior of agents playing a role in it.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper we use normative systems to introduce roles and rights in the game-theoretic artificial social systems developed by Shoham and Tennenholtz. We model normative systems as socially constructed agents whose behavior is determined by a set of role playing agents. Roles are again modeled as socially constructed agents, and the roles? behavior is the ideal behavior of agents playing the roles. In our approach, the strategies of the role correspond to the rights that can be exercised by the role. In other words, rights are powers extending the set of strategies of an agent - not constraining them! - due to the new opportunities to exercise rights. We consider the role assignment problem of how to assign agents to roles such that the role playing agent is expected to behave like the ideal behavior of the role. We also consider how the normative system controls the behavior of agents playing a role in it.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper we use normative systems to introduce roles and rights in the game-theoretic artificial social systems developed by Shoham and Tennenholtz. We model normative systems as socially constructed agents whose behavior is determined by a set of role playing agents. Roles are again modeled as socially constructed agents, and the roles? behavior is the ideal behavior of agents playing the roles. In our approach, the strategies of the role correspond to the rights that can be exercised by the role. In other words, rights are powers extending the set of strategies of an agent - not constraining them! - due to the new opportunities to exercise rights. We consider the role assignment problem of how to assign agents to roles such that the role playing agent is expected to behave like the ideal behavior of the role. We also consider how the normative system controls the behavior of agents playing a role in it.",
"fno": "24160516",
"keywords": [],
"authors": [
{
"affiliation": "Dipartimento di Informatica Universit`a di Torino Italy",
"fullName": "Guido Boella",
"givenName": "Guido",
"surname": "Boella",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "CWI Amsterdam and Delft University of Technology The Netherlands",
"fullName": "Leendert van der Torre",
"givenName": "Leendert",
"surname": "van der Torre",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iat",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2005-09-01T00:00:00",
"pubType": "proceedings",
"pages": "516-519",
"year": "2005",
"issn": null,
"isbn": "0-7695-2416-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "24160512",
"articleId": "12OmNCbCrOV",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "24160520",
"articleId": "12OmNyaGeJM",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wetice/1996/7445/0/74450080",
"title": "Role-based security for distributed object systems",
"doi": null,
"abstractUrl": "/proceedings-article/wetice/1996/74450080/12OmNBOCWoH",
"parentPublication": {
"id": "proceedings/wetice/1996/7445/0",
"title": "Proceedings of WET ICE '96. IEEE 5th Workshop on Enabling Technologies; Infrastucture for Collaborative Enterprises",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ainaw/2008/3096/0/3096a495",
"title": "Role-Based Access Control in Peer-to-Peer (P2P) Societies",
"doi": null,
"abstractUrl": "/proceedings-article/ainaw/2008/3096a495/12OmNCyBXij",
"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": "proceedings/dis/2006/2589/0/25890348",
"title": "A Role-Based Modeling for Agent Teams",
"doi": null,
"abstractUrl": "/proceedings-article/dis/2006/25890348/12OmNqJHFFk",
"parentPublication": {
"id": "proceedings/dis/2006/2589/0",
"title": "IEEE Workshop on Distributed Intelligent Systems: Collective Intelligence and Its Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/edoc/1997/8031/0/80310036",
"title": "A Policy Based Role Object Model",
"doi": null,
"abstractUrl": "/proceedings-article/edoc/1997/80310036/12OmNvonIHj",
"parentPublication": {
"id": "proceedings/edoc/1997/8031/0",
"title": "Proceedings First International Enterprise Distributed Object Computing Workshop",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi-iat/2011/4513/2/4513b133",
"title": "Programming Role Enactment through Reflection",
"doi": null,
"abstractUrl": "/proceedings-article/wi-iat/2011/4513b133/12OmNwLfMBP",
"parentPublication": {
"id": "proceedings/wi-iat/2011/4513/2",
"title": "Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icci/2008/2538/0/04639162",
"title": "Role-based systems are autonomic",
"doi": null,
"abstractUrl": "/proceedings-article/icci/2008/04639162/12OmNxRF78P",
"parentPublication": {
"id": "proceedings/icci/2008/2538/0",
"title": "Cognitive Informatics, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aina/2006/2466/1/246610407",
"title": "Role-Based Concurrency Control for Distributed Systems",
"doi": null,
"abstractUrl": "/proceedings-article/aina/2006/246610407/12OmNzt0IPD",
"parentPublication": {
"id": "proceedings/aina/2006/2466/1",
"title": "20th International Conference on Advanced Information Networking and Applications - Volume 1 (AINA'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wi-iat/2013/5145/2/5145b287",
"title": "Role Modeling for Adaptive Multiagent Systems Engineering",
"doi": null,
"abstractUrl": "/proceedings-article/wi-iat/2013/5145b287/12OmNzwpUm0",
"parentPublication": {
"id": "proceedings/wi-iat/2013/5145/2",
"title": "Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09802694",
"title": "Role-Exchange Playing: An Exploration of Role-Playing Effects for Anti-Bullying in Immersive Virtual Environments",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09802694/1Eo1x2xfhYs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2022/8563/0/09859945",
"title": "ROGC: Role-Oriented Graph Convolution Based Multi-Agent Reinforcement Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2022/09859945/1G9EcdUWtag",
"parentPublication": {
"id": "proceedings/icme/2022/8563/0",
"title": "2022 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNqJ8tgX",
"title": "2016 IEEE 18th Conference on Business Informatics (CBI)",
"acronym": "cbi",
"groupId": "1002843",
"volume": "1",
"displayVolume": "1",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNs59JRb",
"doi": "10.1109/CBI.2016.33",
"title": "Process Modelling as Serious Game: Design of a Role-Playing Game for a Corporate Training",
"normalizedTitle": "Process Modelling as Serious Game: Design of a Role-Playing Game for a Corporate Training",
"abstract": "This paper presents findings of a field study into the design and initial evaluation of a role-playing game based on a model of a complex tendering process at a German manufacturing company. Conceived as part of an inhouse training for 1,000 employees by the process management unit, the role-playing game aims to familiarize the participants with the intricacies of the manufacturer's tendering process—by instructing them to properly interpret a BPMN (Business Process Model & Notation) representation of the process presented to the participants in a modelling tool. Rather than presenting the participants with a syntactically correct and semantically adequate process model, the process model is reduced to a simplified representation of the control flow and to placeholders for activities, events, roles, documents and information systems. In the role-playing game, teams of four employees from different business functions perform the group task of understanding the meaning of predefined model elements in the context of the tendering process, and of assigning these elements to the correct placeholder under time pressure and in competition with other teams in the room. As an original game element, video interviews with experts on a particular aspect of the tendering process are attached to the respective model elements and are required by the participants to solve the group task. The game design is tested and developed in three pilot trainings. We report on the design of the role-playing game, its initial evaluation, and conclude with a discussion of our findings.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents findings of a field study into the design and initial evaluation of a role-playing game based on a model of a complex tendering process at a German manufacturing company. Conceived as part of an inhouse training for 1,000 employees by the process management unit, the role-playing game aims to familiarize the participants with the intricacies of the manufacturer's tendering process—by instructing them to properly interpret a BPMN (Business Process Model & Notation) representation of the process presented to the participants in a modelling tool. Rather than presenting the participants with a syntactically correct and semantically adequate process model, the process model is reduced to a simplified representation of the control flow and to placeholders for activities, events, roles, documents and information systems. In the role-playing game, teams of four employees from different business functions perform the group task of understanding the meaning of predefined model elements in the context of the tendering process, and of assigning these elements to the correct placeholder under time pressure and in competition with other teams in the room. As an original game element, video interviews with experts on a particular aspect of the tendering process are attached to the respective model elements and are required by the participants to solve the group task. The game design is tested and developed in three pilot trainings. We report on the design of the role-playing game, its initial evaluation, and conclude with a discussion of our findings.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents findings of a field study into the design and initial evaluation of a role-playing game based on a model of a complex tendering process at a German manufacturing company. Conceived as part of an inhouse training for 1,000 employees by the process management unit, the role-playing game aims to familiarize the participants with the intricacies of the manufacturer's tendering process—by instructing them to properly interpret a BPMN (Business Process Model & Notation) representation of the process presented to the participants in a modelling tool. Rather than presenting the participants with a syntactically correct and semantically adequate process model, the process model is reduced to a simplified representation of the control flow and to placeholders for activities, events, roles, documents and information systems. In the role-playing game, teams of four employees from different business functions perform the group task of understanding the meaning of predefined model elements in the context of the tendering process, and of assigning these elements to the correct placeholder under time pressure and in competition with other teams in the room. As an original game element, video interviews with experts on a particular aspect of the tendering process are attached to the respective model elements and are required by the participants to solve the group task. The game design is tested and developed in three pilot trainings. We report on the design of the role-playing game, its initial evaluation, and conclude with a discussion of our findings.",
"fno": "3231a228",
"keywords": [
"Games",
"Training",
"Computational Modeling",
"Business Process Management",
"Companies",
"Field Study",
"Business Process Modelling",
"Serious Game"
],
"authors": [
{
"affiliation": null,
"fullName": "Stefan Strecker",
"givenName": "Stefan",
"surname": "Strecker",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Kristina Rosenthal",
"givenName": "Kristina",
"surname": "Rosenthal",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cbi",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-08-01T00:00:00",
"pubType": "proceedings",
"pages": "228-237",
"year": "2016",
"issn": "2378-1971",
"isbn": "978-1-5090-3231-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3231a218",
"articleId": "12OmNyuPLhQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3231a238",
"articleId": "12OmNzmclXn",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cbi/2016/3231/1/3231a248",
"title": "Learning Business Process Management through Serious Games: Feedbacks on the Usage of INNOV8",
"doi": null,
"abstractUrl": "/proceedings-article/cbi/2016/3231a248/12OmNvAAtD5",
"parentPublication": {
"id": "proceedings/cbi/2016/3231/2",
"title": "2016 IEEE 18th Conference on Business Informatics (CBI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2016/9041/0/9041a148",
"title": "Teaching STEM through a Role-Playing Serious Game and Intelligent Pedagogical Agents",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2016/9041a148/12OmNwpGgN1",
"parentPublication": {
"id": "proceedings/icalt/2016/9041/0",
"title": "2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2014/2504/0/2504b213",
"title": "Cultural Differences in Playing Repeated Ultimatum Game Online with Virtual Humans",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2014/2504b213/12OmNx19jS2",
"parentPublication": {
"id": "proceedings/hicss/2014/2504/0",
"title": "2014 47th Hawaii International Conference on System Sciences (HICSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgames/2011/1451/0/06000361",
"title": "A study of how different game play aspects can affect the popularity of role-playing video games",
"doi": null,
"abstractUrl": "/proceedings-article/cgames/2011/06000361/12OmNxFsmm2",
"parentPublication": {
"id": "proceedings/cgames/2011/1451/0",
"title": "2011 16th International Conference on Computer Games (CGAMES)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itng/2011/4367/0/4367a816",
"title": "Artificial Intelligence Design in a Multiplayer Online Role Playing Game",
"doi": null,
"abstractUrl": "/proceedings-article/itng/2011/4367a816/12OmNxXl5xc",
"parentPublication": {
"id": "proceedings/itng/2011/4367/0",
"title": "Information Technology: New Generations, Third International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cseet/2012/1592/0/06245003",
"title": "A Role-Playing Game for a Software Engineering Lab: Developing a Product Line",
"doi": null,
"abstractUrl": "/proceedings-article/cseet/2012/06245003/12OmNzhnagd",
"parentPublication": {
"id": "proceedings/cseet/2012/1592/0",
"title": "2012 IEEE 25th Conference on Software Engineering Education and Training (CSEE&T)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ci/2014/04/06720188",
"title": "The Axiom General Purpose Game Playing System",
"doi": null,
"abstractUrl": "/journal/ci/2014/04/06720188/13rRUy0ZzSg",
"parentPublication": {
"id": "trans/ci",
"title": "IEEE Transactions on Computational Intelligence and AI in Games",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2018/7123/0/08493440",
"title": "Rallye Game: Learning by Playing with Racing Cars",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2018/08493440/14tNJrfrsWe",
"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": "proceedings/iisa/2018/8161/0/08633655",
"title": "A Stereotype User Model for an Educational Game: Overcome the Difficulties in Game Playing and Focus on the Educational Goal",
"doi": null,
"abstractUrl": "/proceedings-article/iisa/2018/08633655/17D45XlyDvd",
"parentPublication": {
"id": "proceedings/iisa/2018/8161/0",
"title": "2018 9th International Conference on Information, Intelligence, Systems and Applications (IISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsme/2020/5619/0/561900a692",
"title": "Regression Testing of Massively Multiplayer Online Role-Playing Games",
"doi": null,
"abstractUrl": "/proceedings-article/icsme/2020/561900a692/1oqKNobL9i8",
"parentPublication": {
"id": "proceedings/icsme/2020/5619/0",
"title": "2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNC8dg90",
"title": "2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)",
"acronym": "icalt",
"groupId": "1000009",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwpGgN1",
"doi": "10.1109/ICALT.2016.121",
"title": "Teaching STEM through a Role-Playing Serious Game and Intelligent Pedagogical Agents",
"normalizedTitle": "Teaching STEM through a Role-Playing Serious Game and Intelligent Pedagogical Agents",
"abstract": "Teaching STEM is a promising application domain for game-based instructional methods. In this paper we present a serious game organized as a role playing game: players learn how to inhabit the headspace of someone other than their primary ego identity, offering them the chance to develop a stronger sense of empathy. The same empathy is established between the player and her Intelligent Pedagogical Agent, which should guide the player into the Virtual Learning Environment and trough the game as well. We present the ongoing development of the game, and a preliminary validation of the Intelligent Pedagogical Agent to show its effectiveness with teenager students.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Teaching STEM is a promising application domain for game-based instructional methods. In this paper we present a serious game organized as a role playing game: players learn how to inhabit the headspace of someone other than their primary ego identity, offering them the chance to develop a stronger sense of empathy. The same empathy is established between the player and her Intelligent Pedagogical Agent, which should guide the player into the Virtual Learning Environment and trough the game as well. We present the ongoing development of the game, and a preliminary validation of the Intelligent Pedagogical Agent to show its effectiveness with teenager students.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Teaching STEM is a promising application domain for game-based instructional methods. In this paper we present a serious game organized as a role playing game: players learn how to inhabit the headspace of someone other than their primary ego identity, offering them the chance to develop a stronger sense of empathy. The same empathy is established between the player and her Intelligent Pedagogical Agent, which should guide the player into the Virtual Learning Environment and trough the game as well. We present the ongoing development of the game, and a preliminary validation of the Intelligent Pedagogical Agent to show its effectiveness with teenager students.",
"fno": "9041a148",
"keywords": [
"Games",
"Education",
"Artificial Intelligence",
"Problem Solving",
"Computational Modeling",
"Mobile Handsets",
"Avatars",
"Game Based Learning",
"Virtual Learning Environment",
"Intelligent Pedagogical Agent"
],
"authors": [
{
"affiliation": null,
"fullName": "A. Terracina",
"givenName": "A.",
"surname": "Terracina",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "R. Berta",
"givenName": "R.",
"surname": "Berta",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "F. Bordini",
"givenName": "F.",
"surname": "Bordini",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "R. Damilano",
"givenName": "R.",
"surname": "Damilano",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "M. Mecella",
"givenName": "M.",
"surname": "Mecella",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icalt",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-07-01T00:00:00",
"pubType": "proceedings",
"pages": "148-152",
"year": "2016",
"issn": "2161-377X",
"isbn": "978-1-4673-9041-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "9041a143",
"articleId": "12OmNxGAL6Y",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "9041a153",
"articleId": "12OmNzFv4iL",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/t4e/2016/6115/0/6115a120",
"title": "Evidence Centred Approach to Measuring Learning Outcomes Amongst Management Students Using Epistemic Games",
"doi": null,
"abstractUrl": "/proceedings-article/t4e/2016/6115a120/12OmNA1DMjH",
"parentPublication": {
"id": "proceedings/t4e/2016/6115/0",
"title": "2016 IEEE Eighth International Conference on Technology for Education (T4E)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wmute/2012/4662/0/4662a017",
"title": "Mobile Gaming - A Serious Business!",
"doi": null,
"abstractUrl": "/proceedings-article/wmute/2012/4662a017/12OmNAoUTmb",
"parentPublication": {
"id": "proceedings/wmute/2012/4662/0",
"title": "IEEE International Conference on Wireless, Mobile, and Ubiquitous Technology in Education",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgames/2015/7921/0/07272956",
"title": "Machiavellian agents: Player modelling to deceive and be deceived",
"doi": null,
"abstractUrl": "/proceedings-article/cgames/2015/07272956/12OmNC1Y5hv",
"parentPublication": {
"id": "proceedings/cgames/2015/7921/0",
"title": "2015 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2011/4346/0/4346a486",
"title": "Tailoring Serious Games with Adaptive Pedagogical Scenarios: A Serious Game for Persons with Cognitive Disabilities",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2011/4346a486/12OmNCwUmBe",
"parentPublication": {
"id": "proceedings/icalt/2011/4346/0",
"title": "Advanced Learning Technologies, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2015/9403/0/9403a145",
"title": "Does the Perceived Identity of Non-player Characters Change How We Interact with Them?",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2015/9403a145/12OmNyoAA5i",
"parentPublication": {
"id": "proceedings/cw/2015/9403/0",
"title": "2015 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2015/8102/0/07295780",
"title": "Mapping between Pedagogical Design Strategies and Serious Game Narratives",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2015/07295780/12OmNyqRn5Y",
"parentPublication": {
"id": "proceedings/vs-games/2015/8102/0",
"title": "2015 7th International Conference on Games and Virtual Worlds for Serious Applications (VS-Games)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2017/3870/0/3870a178",
"title": "Towards Serious Game Content-Extraction for a Pedagogical Evaluation",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2017/3870a178/12OmNyuPLlV",
"parentPublication": {
"id": "proceedings/icalt/2017/3870/0",
"title": "2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgames/2014/5854/0/06934153",
"title": "Identification features and pedagogical agents in a mathematical game",
"doi": null,
"abstractUrl": "/proceedings-article/cgames/2014/06934153/12OmNzXnNo6",
"parentPublication": {
"id": "proceedings/cgames/2014/5854/0",
"title": "2014 Computer Games: AI, Animation, Mobile, Multimedia, Educational and Serious Games (CGAMES)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/lt/2016/03/07390265",
"title": "Agent Supported Serious Game Environment",
"doi": null,
"abstractUrl": "/journal/lt/2016/03/07390265/13rRUIM2Vyo",
"parentPublication": {
"id": "trans/lt",
"title": "IEEE Transactions on Learning Technologies",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2022/5908/0/09953869",
"title": "Computational Empathy Counteracts the Negative Effects of Anger on Creative Problem Solving",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2022/09953869/1IAK52oWzbq",
"parentPublication": {
"id": "proceedings/acii/2022/5908/0",
"title": "2022 10th International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxTEiSp",
"title": "2015 4th International Conference on Modeling and Simulation (MAS)",
"acronym": "mas",
"groupId": "1812404",
"volume": "0",
"displayVolume": "0",
"year": "2015",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyuPLlj",
"doi": "10.1109/MAS.2015.19",
"title": "A Social Network Analysis of a Massively Multi-player On-Line Role Playing Game",
"normalizedTitle": "A Social Network Analysis of a Massively Multi-player On-Line Role Playing Game",
"abstract": "An instance of a massively on-line role playing game called The Mana World is analyzed for its social networks. The gathered data is the result of the first phase of the ModelMMORPG project in which players played a specially designed quest during a controlled experiment. Observations based on the monitored virtual community behaviour and individual elements of interaction are visualised herein and analysed using social network analysis. Insight into the dynamics of the studied virtual society is given along with observations regarding structure of groups and individuals alike.",
"abstracts": [
{
"abstractType": "Regular",
"content": "An instance of a massively on-line role playing game called The Mana World is analyzed for its social networks. The gathered data is the result of the first phase of the ModelMMORPG project in which players played a specially designed quest during a controlled experiment. Observations based on the monitored virtual community behaviour and individual elements of interaction are visualised herein and analysed using social network analysis. Insight into the dynamics of the studied virtual society is given along with observations regarding structure of groups and individuals alike.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "An instance of a massively on-line role playing game called The Mana World is analyzed for its social networks. The gathered data is the result of the first phase of the ModelMMORPG project in which players played a specially designed quest during a controlled experiment. Observations based on the monitored virtual community behaviour and individual elements of interaction are visualised herein and analysed using social network analysis. Insight into the dynamics of the studied virtual society is given along with observations regarding structure of groups and individuals alike.",
"fno": "9828a037",
"keywords": [
"Computer Games",
"Social Networking Online",
"Social Network Analysis",
"Massively Multiplayer Online Role Playing Game",
"Massively Online Role Playing Game",
"The Mana World",
"Model MMORPG Project",
"Virtual Community Behaviour",
"Virtual Society",
"Games",
"Social Network Services",
"Analytical Models",
"Data Visualization",
"Avatars",
"Data Collection",
"Organizations",
"Virtual Community",
"MMORPG",
"Social Network Analysis"
],
"authors": [
{
"affiliation": "Artificial Intell. Lab., Univ. of Zagreb, Varaſdin, Croatia",
"fullName": "Markus Schatten",
"givenName": "Markus",
"surname": "Schatten",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Artificial Intell. Lab., Univ. of Zagreb, Varaſdin, Croatia",
"fullName": "Bogdan Okrea Ðuric",
"givenName": "Bogdan Okrea",
"surname": "Ðuric",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "mas",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2015-11-01T00:00:00",
"pubType": "proceedings",
"pages": "37-42",
"year": "2015",
"issn": null,
"isbn": "978-1-4673-9828-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "9828a033",
"articleId": "12OmNqBtiVy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "9828a043",
"articleId": "12OmNqJq4rI",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/aina/2015/7905/0/7905a406",
"title": "Detection of Illegal Players in Massively Multiplayer Online Role Playing Game by Classification Algorithms",
"doi": null,
"abstractUrl": "/proceedings-article/aina/2015/7905a406/12OmNvoWV4E",
"parentPublication": {
"id": "proceedings/aina/2015/7905/0",
"title": "2015 IEEE 29th International Conference on Advanced Information Networking and Applications (AINA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/passat-socialcom/2011/1931/0/06113105",
"title": "An Exploratory Study of Player Performance, Motivation, and Enjoyment in Massively Multiplayer Online Role-Playing Games",
"doi": null,
"abstractUrl": "/proceedings-article/passat-socialcom/2011/06113105/12OmNwCsdDG",
"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": "proceedings/icdmw/2010/4257/0/4257a997",
"title": "Sequence Alignment Based Analysis of Player Behavior in Massively Multiplayer Online Role-Playing Games (MMORPGs)",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2010/4257a997/12OmNweBUQD",
"parentPublication": {
"id": "proceedings/icdmw/2010/4257/0",
"title": "2010 IEEE International Conference on Data Mining Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2016/9041/0/9041a148",
"title": "Teaching STEM through a Role-Playing Serious Game and Intelligent Pedagogical Agents",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2016/9041a148/12OmNwpGgN1",
"parentPublication": {
"id": "proceedings/icalt/2016/9041/0",
"title": "2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asonam/2011/4375/0/4375a438",
"title": "Modeling Player Performance in Massively Multiplayer Online Role-Playing Games: The Effects of Diversity in Mentoring Network",
"doi": null,
"abstractUrl": "/proceedings-article/asonam/2011/4375a438/12OmNxeut85",
"parentPublication": {
"id": "proceedings/asonam/2011/4375/0",
"title": "2011 International Conference on Advances in Social Networks Analysis and Mining",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asonam/2011/4375/0/4375a561",
"title": "Effects of Mentoring on Player Performance in Massively Multiplayer Online Role-Playing Games (MMORPGs)",
"doi": null,
"abstractUrl": "/proceedings-article/asonam/2011/4375a561/12OmNylsZNk",
"parentPublication": {
"id": "proceedings/asonam/2011/4375/0",
"title": "2011 International Conference on Advances in Social Networks Analysis and Mining",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ec/2015/02/06910312",
"title": "A Survey and Analysis of Techniques for Player Behavior Prediction in Massively Multiplayer Online Role-Playing Games",
"doi": null,
"abstractUrl": "/journal/ec/2015/02/06910312/13rRUILLkrm",
"parentPublication": {
"id": "trans/ec",
"title": "IEEE Transactions on Emerging Topics in Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/sp/2009/03/msp2009030013",
"title": "Reducing the Attack Surface in Massively Multiplayer Online Role-Playing Games",
"doi": null,
"abstractUrl": "/magazine/sp/2009/03/msp2009030013/13rRUygT7l3",
"parentPublication": {
"id": "mags/sp",
"title": "IEEE Security & Privacy",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2018/6857/0/685700a247",
"title": "Player Types in Mobile Learning Games – Playing Patterns and Motivation",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2018/685700a247/17D45WK5Ala",
"parentPublication": {
"id": "proceedings/ism/2018/6857/0",
"title": "2018 IEEE International Symposium on Multimedia (ISM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2018/7315/0/731500a108",
"title": "Autonomous Virtual Player in a Video Game Imitating Human Players: The ORION Framework",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2018/731500a108/17D45WK5Anp",
"parentPublication": {
"id": "proceedings/cw/2018/7315/0",
"title": "2018 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNvkYx8t",
"title": "2011 44th Hawaii International Conference on System Sciences",
"acronym": "hicss",
"groupId": "1000730",
"volume": "0",
"displayVolume": "0",
"year": "2011",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNywxlSe",
"doi": "10.1109/HICSS.2011.484",
"title": "Virtual Team Role Play Using Second Life for Teaching Business Process Concepts",
"normalizedTitle": "Virtual Team Role Play Using Second Life for Teaching Business Process Concepts",
"abstract": "This paper describes the use of a virtual world environment to facilitate a role play assignment for buying and selling Enterprise Resource Planning (ERP) software solutions in a distributed environment. The exercise involved the use of Second Life to facilitate the virtual presentation and meeting among the vendors and the purchaser of the software. Students playing vendors and purchase roles were organized into teams who meet, collaborate, and negotiate business transactions in the virtual environment. The aim of the experiment was to introduce students to properties of ERP-systems which are the most common software systems used by businesses, and at the same time introduce tools for virtual team collaboration in an international setting between students in Norway and Australia. This paper reports the experiences from the students' and teachers' perspectives and we give recommendations regarding the use of Second Life in role-playing exercises.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper describes the use of a virtual world environment to facilitate a role play assignment for buying and selling Enterprise Resource Planning (ERP) software solutions in a distributed environment. The exercise involved the use of Second Life to facilitate the virtual presentation and meeting among the vendors and the purchaser of the software. Students playing vendors and purchase roles were organized into teams who meet, collaborate, and negotiate business transactions in the virtual environment. The aim of the experiment was to introduce students to properties of ERP-systems which are the most common software systems used by businesses, and at the same time introduce tools for virtual team collaboration in an international setting between students in Norway and Australia. This paper reports the experiences from the students' and teachers' perspectives and we give recommendations regarding the use of Second Life in role-playing exercises.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper describes the use of a virtual world environment to facilitate a role play assignment for buying and selling Enterprise Resource Planning (ERP) software solutions in a distributed environment. The exercise involved the use of Second Life to facilitate the virtual presentation and meeting among the vendors and the purchaser of the software. Students playing vendors and purchase roles were organized into teams who meet, collaborate, and negotiate business transactions in the virtual environment. The aim of the experiment was to introduce students to properties of ERP-systems which are the most common software systems used by businesses, and at the same time introduce tools for virtual team collaboration in an international setting between students in Norway and Australia. This paper reports the experiences from the students' and teachers' perspectives and we give recommendations regarding the use of Second Life in role-playing exercises.",
"fno": "05718430",
"keywords": [
"Computer Aided Instruction",
"Enterprise Resource Planning",
"Management Education",
"Teaching",
"Virtual Reality",
"Virtual Team Role Play",
"Business Process Concepts",
"Teaching",
"Virtual World Environment",
"Enterprise Resource Planning",
"ERP Software Solutions",
"Distributed Environment",
"Second Life",
"Virtual Presentation",
"Virtual Meeting",
"Virtual Team Collaboration",
"Norway",
"Australia",
"Second Life",
"Marketing And Sales",
"Avatars",
"Companies",
"Information Systems",
"Virtual Groups"
],
"authors": [
{
"affiliation": null,
"fullName": "Amit Rudra",
"givenName": "Amit",
"surname": "Rudra",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Bjorn Jaeger",
"givenName": "Bjorn",
"surname": "Jaeger",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Ashley Aitken",
"givenName": "Ashley",
"surname": "Aitken",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Vanessa Chang",
"givenName": "Vanessa",
"surname": "Chang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Berit Helgheim",
"givenName": "Berit",
"surname": "Helgheim",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "hicss",
"isOpenAccess": true,
"showRecommendedArticles": true,
"showBuyMe": false,
"hasPdf": true,
"pubDate": "2011-01-01T00:00:00",
"pubType": "proceedings",
"pages": "1-8",
"year": "2011",
"issn": "1530-1605",
"isbn": "978-1-4244-9618-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05718429",
"articleId": "12OmNzdGnyc",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05718431",
"articleId": "12OmNwt5snA",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icalt/2015/7334/0/7334a464",
"title": "Teaching Interpersonal Problem Solving Skills Using Roleplay in a 3D Virtual World for Special Education: A Case Study in Second Life",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2015/7334a464/12OmNAPjA73",
"parentPublication": {
"id": "proceedings/icalt/2015/7334/0",
"title": "2015 IEEE 15th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2014/4038/0/4038a691",
"title": "The Teacher as Designer: Preparations for Teaching in a Second Life Distance Education Course",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2014/4038a691/12OmNASraXo",
"parentPublication": {
"id": "proceedings/icalt/2014/4038/0",
"title": "2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2011/4467/0/4467a227",
"title": "Avatar Impotence: On 'User Will,' 'Avatar Agency,' and 'System Control' in Second Life",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2011/4467a227/12OmNBa2iAQ",
"parentPublication": {
"id": "proceedings/cw/2011/4467/0",
"title": "2011 International Conference on Cyberworlds",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/digitel/2010/3993/0/3993a114",
"title": "Recreating Ancient Egyptian Culture in Second Life",
"doi": null,
"abstractUrl": "/proceedings-article/digitel/2010/3993a114/12OmNC4wtu7",
"parentPublication": {
"id": "proceedings/digitel/2010/3993/0",
"title": "Digital Game and Intelligent Toy Enhanced Learning, IEEE International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2010/6331/0/05459570",
"title": "Social Traps in Second Life",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2010/05459570/12OmNCxbXLf",
"parentPublication": {
"id": "proceedings/vs-games/2010/6331/0",
"title": "2010 2nd International Conference on Games and Virtual Worlds for Serious Applications (VS-GAMES 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2012/4814/0/4814a107",
"title": "Immersion in Virtual Worlds - But not Second Life!",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2012/4814a107/12OmNrAv3P5",
"parentPublication": {
"id": "proceedings/cw/2012/4814/0",
"title": "2012 International Conference on Cyberworlds",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2010/4215/0/4215a215",
"title": "Leisure Time in Second Life: Cultural Differences and Similarities",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2010/4215a215/12OmNy3149H",
"parentPublication": {
"id": "proceedings/cw/2010/4215/0",
"title": "2010 International Conference on Cyberworlds",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2011/348/0/06012038",
"title": "Toward region- and action-aware second life clients: A parameterized second life traffic model",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2011/06012038/12OmNzZ5oh8",
"parentPublication": {
"id": "proceedings/icme/2011/348/0",
"title": "2011 IEEE International Conference on Multimedia and Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/nt/2011/01/05545464",
"title": "Exploring Second Life",
"doi": null,
"abstractUrl": "/journal/nt/2011/01/05545464/13rRUwI5TUN",
"parentPublication": {
"id": "trans/nt",
"title": "IEEE/ACM Transactions on Networking",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/sp/2009/02/msp2009020071",
"title": "Security Education Using Second Life",
"doi": null,
"abstractUrl": "/magazine/sp/2009/02/msp2009020071/13rRUwh80Fg",
"parentPublication": {
"id": "mags/sp",
"title": "IEEE Security & Privacy",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNANkoae",
"title": "2010 5th International Workshop on Requirements Engineering Education and Training (REET 2010)",
"acronym": "reet",
"groupId": "1002648",
"volume": "0",
"displayVolume": "0",
"year": "2010",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzX6cge",
"doi": "10.1109/REET.2010.5633115",
"title": "Experiences of using role playing andwiki in requirements engineering course projects",
"normalizedTitle": "Experiences of using role playing andwiki in requirements engineering course projects",
"abstract": "Teaching requirements engineering (RE) course is challenging for teachers and a bit of boring for students due to the lack of involvement to a real software development project. Role playing method has been introduced as an effective pedagogical approach that allows students to practise RE methods in a simulated project environment by playing different roles/stakeholders at RE phase. We employ role playing method with a wiki tool support in the RE course projects for the third-year bachelor students running in the academic year of 2009-2010. In this paper, we report our experiences gained in applying role playing method and the wiki tool according to the survey results from the students who participated this course. We believe that the lessons learned in our experiences will help other RE education and training practitioners to improve their RE course projects by using role playing method and appropriate RE tools.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Teaching requirements engineering (RE) course is challenging for teachers and a bit of boring for students due to the lack of involvement to a real software development project. Role playing method has been introduced as an effective pedagogical approach that allows students to practise RE methods in a simulated project environment by playing different roles/stakeholders at RE phase. We employ role playing method with a wiki tool support in the RE course projects for the third-year bachelor students running in the academic year of 2009-2010. In this paper, we report our experiences gained in applying role playing method and the wiki tool according to the survey results from the students who participated this course. We believe that the lessons learned in our experiences will help other RE education and training practitioners to improve their RE course projects by using role playing method and appropriate RE tools.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Teaching requirements engineering (RE) course is challenging for teachers and a bit of boring for students due to the lack of involvement to a real software development project. Role playing method has been introduced as an effective pedagogical approach that allows students to practise RE methods in a simulated project environment by playing different roles/stakeholders at RE phase. We employ role playing method with a wiki tool support in the RE course projects for the third-year bachelor students running in the academic year of 2009-2010. In this paper, we report our experiences gained in applying role playing method and the wiki tool according to the survey results from the students who participated this course. We believe that the lessons learned in our experiences will help other RE education and training practitioners to improve their RE course projects by using role playing method and appropriate RE tools.",
"fno": "05633115",
"keywords": [
"Computer Aided Instruction",
"Computer Science Education",
"Internet",
"Software Engineering",
"Using Role Playing Experiences",
"Requirements Engineering Course Projects",
"Wiki",
"Teaching Requirements Engineering",
"RE",
"Software Development Project",
"Pedagogical Approach",
"Simulated Project Environment",
"RE Course Projects",
"Education",
"Requirements Engineering Education",
"Course Project",
"Role Playing",
"Wiki"
],
"authors": [
{
"affiliation": "Department of Computing Science, University of Groningen, The Netherlands",
"fullName": "Peng Liang",
"givenName": null,
"surname": "Peng Liang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Graduate School of Science, University of Groningen, The Netherlands",
"fullName": "Onno de Graaf",
"givenName": "Onno",
"surname": "de Graaf",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "reet",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2010-09-01T00:00:00",
"pubType": "proceedings",
"pages": "1-6",
"year": "2010",
"issn": null,
"isbn": "978-1-4244-8786-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05633114",
"articleId": "12OmNxWcHkv",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05633112",
"articleId": "12OmNvT2p7X",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icse/2005/963/0/01553628",
"title": "The role of a project-based capstone course",
"doi": null,
"abstractUrl": "/proceedings-article/icse/2005/01553628/12OmNwdbVba",
"parentPublication": {
"id": "proceedings/icse/2005/963/0",
"title": "27th International Conference on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/digitel/2010/3993/0/3993a103",
"title": "Web-Based Multiplayer Online Role Playing Game (MORPG) for Assessing Students' Java Programming Knowledge and Skills",
"doi": null,
"abstractUrl": "/proceedings-article/digitel/2010/3993a103/12OmNwpGgId",
"parentPublication": {
"id": "proceedings/digitel/2010/3993/0",
"title": "Digital Game and Intelligent Toy Enhanced Learning, IEEE International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2016/9041/0/9041a148",
"title": "Teaching STEM through a Role-Playing Serious Game and Intelligent Pedagogical Agents",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2016/9041a148/12OmNwpGgN1",
"parentPublication": {
"id": "proceedings/icalt/2016/9041/0",
"title": "2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/re/2003/1980/0/19800233",
"title": "Teaching Requirements Engineering through Role Playing: Lessons Learnt",
"doi": null,
"abstractUrl": "/proceedings-article/re/2003/19800233/12OmNyxFKki",
"parentPublication": {
"id": "proceedings/re/2003/1980/0",
"title": "Proceedings. 11th IEEE International Requirements Engineering Conference, 2003.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cseet/2012/1592/0/06245003",
"title": "A Role-Playing Game for a Software Engineering Lab: Developing a Product Line",
"doi": null,
"abstractUrl": "/proceedings-article/cseet/2012/06245003/12OmNzhnagd",
"parentPublication": {
"id": "proceedings/cseet/2012/1592/0",
"title": "2012 IEEE 25th Conference on Software Engineering Education and Training (CSEE&T)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09802694",
"title": "Role-Exchange Playing: An Exploration of Role-Playing Effects for Anti-Bullying in Immersive Virtual Environments",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09802694/1Eo1x2xfhYs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2022/6244/0/09962708",
"title": "Pilot Study and Survey to Increase Adoption and Sustained Utilization of Simulations Using Role-Play Course Content",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2022/09962708/1IHoopZ7ppm",
"parentPublication": {
"id": "proceedings/fie/2022/6244/0",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ccat/2022/9069/0/906900a084",
"title": "Application of Role-Playing to Enhance Participation in Computer Network Technology Course",
"doi": null,
"abstractUrl": "/proceedings-article/ccat/2022/906900a084/1JZ3TfwlYT6",
"parentPublication": {
"id": "proceedings/ccat/2022/9069/0",
"title": "2022 International Conference on Computer Applications Technology (CCAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icore/2022/3390/0/339000a208",
"title": "D-Knights: A 3D Role-Playing Mobile Game for Students with Dyscalculia and Math Learning Disability",
"doi": null,
"abstractUrl": "/proceedings-article/icore/2022/339000a208/1LSOTTDVmO4",
"parentPublication": {
"id": "proceedings/icore/2022/3390/0",
"title": "2022 2nd International Conference in Information and Computing Research (iCORE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsa-c/2023/6459/0/645900a171",
"title": "Role-playing software architecture styles",
"doi": null,
"abstractUrl": "/proceedings-article/icsa-c/2023/645900a171/1MBDgupz3fq",
"parentPublication": {
"id": "proceedings/icsa-c/2023/6459/0",
"title": "2023 IEEE 20th International Conference on Software Architecture Companion (ICSA-C)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1JZ3SbqEF9K",
"title": "2022 International Conference on Computer Applications Technology (CCAT)",
"acronym": "ccat",
"groupId": "10006724",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1JZ3TfwlYT6",
"doi": "10.1109/CCAT56798.2022.00023",
"title": "Application of Role-Playing to Enhance Participation in Computer Network Technology Course",
"normalizedTitle": "Application of Role-Playing to Enhance Participation in Computer Network Technology Course",
"abstract": "Based on the fact that many difficult points of Computer Network Technology course could be more effectively understood and mastered through the “interactive process”, the present paper explores to introduce the method of role-playing in this course teaching. Results show that the course used role-playing was obviously more impressive for students than other courses. The role-playing method could effectively enhance students' participation in the classroom and promote their ability of master difficult points of the course.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Based on the fact that many difficult points of Computer Network Technology course could be more effectively understood and mastered through the “interactive process”, the present paper explores to introduce the method of role-playing in this course teaching. Results show that the course used role-playing was obviously more impressive for students than other courses. The role-playing method could effectively enhance students' participation in the classroom and promote their ability of master difficult points of the course.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Based on the fact that many difficult points of Computer Network Technology course could be more effectively understood and mastered through the “interactive process”, the present paper explores to introduce the method of role-playing in this course teaching. Results show that the course used role-playing was obviously more impressive for students than other courses. The role-playing method could effectively enhance students' participation in the classroom and promote their ability of master difficult points of the course.",
"fno": "906900a084",
"keywords": [
"Computer Aided Instruction",
"Computer Networks",
"Computer Science Education",
"Educational Courses",
"Teaching",
"Computer Network Technology Course",
"Course Teaching",
"Interactive Process",
"Master Difficult Points",
"Role Playing Method",
"Students",
"Students Participation",
"Education",
"Computer Applications",
"Computer Networks",
"Computer Network Technology Course",
"Role Playing",
"To Promote Participation"
],
"authors": [
{
"affiliation": "School of Information Engineering, Wuhan Business University,Wuhan,China",
"fullName": "Hui Mao",
"givenName": "Hui",
"surname": "Mao",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ccat",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-07-01T00:00:00",
"pubType": "proceedings",
"pages": "84-88",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-9069-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "906900a080",
"articleId": "1JZ3SOMEzgk",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "906900a089",
"articleId": "1JZ3TlFQRHO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/isspit/2008/3554/0/04775676",
"title": "Simple Computer Vision System for Chess Playing Robot Manipulator as a Project-based Learning Example",
"doi": null,
"abstractUrl": "/proceedings-article/isspit/2008/04775676/12OmNvnfkdd",
"parentPublication": {
"id": "proceedings/isspit/2008/3554/0",
"title": "2008 8th IEEE International Symposium on Signal Processing and Information Technology. ISSPIT 2008",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icse/2005/963/0/01553628",
"title": "The role of a project-based capstone course",
"doi": null,
"abstractUrl": "/proceedings-article/icse/2005/01553628/12OmNwdbVba",
"parentPublication": {
"id": "proceedings/icse/2005/963/0",
"title": "27th International Conference on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/digitel/2010/3993/0/3993a103",
"title": "Web-Based Multiplayer Online Role Playing Game (MORPG) for Assessing Students' Java Programming Knowledge and Skills",
"doi": null,
"abstractUrl": "/proceedings-article/digitel/2010/3993a103/12OmNwpGgId",
"parentPublication": {
"id": "proceedings/digitel/2010/3993/0",
"title": "Digital Game and Intelligent Toy Enhanced Learning, IEEE International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/re/2003/1980/0/19800233",
"title": "Teaching Requirements Engineering through Role Playing: Lessons Learnt",
"doi": null,
"abstractUrl": "/proceedings-article/re/2003/19800233/12OmNyxFKki",
"parentPublication": {
"id": "proceedings/re/2003/1980/0",
"title": "Proceedings. 11th IEEE International Requirements Engineering Conference, 2003.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/reet/2010/8786/0/05633115",
"title": "Experiences of using role playing andwiki in requirements engineering course projects",
"doi": null,
"abstractUrl": "/proceedings-article/reet/2010/05633115/12OmNzX6cge",
"parentPublication": {
"id": "proceedings/reet/2010/8786/0",
"title": "2010 5th International Workshop on Requirements Engineering Education and Training (REET 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cseet/2012/1592/0/06245003",
"title": "A Role-Playing Game for a Software Engineering Lab: Developing a Product Line",
"doi": null,
"abstractUrl": "/proceedings-article/cseet/2012/06245003/12OmNzhnagd",
"parentPublication": {
"id": "proceedings/cseet/2012/1592/0",
"title": "2012 IEEE 25th Conference on Software Engineering Education and Training (CSEE&T)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09802694",
"title": "Role-Exchange Playing: An Exploration of Role-Playing Effects for Anti-Bullying in Immersive Virtual Environments",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09802694/1Eo1x2xfhYs",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2022/6244/0/09962708",
"title": "Pilot Study and Survey to Increase Adoption and Sustained Utilization of Simulations Using Role-Play Course Content",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2022/09962708/1IHoopZ7ppm",
"parentPublication": {
"id": "proceedings/fie/2022/6244/0",
"title": "2022 IEEE Frontiers in Education Conference (FIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsa-c/2023/6459/0/645900a171",
"title": "Role-playing software architecture styles",
"doi": null,
"abstractUrl": "/proceedings-article/icsa-c/2023/645900a171/1MBDgupz3fq",
"parentPublication": {
"id": "proceedings/icsa-c/2023/6459/0",
"title": "2023 IEEE 20th International Conference on Software Architecture Companion (ICSA-C)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/re/2019/3912/0/391200a028",
"title": "Learning Requirements Elicitation Interviews with Role-Playing, Self-Assessment and Peer-Review",
"doi": null,
"abstractUrl": "/proceedings-article/re/2019/391200a028/1fHltothp6w",
"parentPublication": {
"id": "proceedings/re/2019/3912/0",
"title": "2019 IEEE 27th International Requirements Engineering Conference (RE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1MBDbXf1UXe",
"title": "2023 IEEE 20th International Conference on Software Architecture Companion (ICSA-C)",
"acronym": "icsa-c",
"groupId": "10092530",
"volume": "0",
"displayVolume": "0",
"year": "2023",
"__typename": "ProceedingType"
},
"article": {
"id": "1MBDgupz3fq",
"doi": "10.1109/ICSA-C57050.2023.00045",
"title": "Role-playing software architecture styles",
"normalizedTitle": "Role-playing software architecture styles",
"abstract": "Software Architecture, from definition to maintenance and evolution, is a complex aspect of software development and, consequently, a challenging subject when it comes to teaching it, and learning it.Many research efforts have been devoted to designing teaching approaches, strategies and tools. Most of them, however, focus on the knowledge itself and the ways to convey it to students, rather than on the different learning styles of students themselves.Teaching methods which predominantly rely on verbal and written communication, are very well aligned with some learning styles. However, students with learning styles that benefit more from physical activity or first-hand experience, need to defer to cognitive processes that are less natural to them.In this work, we propose an innovative use of role-playing as teaching strategy for architecture models of reference (i.e. layered, pipe & filter, client-server, etc.). This role-playing of different software architectures, in which students play the part of specific components in the system, intends to complement other classical teaching materials, such as in-person or recorded lectures, lab assignments, or development projects.Addressing all learning styles within a classroom is key to ensure that we favour and foster the students’ different learning processes, and give everyone an even playfield in which to best develop their capabilities as Software Architects.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Software Architecture, from definition to maintenance and evolution, is a complex aspect of software development and, consequently, a challenging subject when it comes to teaching it, and learning it.Many research efforts have been devoted to designing teaching approaches, strategies and tools. Most of them, however, focus on the knowledge itself and the ways to convey it to students, rather than on the different learning styles of students themselves.Teaching methods which predominantly rely on verbal and written communication, are very well aligned with some learning styles. However, students with learning styles that benefit more from physical activity or first-hand experience, need to defer to cognitive processes that are less natural to them.In this work, we propose an innovative use of role-playing as teaching strategy for architecture models of reference (i.e. layered, pipe & filter, client-server, etc.). This role-playing of different software architectures, in which students play the part of specific components in the system, intends to complement other classical teaching materials, such as in-person or recorded lectures, lab assignments, or development projects.Addressing all learning styles within a classroom is key to ensure that we favour and foster the students’ different learning processes, and give everyone an even playfield in which to best develop their capabilities as Software Architects.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Software Architecture, from definition to maintenance and evolution, is a complex aspect of software development and, consequently, a challenging subject when it comes to teaching it, and learning it.Many research efforts have been devoted to designing teaching approaches, strategies and tools. Most of them, however, focus on the knowledge itself and the ways to convey it to students, rather than on the different learning styles of students themselves.Teaching methods which predominantly rely on verbal and written communication, are very well aligned with some learning styles. However, students with learning styles that benefit more from physical activity or first-hand experience, need to defer to cognitive processes that are less natural to them.In this work, we propose an innovative use of role-playing as teaching strategy for architecture models of reference (i.e. layered, pipe & filter, client-server, etc.). This role-playing of different software architectures, in which students play the part of specific components in the system, intends to complement other classical teaching materials, such as in-person or recorded lectures, lab assignments, or development projects.Addressing all learning styles within a classroom is key to ensure that we favour and foster the students’ different learning processes, and give everyone an even playfield in which to best develop their capabilities as Software Architects.",
"fno": "645900a171",
"keywords": [
"Software Architecture",
"Cognitive Processes",
"Education",
"Computer Architecture",
"Games",
"Maintenance Engineering",
"Software",
"Learning Styles",
"Role Playing",
"Software Architecture Models"
],
"authors": [
{
"affiliation": "Universidade da Coruña,Centro de Investigación en TIC (CITIC),A Coruña,Spain",
"fullName": "Laura M. Castro",
"givenName": "Laura M.",
"surname": "Castro",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icsa-c",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2023-03-01T00:00:00",
"pubType": "proceedings",
"pages": "171-174",
"year": "2023",
"issn": null,
"isbn": "978-1-6654-6459-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "645900a167",
"articleId": "1MBDcf5cIQE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "645900a175",
"articleId": "1MBDi1VAjXq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/fie/1998/4762/2/00738799",
"title": "Comparison of teaching styles in chemical engineering",
"doi": null,
"abstractUrl": "/proceedings-article/fie/1998/00738799/12OmNAs2tpW",
"parentPublication": {
"id": "proceedings/fie/1998/4762/2",
"title": "FIE '98. 28th Annual Frontiers in Education Conference. Moving from 'Teacher-Centered' to 'Learner-Centered' Education. Conference Proceedings (Cat. No.98CH36214)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/latice/2014/3592/0/3592a311",
"title": "Effect of Educational Software on Students' Achievement Based on Cognitive Styles",
"doi": null,
"abstractUrl": "/proceedings-article/latice/2014/3592a311/12OmNBgz4z8",
"parentPublication": {
"id": "proceedings/latice/2014/3592/0",
"title": "2014 International Conference on Teaching and Learning in Computing and Engineering (LaTiCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2008/1969/0/04720326",
"title": "Teaching and learning styles in engineering education",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2008/04720326/12OmNqN6R7D",
"parentPublication": {
"id": "proceedings/fie/2008/1969/0",
"title": "2008 38th Annual Frontiers in Education Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2016/9041/0/9041a148",
"title": "Teaching STEM through a Role-Playing Serious Game and Intelligent Pedagogical Agents",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2016/9041a148/12OmNwpGgN1",
"parentPublication": {
"id": "proceedings/icalt/2016/9041/0",
"title": "2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fie/2003/7961/3/01265916",
"title": "New questions about learning styles",
"doi": null,
"abstractUrl": "/proceedings-article/fie/2003/01265916/12OmNxUv6dJ",
"parentPublication": {
"id": "proceedings/fie/2003/7961/3",
"title": "33rd Annual Frontiers in Education, 2003. FIE 2003.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/reet/2010/8786/0/05633115",
"title": "Experiences of using role playing andwiki in requirements engineering course projects",
"doi": null,
"abstractUrl": "/proceedings-article/reet/2010/05633115/12OmNzX6cge",
"parentPublication": {
"id": "proceedings/reet/2010/8786/0",
"title": "2010 5th International Workshop on Requirements Engineering Education and Training (REET 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cseet/2012/1592/0/06245003",
"title": "A Role-Playing Game for a Software Engineering Lab: Developing a Product Line",
"doi": null,
"abstractUrl": "/proceedings-article/cseet/2012/06245003/12OmNzhnagd",
"parentPublication": {
"id": "proceedings/cseet/2012/1592/0",
"title": "2012 IEEE 25th Conference on Software Engineering Education and Training (CSEE&T)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csci/2019/5584/0/558400a880",
"title": "Which Styles of Teaching and Learning Are Effective for Students? – Students' Perspective",
"doi": null,
"abstractUrl": "/proceedings-article/csci/2019/558400a880/1jdDVGvp9Oo",
"parentPublication": {
"id": "proceedings/csci/2019/5584/0",
"title": "2019 International Conference on Computational Science and Computational Intelligence (CSCI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsme/2020/5619/0/561900a692",
"title": "Regression Testing of Massively Multiplayer Online Role-Playing Games",
"doi": null,
"abstractUrl": "/proceedings-article/icsme/2020/561900a692/1oqKNobL9i8",
"parentPublication": {
"id": "proceedings/icsme/2020/5619/0",
"title": "2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icise/2020/2261/0/226100a013",
"title": "Teaching exploration of piano playing and singing based on big data analysis",
"doi": null,
"abstractUrl": "/proceedings-article/icise/2020/226100a013/1tnYhwwnzAQ",
"parentPublication": {
"id": "proceedings/icise/2020/2261/0",
"title": "2020 International Conference on Information Science and Education (ICISE-IE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNwJPMXl",
"title": "2012 IEEE International Conference on Bioinformatics and Biomedicine",
"acronym": "bibm",
"groupId": "1001586",
"volume": "0",
"displayVolume": "0",
"year": "2012",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyFU75f",
"doi": "10.1109/BIBM.2012.6392671",
"title": "iSimp: A sentence simplification system for biomedicail text",
"normalizedTitle": "iSimp: A sentence simplification system for biomedicail text",
"abstract": "Text mining applications using natural language processing are often confronted with long and complicated sentences. This is observed particularly in the abstracts of scientific articles where authors summarize, in few sentences, the various facts described throughout the manuscript. Being rich in novel and important information, the abstract has been the primary target of biomedicai text mining applications. In this work, we aim to simplify complex sentences in abstracts of biomedicai text so that they can be readily processed by text mining applications. We focus on syntactic constructs that are frequently encountered in the biomedicai literature, such as coordinations, relative clauses, and appositions, with emphasis on their boundary detection. Our approach yielded good detection performance (average F-measure between 86.5% and 92.7%), and aided in improving biomedicai text mining applications, RLIMS-P and RankPref.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Text mining applications using natural language processing are often confronted with long and complicated sentences. This is observed particularly in the abstracts of scientific articles where authors summarize, in few sentences, the various facts described throughout the manuscript. Being rich in novel and important information, the abstract has been the primary target of biomedicai text mining applications. In this work, we aim to simplify complex sentences in abstracts of biomedicai text so that they can be readily processed by text mining applications. We focus on syntactic constructs that are frequently encountered in the biomedicai literature, such as coordinations, relative clauses, and appositions, with emphasis on their boundary detection. Our approach yielded good detection performance (average F-measure between 86.5% and 92.7%), and aided in improving biomedicai text mining applications, RLIMS-P and RankPref.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Text mining applications using natural language processing are often confronted with long and complicated sentences. This is observed particularly in the abstracts of scientific articles where authors summarize, in few sentences, the various facts described throughout the manuscript. Being rich in novel and important information, the abstract has been the primary target of biomedicai text mining applications. In this work, we aim to simplify complex sentences in abstracts of biomedicai text so that they can be readily processed by text mining applications. We focus on syntactic constructs that are frequently encountered in the biomedicai literature, such as coordinations, relative clauses, and appositions, with emphasis on their boundary detection. Our approach yielded good detection performance (average F-measure between 86.5% and 92.7%), and aided in improving biomedicai text mining applications, RLIMS-P and RankPref.",
"fno": "06392671",
"keywords": [
"Text Mining",
"Sentence Simplification",
"Information Extraction",
"Natural Language Processing"
],
"authors": [
{
"affiliation": "Computer & Information Sciences, University of Delaware, Newark, DE",
"fullName": "Yifan Peng",
"givenName": "Yifan",
"surname": "Peng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computer & Information Sciences, University of Delaware, Newark, DE",
"fullName": "Catalina O. Tudor",
"givenName": "Catalina O.",
"surname": "Tudor",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computer & Information Sciences, University of Delaware, Newark, DE",
"fullName": "Manabu Torii",
"givenName": "Manabu",
"surname": "Torii",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computer & Information Sciences, University of Delaware, Newark, DE",
"fullName": "Cathy H. Wu",
"givenName": "Cathy H.",
"surname": "Wu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Computer & Information Sciences, University of Delaware, Newark, DE",
"fullName": "K. Vijay-Shanker",
"givenName": "K.",
"surname": "Vijay-Shanker",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2012-10-01T00:00:00",
"pubType": "proceedings",
"pages": "1-6",
"year": "2012",
"issn": null,
"isbn": "978-1-4673-2559-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06392670",
"articleId": "12OmNBtUdNY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06392672",
"articleId": "12OmNz61cUQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ichi/2018/5377/0/537701a374",
"title": "Analyzing Patterns of Literature-Based Phenotyping Definitions for Text Mining Applications",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2018/537701a374/12OmNAle6QX",
"parentPublication": {
"id": "proceedings/ichi/2018/5377/0",
"title": "2018 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bracis/2017/2407/0/2407a342",
"title": "Statistical and Semantic Features to Measure Sentence Similarity in Portuguese",
"doi": null,
"abstractUrl": "/proceedings-article/bracis/2017/2407a342/12OmNBNM8TW",
"parentPublication": {
"id": "proceedings/bracis/2017/2407/0",
"title": "2017 Brazilian Conference on Intelligent Systems (BRACIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2011/4584/0/4584a427",
"title": "A Topic Partition Algorithm Based on Average Sentence Similarity for Interactive Text",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2011/4584a427/12OmNCd2rMB",
"parentPublication": {
"id": "proceedings/cis/2011/4584/0",
"title": "2011 Seventh International Conference on Computational Intelligence and Security",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/his/2009/3745/1/3745a142",
"title": "Sentence Features Fusion for Text Summarization Using Fuzzy Logic",
"doi": null,
"abstractUrl": "/proceedings-article/his/2009/3745a142/12OmNCm7BGy",
"parentPublication": {
"id": "proceedings/his/2009/3745/1",
"title": "Hybrid Intelligent Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ialp/2011/4554/0/4554a276",
"title": "Building a Rule-Based Malay Text Segmentation Tool",
"doi": null,
"abstractUrl": "/proceedings-article/ialp/2011/4554a276/12OmNvUaNnr",
"parentPublication": {
"id": "proceedings/ialp/2011/4554/0",
"title": "Asian Language Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hisb/2011/4407/0/4407a089",
"title": "Knowledge Discovery and Data Mining of Free Text Radiology Reports",
"doi": null,
"abstractUrl": "/proceedings-article/hisb/2011/4407a089/12OmNwErpXw",
"parentPublication": {
"id": "proceedings/hisb/2011/4407/0",
"title": "Healthcare Informatics, Imaging and Systems Biology, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2010/4257/0/4257b114",
"title": "Sentence-Level and Document-Level Sentiment Mining for Arabic Texts",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2010/4257b114/12OmNzBOhTn",
"parentPublication": {
"id": "proceedings/icdmw/2010/4257/0",
"title": "2010 IEEE International Conference on Data Mining Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ialp/2011/4554/0/4554a030",
"title": "Sentence Boundary Detection in Colloquial Arabic Text: A Preliminary Result",
"doi": null,
"abstractUrl": "/proceedings-article/ialp/2011/4554a030/12OmNzUgd7k",
"parentPublication": {
"id": "proceedings/ialp/2011/4554/0",
"title": "Asian Language Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fskd/2008/3305/4/3305d140",
"title": "A Practical Approach for Relevance Measure of Inter-sentence",
"doi": null,
"abstractUrl": "/proceedings-article/fskd/2008/3305d140/12OmNzX6cp7",
"parentPublication": {
"id": "proceedings/fskd/2008/3305/4",
"title": "Fuzzy Systems and Knowledge Discovery, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2006/08/k1138",
"title": "Sentence Similarity Based on Semantic Nets and Corpus Statistics",
"doi": null,
"abstractUrl": "/journal/tk/2006/08/k1138/13rRUxCitJD",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1AH7K6dctEI",
"title": "2021 International Conference on Information Technology and Biomedical Engineering (ICITBE)",
"acronym": "icitbe",
"groupId": "1845444",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1AH7MM9a012",
"doi": "10.1109/ICITBE54178.2021.00017",
"title": "A Text Classification Method Based on Graph Attention Networks",
"normalizedTitle": "A Text Classification Method Based on Graph Attention Networks",
"abstract": "With the rapid generation and dissemination of information data in modern society, intelligent processing of text classification is becoming more and more important. The Sequential and Graph-based deep learning models are often used in Natural Language Processing (NLP). The Sequential model usually uses Recurrent Neural Network (RNN), Convolutional Neural Network (CNN) and Bidirectional Encoder Representations from Transformers (BERT) The model performs natural language processing. The graph-based depth model uses the Co-occurrence relationship between texts to learn the characteristics of texts and texts for classification. In this paper, we use RNN to preliminarily calculate the features in the text as the node of the graph, construct a graph with the help of the modification relationship between texts, and then use the graph model to obtain the final text features used to predict the text category. The experiment was compared with a variety of methods through a variety of data sets, and the results showed that the method in this paper achieved better results on the text data set used for emotion classification, and the accuracy rate reached 82.03%.",
"abstracts": [
{
"abstractType": "Regular",
"content": "With the rapid generation and dissemination of information data in modern society, intelligent processing of text classification is becoming more and more important. The Sequential and Graph-based deep learning models are often used in Natural Language Processing (NLP). The Sequential model usually uses Recurrent Neural Network (RNN), Convolutional Neural Network (CNN) and Bidirectional Encoder Representations from Transformers (BERT) The model performs natural language processing. The graph-based depth model uses the Co-occurrence relationship between texts to learn the characteristics of texts and texts for classification. In this paper, we use RNN to preliminarily calculate the features in the text as the node of the graph, construct a graph with the help of the modification relationship between texts, and then use the graph model to obtain the final text features used to predict the text category. The experiment was compared with a variety of methods through a variety of data sets, and the results showed that the method in this paper achieved better results on the text data set used for emotion classification, and the accuracy rate reached 82.03%.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "With the rapid generation and dissemination of information data in modern society, intelligent processing of text classification is becoming more and more important. The Sequential and Graph-based deep learning models are often used in Natural Language Processing (NLP). The Sequential model usually uses Recurrent Neural Network (RNN), Convolutional Neural Network (CNN) and Bidirectional Encoder Representations from Transformers (BERT) The model performs natural language processing. The graph-based depth model uses the Co-occurrence relationship between texts to learn the characteristics of texts and texts for classification. In this paper, we use RNN to preliminarily calculate the features in the text as the node of the graph, construct a graph with the help of the modification relationship between texts, and then use the graph model to obtain the final text features used to predict the text category. The experiment was compared with a variety of methods through a variety of data sets, and the results showed that the method in this paper achieved better results on the text data set used for emotion classification, and the accuracy rate reached 82.03%.",
"fno": "009900a035",
"keywords": [
"Graph Theory",
"Learning Artificial Intelligence",
"Natural Language Processing",
"Neural Nets",
"Pattern Classification",
"Recurrent Neural Nets",
"Text Analysis",
"Rapid Generation",
"Information Data",
"Intelligent Processing",
"Sequential Graph",
"Natural Language Processing",
"Sequential Model",
"Recurrent Neural Network",
"RNN",
"Convolutional Neural Network",
"Bidirectional Encoder Representations",
"Graph Based Depth Model",
"Graph Model",
"Final Text Features",
"Text Category",
"Text Data",
"Emotion Classification",
"Text Classification Method",
"Graph Attention Networks",
"Deep Learning",
"Recurrent Neural Networks",
"Text Categorization",
"Bit Error Rate",
"Predictive Models",
"Transformers",
"Natural Language Processing",
"Graph Attention Networks",
"Natural Language Processing",
"Text Classification"
],
"authors": [
{
"affiliation": "Lingnan Normal University,School of Computer and Intelligence Education,Zhanjiang,P.R. China,524048",
"fullName": "Yong Liu",
"givenName": "Yong",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xiamen University,Software School,Xiamen Fujian,P.R. China,361005",
"fullName": "Xiangnan Gou",
"givenName": "Xiangnan",
"surname": "Gou",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icitbe",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-12-01T00:00:00",
"pubType": "proceedings",
"pages": "35-39",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-0099-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "009900a030",
"articleId": "1AH7YrM4VWg",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "009900a040",
"articleId": "1AH7LO7hAv6",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icece/2010/4031/0/4031b092",
"title": "Graph-Based Chinese Text Categorization",
"doi": null,
"abstractUrl": "/proceedings-article/icece/2010/4031b092/12OmNwwd304",
"parentPublication": {
"id": "proceedings/icece/2010/4031/0",
"title": "Electrical and Control Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icbk/2021/3858/0/385800a462",
"title": "A Character-Word Graph Attention Networks for Chinese Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icbk/2021/385800a462/1A9X4N5ktag",
"parentPublication": {
"id": "proceedings/icbk/2021/3858/0",
"title": "2021 IEEE International Conference on Big Knowledge (ICBK)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccnea/2022/9109/0/910900a189",
"title": "Research on Semi-Supervised Text Classification Based on Graph Attention Network",
"doi": null,
"abstractUrl": "/proceedings-article/iccnea/2022/910900a189/1HYvc1gZgyc",
"parentPublication": {
"id": "proceedings/iccnea/2022/9109/0",
"title": "2022 International Conference on Computer Network, Electronic and Automation (ICCNEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ithings-greencom-cpscom-smartdata-cybermatics/2022/5417/0/541700a495",
"title": "UA-HGAT: Uncertainty-aware Heterogeneous Graph Attention Network for Short Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/ithings-greencom-cpscom-smartdata-cybermatics/2022/541700a495/1HcmWQ95IRi",
"parentPublication": {
"id": "proceedings/ithings-greencom-cpscom-smartdata-cybermatics/2022/5417/0",
"title": "2022 IEEE International Conferences on Internet of Things (iThings) and IEEE Green Computing & Communications (GreenCom) and IEEE Cyber, Physical & Social Computing (CPSCom) and IEEE Smart Data (SmartData) and IEEE Congress on Cybermatics (Cybermatics)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2019/6092/0/609200a277",
"title": "Text Classification Method Based on Co-Occurrence Events",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2019/609200a277/1i5m5m7eVna",
"parentPublication": {
"id": "proceedings/cis/2019/6092/0",
"title": "2019 15th International Conference on Computational Intelligence and Security (CIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsc/2021/8899/0/889900a183",
"title": "A Comparative Study of Deep Neural Network Models on Multi-Label Text Classification in Finance",
"doi": null,
"abstractUrl": "/proceedings-article/icsc/2021/889900a183/1rFzTzHTccg",
"parentPublication": {
"id": "proceedings/icsc/2021/8899/0",
"title": "2021 IEEE 15th International Conference on Semantic Computing (ICSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09413086",
"title": "Label Incorporated Graph Neural Networks for Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09413086/1tmiopNVavK",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icise/2020/2261/0/226100a064",
"title": "A general evaluation method of university curriculum summative text based on optimized BERT model",
"doi": null,
"abstractUrl": "/proceedings-article/icise/2020/226100a064/1tnYewq31gk",
"parentPublication": {
"id": "proceedings/icise/2020/2261/0",
"title": "2020 International Conference on Information Science and Education (ICISE-IE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/caibda/2021/2490/0/249000a137",
"title": "News text classification based on Bidirectional Encoder Representation from Transformers",
"doi": null,
"abstractUrl": "/proceedings-article/caibda/2021/249000a137/1xgBpSxuhri",
"parentPublication": {
"id": "proceedings/caibda/2021/2490/0",
"title": "2021 International Conference on Artificial Intelligence, Big Data and Algorithms (CAIBDA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icceai/2021/3960/0/396000a230",
"title": "A comparative study of deep learning approaches for Chinese Sentence Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icceai/2021/396000a230/1xqyGNeIMyA",
"parentPublication": {
"id": "proceedings/icceai/2021/3960/0",
"title": "2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1FUUlAQhJwk",
"title": "2022 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)",
"acronym": "icceai",
"groupId": "1843184",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1FUVO1IgtPi",
"doi": "10.1109/ICCEAI55464.2022.00090",
"title": "Text Semantic Representation Based on Knowledge Graph Correction",
"normalizedTitle": "Text Semantic Representation Based on Knowledge Graph Correction",
"abstract": "Text semantic representation is the foundation of natural language processing tasks. Most existing text representation methods are based on the bag-of-words model to represent text composition. However, they ignore the textual semantics of phrases, which affects the performance of downstream natural language processing tasks. In this paper, we propose a Text Semantic Representation Method Based on Knowledge Graph Correction, called TRKGC. Firstly, we adopt PCFG and CKY methods to construct the parsing tree in units of sentences. Secondly, we traverse the parse tree according to the idea of hierarchical traversal to get the phrase representation of texts. Finally, we utilize the knowledge graph to correct text representation and improve text representation semantics. Extensive experiments on text classification and text clustering demonstrate that TRKGC outperforms baseline methods in terms of text semantic representation.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Text semantic representation is the foundation of natural language processing tasks. Most existing text representation methods are based on the bag-of-words model to represent text composition. However, they ignore the textual semantics of phrases, which affects the performance of downstream natural language processing tasks. In this paper, we propose a Text Semantic Representation Method Based on Knowledge Graph Correction, called TRKGC. Firstly, we adopt PCFG and CKY methods to construct the parsing tree in units of sentences. Secondly, we traverse the parse tree according to the idea of hierarchical traversal to get the phrase representation of texts. Finally, we utilize the knowledge graph to correct text representation and improve text representation semantics. Extensive experiments on text classification and text clustering demonstrate that TRKGC outperforms baseline methods in terms of text semantic representation.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Text semantic representation is the foundation of natural language processing tasks. Most existing text representation methods are based on the bag-of-words model to represent text composition. However, they ignore the textual semantics of phrases, which affects the performance of downstream natural language processing tasks. In this paper, we propose a Text Semantic Representation Method Based on Knowledge Graph Correction, called TRKGC. Firstly, we adopt PCFG and CKY methods to construct the parsing tree in units of sentences. Secondly, we traverse the parse tree according to the idea of hierarchical traversal to get the phrase representation of texts. Finally, we utilize the knowledge graph to correct text representation and improve text representation semantics. Extensive experiments on text classification and text clustering demonstrate that TRKGC outperforms baseline methods in terms of text semantic representation.",
"fno": "680300a404",
"keywords": [
"Graph Theory",
"Natural Language Processing",
"Pattern Clustering",
"Text Analysis",
"Word Processing",
"Text Composition",
"Downstream Natural Language Processing Tasks",
"Text Representation Semantics",
"Text Classification",
"Text Clustering",
"Text Semantic Representation Method",
"Knowledge Graph Correction",
"Text Representation Methods",
"Semantics",
"Text Categorization",
"Syntactics",
"Natural Language Processing",
"Task Analysis",
"Artificial Intelligence",
"Phrase Mining",
"Text Semantic Representation",
"Parsing",
"Knowledge Graph"
],
"authors": [
{
"affiliation": "School of Information Science and Technology, Shijiazhuang Tiedao University,Shijiazhuang,China,050043",
"fullName": "Yongliang Wu",
"givenName": "Yongliang",
"surname": "Wu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Information Science and Technology, Shijiazhuang Tiedao University,Shijiazhuang,China,050043",
"fullName": "Hu Yin",
"givenName": "Hu",
"surname": "Yin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Information Science and Technology, Shijiazhuang Tiedao University,Shijiazhuang,China,050043",
"fullName": "Dongbo Liu",
"givenName": "Dongbo",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Information Science and Technology, Shijiazhuang Tiedao University,Shijiazhuang,China,050043",
"fullName": "Qianqian Zhou",
"givenName": "Qianqian",
"surname": "Zhou",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icceai",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-07-01T00:00:00",
"pubType": "proceedings",
"pages": "404-408",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6803-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "680300a400",
"articleId": "1FUVLa4uDS0",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "680300a409",
"articleId": "1FUVLMJlwcM",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/hicss/1994/5090/4/00323416",
"title": "The semantic vector space model (SVSM): a text representation and searching technique",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/1994/00323416/12OmNsd6vht",
"parentPublication": {
"id": "proceedings/hicss/1994/5090/4",
"title": "Proceedings of the Twenty-Seventh Annual Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2012/2216/0/06460158",
"title": "Non-negative Sparse Semantic Coding for text categorization",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460158/12OmNx6g6oR",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/snpd/2016/2239/0/07515879",
"title": "Document representation based on semantic smoothed topic model",
"doi": null,
"abstractUrl": "/proceedings-article/snpd/2016/07515879/12OmNxu6p8P",
"parentPublication": {
"id": "proceedings/snpd/2016/2239/0",
"title": "2016 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2013/05/ttb2013051211",
"title": "Text Categorization of Biomedical Data Sets Using Graph Kernels and a Controlled Vocabulary",
"doi": null,
"abstractUrl": "/journal/tb/2013/05/ttb2013051211/13rRUyfbwpe",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsc/2019/6783/0/08665592",
"title": "Graph-Based Semantic Learning, Representation and Growth from Text: A Systematic Review",
"doi": null,
"abstractUrl": "/proceedings-article/icsc/2019/08665592/18qceKSYYwg",
"parentPublication": {
"id": "proceedings/icsc/2019/6783/0",
"title": "2019 IEEE 13th International Conference on Semantic Computing (ICSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictech/2022/9694/0/969400a394",
"title": "Text Classification Using BiGRU with Directional Self-Attention",
"doi": null,
"abstractUrl": "/proceedings-article/ictech/2022/969400a394/1FWmC7MfyOQ",
"parentPublication": {
"id": "proceedings/ictech/2022/9694/0",
"title": "2022 11th International Conference of Information and Communication Technology (ICTech)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icnlp/2022/9544/0/954400a420",
"title": "Graph Convolutional Networks for Fast Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icnlp/2022/954400a420/1GNtp6dDqRG",
"parentPublication": {
"id": "proceedings/icnlp/2022/9544/0",
"title": "2022 4th International Conference on Natural Language Processing (ICNLP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccnea/2022/9109/0/910900a189",
"title": "Research on Semi-Supervised Text Classification Based on Graph Attention Network",
"doi": null,
"abstractUrl": "/proceedings-article/iccnea/2022/910900a189/1HYvc1gZgyc",
"parentPublication": {
"id": "proceedings/iccnea/2022/9109/0",
"title": "2022 International Conference on Computer Network, Electronic and Automation (ICCNEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/ex/5555/01/10105905",
"title": "DCAT: Combining Multi-semantic Dual-channel Attention Fusion for Text Classification",
"doi": null,
"abstractUrl": "/magazine/ex/5555/01/10105905/1MtgtjkU8qQ",
"parentPublication": {
"id": "mags/ex",
"title": "IEEE Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09413086",
"title": "Label Incorporated Graph Neural Networks for Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09413086/1tmiopNVavK",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1GNtgmAqRB6",
"title": "2022 4th International Conference on Natural Language Processing (ICNLP)",
"acronym": "icnlp",
"groupId": "1843064",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1GNtp6dDqRG",
"doi": "10.1109/ICNLP55136.2022.00078",
"title": "Graph Convolutional Networks for Fast Text Classification",
"normalizedTitle": "Graph Convolutional Networks for Fast Text Classification",
"abstract": "Recently, lots of studies have explored text classification methods based on graph convolutional neural network (GCN) technology. Compared with traditional deep learning methods, graph convolutional neural networks can capture global information while processing complex graph-structured data. However, when the previous GCN method deals with text classification problems, the entire corpus is often constructed as a complex heterogeneous graph. Such a graph structure faces the problems of the huge amount of calculation and long network training time when learning text representation. To solve the above problems, we simplified the construction of the adjacency matrix of the text heterogeneous graph based on Text GCN to reduce the amount of calculation during training. In addition, by constructing a special feature matrix, the graph convolutional neural network can extract a better text representation during training, while reducing the dimension of the feature matrix. The model performs text classification tasks on three data sets of R8, R52, and Ohsumed. The results show that the training speed of the proposed model on the three data sets of R8, R52, and Ohsumed is improved compared with the benchmark method (Text GCN) 71.5%, 72.6%, 78.6%. At the same time, the proposed model achieves an accuracy comparable to Text GCN on three data sets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recently, lots of studies have explored text classification methods based on graph convolutional neural network (GCN) technology. Compared with traditional deep learning methods, graph convolutional neural networks can capture global information while processing complex graph-structured data. However, when the previous GCN method deals with text classification problems, the entire corpus is often constructed as a complex heterogeneous graph. Such a graph structure faces the problems of the huge amount of calculation and long network training time when learning text representation. To solve the above problems, we simplified the construction of the adjacency matrix of the text heterogeneous graph based on Text GCN to reduce the amount of calculation during training. In addition, by constructing a special feature matrix, the graph convolutional neural network can extract a better text representation during training, while reducing the dimension of the feature matrix. The model performs text classification tasks on three data sets of R8, R52, and Ohsumed. The results show that the training speed of the proposed model on the three data sets of R8, R52, and Ohsumed is improved compared with the benchmark method (Text GCN) 71.5%, 72.6%, 78.6%. At the same time, the proposed model achieves an accuracy comparable to Text GCN on three data sets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recently, lots of studies have explored text classification methods based on graph convolutional neural network (GCN) technology. Compared with traditional deep learning methods, graph convolutional neural networks can capture global information while processing complex graph-structured data. However, when the previous GCN method deals with text classification problems, the entire corpus is often constructed as a complex heterogeneous graph. Such a graph structure faces the problems of the huge amount of calculation and long network training time when learning text representation. To solve the above problems, we simplified the construction of the adjacency matrix of the text heterogeneous graph based on Text GCN to reduce the amount of calculation during training. In addition, by constructing a special feature matrix, the graph convolutional neural network can extract a better text representation during training, while reducing the dimension of the feature matrix. The model performs text classification tasks on three data sets of R8, R52, and Ohsumed. The results show that the training speed of the proposed model on the three data sets of R8, R52, and Ohsumed is improved compared with the benchmark method (Text GCN) 71.5%, 72.6%, 78.6%. At the same time, the proposed model achieves an accuracy comparable to Text GCN on three data sets.",
"fno": "954400a420",
"keywords": [
"Graph Theory",
"Learning Artificial Intelligence",
"Neural Nets",
"Pattern Classification",
"Text Analysis",
"Benchmark Method 71",
"Complex Graph Structured Data",
"Complex Heterogeneous Graph",
"Data Sets",
"Fast Text Classification",
"Graph Convolutional Networks",
"Graph Convolutional Neural Network Technology",
"Graph Structure",
"Learning Text Representation",
"Long Network Training Time",
"Previous GCN Method",
"Text Classification Methods",
"Text Classification Problems",
"Text Classification Tasks",
"Text GCN",
"Text Heterogeneous Graph",
"Traditional Deep Learning Methods",
"Training",
"Deep Learning",
"Computational Modeling",
"Text Categorization",
"Feature Extraction",
"Data Models",
"Natural Language Processing",
"GCN",
"Data Of Graph Structure",
"Feature Representation",
"Text Graph"
],
"authors": [
{
"affiliation": "Xi’an University of Posts and Telecommunications,School of Communication and Information Engineering,Xi’an,China,710121",
"fullName": "Houyv Cai",
"givenName": "Houyv",
"surname": "Cai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xi’an University of Posts and Telecommunications,School of Communication and Information Engineering,Xi’an,China,710121",
"fullName": "Shaoqing Lv",
"givenName": "Shaoqing",
"surname": "Lv",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xi’an University of Posts and Telecommunications,School of Communication and Information Engineering,Xi’an,China,710121",
"fullName": "Guangyue Lu",
"givenName": "Guangyue",
"surname": "Lu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xi’an University of Posts and Telecommunications,School of Communication and Information Engineering,Xi’an,China,710121",
"fullName": "Tingting Li",
"givenName": "Tingting",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icnlp",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-03-01T00:00:00",
"pubType": "proceedings",
"pages": "420-425",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-9544-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "954400a414",
"articleId": "1GNtlhtTlVC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "954400a426",
"articleId": "1GNtix2kWrK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2021/0126/0/09669286",
"title": "Knowledge Graph Integrated Graph Neural Networks for Chinese Medical Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669286/1A9VRXQcy0U",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icbk/2021/3858/0/385800a462",
"title": "A Character-Word Graph Attention Networks for Chinese Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icbk/2021/385800a462/1A9X4N5ktag",
"parentPublication": {
"id": "proceedings/icbk/2021/3858/0",
"title": "2021 IEEE International Conference on Big Knowledge (ICBK)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icitbe/2021/0099/0/009900a035",
"title": "A Text Classification Method Based on Graph Attention Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icitbe/2021/009900a035/1AH7MM9a012",
"parentPublication": {
"id": "proceedings/icitbe/2021/0099/0",
"title": "2021 International Conference on Information Technology and Biomedical Engineering (ICITBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/nlbse/2022/9343/0/934300a075",
"title": "Story Point Level Classification by Text Level Graph Neural Network",
"doi": null,
"abstractUrl": "/proceedings-article/nlbse/2022/934300a075/1ED23LhdCk8",
"parentPublication": {
"id": "proceedings/nlbse/2022/9343/0",
"title": "2022 IEEE/ACM 1st International Workshop on Natural Language-Based Software Engineering (NLBSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccnea/2022/9109/0/910900a189",
"title": "Research on Semi-Supervised Text Classification Based on Graph Attention Network",
"doi": null,
"abstractUrl": "/proceedings-article/iccnea/2022/910900a189/1HYvc1gZgyc",
"parentPublication": {
"id": "proceedings/iccnea/2022/9109/0",
"title": "2022 International Conference on Computer Network, Electronic and Automation (ICCNEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2022/9062/0/09956075",
"title": "InducT-GCN: Inductive Graph Convolutional Networks for Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2022/09956075/1IHq5LYns8U",
"parentPublication": {
"id": "proceedings/icpr/2022/9062/0",
"title": "2022 26th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2022/9744/0/974400a297",
"title": "KPE-GCN: A Keyphrase-Enhanced Graph Convolutional Network for Imbalanced Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2022/974400a297/1MrG3opNQ1G",
"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/icpr/2021/8808/0/09411914",
"title": "Zero-Shot Text Classification with Semantically Extended Graph Convolutional Network",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09411914/1tmhiDu00Jq",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09413086",
"title": "Label Incorporated Graph Neural Networks for Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09413086/1tmiopNVavK",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ieit/2021/2563/0/256300a102",
"title": "Text Classification Study Based on Graph Convolutional Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/ieit/2021/256300a102/1wHKudLBDMs",
"parentPublication": {
"id": "proceedings/ieit/2021/2563/0",
"title": "2021 International Conference on Internet, Education and Information Technology (IEIT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1cI5QHMCbVm",
"title": "2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks – Supplemental Volume (DSN-S)",
"acronym": "dsn-s",
"groupId": "1832724",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1cI5RM2ftcY",
"doi": "10.1109/DSN-S.2019.00018",
"title": "Towards a Bayesian Approach for Assessing Fault Tolerance of Deep Neural Networks",
"normalizedTitle": "Towards a Bayesian Approach for Assessing Fault Tolerance of Deep Neural Networks",
"abstract": "This paper presents Bayesian Deep Learning based Fault Injection (BDLFI), a novel methodology for fault injection in neural networks (NNs) and more generally differentiable programs. BDLFI uses (1) Bayesian Deep Learning to model the propagation of faults, and (2) Markov Chain Monte Carlo inference to quantify the effect of faults on the outputs of a NN. We demonstrate BDLFI on two representative networks and present our results that challenge pre-existing results in the field.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents Bayesian Deep Learning based Fault Injection (BDLFI), a novel methodology for fault injection in neural networks (NNs) and more generally differentiable programs. BDLFI uses (1) Bayesian Deep Learning to model the propagation of faults, and (2) Markov Chain Monte Carlo inference to quantify the effect of faults on the outputs of a NN. We demonstrate BDLFI on two representative networks and present our results that challenge pre-existing results in the field.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents Bayesian Deep Learning based Fault Injection (BDLFI), a novel methodology for fault injection in neural networks (NNs) and more generally differentiable programs. BDLFI uses (1) Bayesian Deep Learning to model the propagation of faults, and (2) Markov Chain Monte Carlo inference to quantify the effect of faults on the outputs of a NN. We demonstrate BDLFI on two representative networks and present our results that challenge pre-existing results in the field.",
"fno": "302800a025",
"keywords": [
"Bayes Methods",
"Fault Tolerant Computing",
"Learning Artificial Intelligence",
"Markov Processes",
"Monte Carlo Methods",
"Neural Nets",
"Representative Networks",
"Differentiable Programs",
"Fault Tolerance",
"Deep Neural Networks",
"BDLFI",
"Bayesian Deep Learning Based Fault Injection",
"Markov Chain Monte Carlo Inference",
"Bayes Methods",
"Artificial Neural Networks",
"Deep Learning",
"Neurons",
"Markov Processes",
"Monte Carlo Methods",
"Fault Injection",
"Neural Networks"
],
"authors": [
{
"affiliation": "Department of Computer Science",
"fullName": "Subho S. Banerjee",
"givenName": "Subho S.",
"surname": "Banerjee",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Illinois at Urbana-Champaign",
"fullName": "James Cyriac",
"givenName": "James",
"surname": "Cyriac",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Science",
"fullName": "Saurabh Jha",
"givenName": "Saurabh",
"surname": "Jha",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Illinois at Urbana-Champaign",
"fullName": "Zbigniew T. Kalbarczyk",
"givenName": "Zbigniew T.",
"surname": "Kalbarczyk",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Illinois at Urbana-Champaign",
"fullName": "Ravishankar K. Iyer",
"givenName": "Ravishankar K.",
"surname": "Iyer",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "dsn-s",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-06-01T00:00:00",
"pubType": "proceedings",
"pages": "25-26",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-3028-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "302800a023",
"articleId": "1cI5Rlc1hAI",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "302800a027",
"articleId": "1cI5QXWCd56",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/pdp/2018/4975/0/497501a666",
"title": "Implementation of Bayesian Inference In Distributed Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/pdp/2018/497501a666/12OmNBh8gUF",
"parentPublication": {
"id": "proceedings/pdp/2018/4975/0",
"title": "2018 26th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscv/2017/4062/0/08054977",
"title": "Bayesian regularized artificial neural network for fault detection and isolation in wind turbine",
"doi": null,
"abstractUrl": "/proceedings-article/iscv/2017/08054977/12OmNC3FGcn",
"parentPublication": {
"id": "proceedings/iscv/2017/4062/0",
"title": "2017 Intelligent Systems and Computer Vision (ISCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/msn/2015/0329/0/0329a037",
"title": "Fault Detection for Medical Body Sensor Networks Under Bayesian Network Model",
"doi": null,
"abstractUrl": "/proceedings-article/msn/2015/0329a037/12OmNCxL9Rw",
"parentPublication": {
"id": "proceedings/msn/2015/0329/0",
"title": "2015 11th International Conference on Mobile Ad-hoc and Sensor Networks (MSN)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csci/2016/5510/0/07881407",
"title": "Adaptive Task Partitioning for Bayesian Applications",
"doi": null,
"abstractUrl": "/proceedings-article/csci/2016/07881407/12OmNwkzuqY",
"parentPublication": {
"id": "proceedings/csci/2016/5510/0",
"title": "2016 International Conference on Computational Science and Computational Intelligence (CSCI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209d185",
"title": "Pseudo-Marginal Bayesian Multiple-Class Multiple-Kernel Learning for Neuroimaging Data",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209d185/12OmNzWfoV2",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2013/02/ttb2013020494",
"title": "Profile-Based LC-MS Data Alignment - A Bayesian Approach",
"doi": null,
"abstractUrl": "/journal/tb/2013/02/ttb2013020494/13rRUwIF6cx",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2015/06/06920043",
"title": "A Very Simple Safe-Bayesian Random Forest",
"doi": null,
"abstractUrl": "/journal/tp/2015/06/06920043/13rRUwvBya0",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/issre/2021/2587/0/258700a242",
"title": "An Efficient Approximation for Quantitative Analysis of Dynamic Fault Trees",
"doi": null,
"abstractUrl": "/proceedings-article/issre/2021/258700a242/1AUpa0oyFwI",
"parentPublication": {
"id": "proceedings/issre/2021/2587/0",
"title": "2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dsn/2019/0057/0/005700a112",
"title": "ML-Based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection",
"doi": null,
"abstractUrl": "/proceedings-article/dsn/2019/005700a112/1cI6jcg5q6c",
"parentPublication": {
"id": "proceedings/dsn/2019/0057/0",
"title": "2019 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300g300",
"title": "Uncertainty-Aware Audiovisual Activity Recognition Using Deep Bayesian Variational Inference",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300g300/1hVlgMvYDMQ",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1vNjD1dZI9q",
"title": "2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA)",
"acronym": "isca",
"groupId": "1000123",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1vNjIaHwBLq",
"doi": "10.1109/ISCA52012.2021.00060",
"title": "ELSA: Hardware-Software Co-design for Efficient, Lightweight Self-Attention Mechanism in Neural Networks",
"normalizedTitle": "ELSA: Hardware-Software Co-design for Efficient, Lightweight Self-Attention Mechanism in Neural Networks",
"abstract": "The self-attention mechanism is rapidly emerging as one of the most important key primitives in neural networks (NNs) for its ability to identify the relations within input entities. The self-attention-oriented NN models such as Google Transformer and its variants have established the state-of-the-art on a very wide range of natural language processing tasks, and many other self-attention-oriented models are achieving competitive results in computer vision and recommender systems as well. Unfortunately, despite its great benefits, the self-attention mechanism is an expensive operation whose cost increases quadratically with the number of input entities that it processes, and thus accounts for a significant portion of the inference runtime. Thus, this paper presents ELSA (Efficient, Lightweight Self-Attention), a hardware-software co-designed solution to substantially reduce the runtime as well as energy spent on the self-attention mechanism. Specifically, based on the intuition that not all relations are equal, we devise a novel approximation scheme that significantly reduces the amount of computation by efficiently filtering out relations that are unlikely to affect the final output. With the specialized hardware for this approximate self-attention mechanism, ELSA achieves a geomean speedup of 58.1× as well as over three orders of magnitude improvements in energy efficiency compared to GPU on self-attention computation in modern NN models while maintaining less than 1% loss in the accuracy metric.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The self-attention mechanism is rapidly emerging as one of the most important key primitives in neural networks (NNs) for its ability to identify the relations within input entities. The self-attention-oriented NN models such as Google Transformer and its variants have established the state-of-the-art on a very wide range of natural language processing tasks, and many other self-attention-oriented models are achieving competitive results in computer vision and recommender systems as well. Unfortunately, despite its great benefits, the self-attention mechanism is an expensive operation whose cost increases quadratically with the number of input entities that it processes, and thus accounts for a significant portion of the inference runtime. Thus, this paper presents ELSA (Efficient, Lightweight Self-Attention), a hardware-software co-designed solution to substantially reduce the runtime as well as energy spent on the self-attention mechanism. Specifically, based on the intuition that not all relations are equal, we devise a novel approximation scheme that significantly reduces the amount of computation by efficiently filtering out relations that are unlikely to affect the final output. With the specialized hardware for this approximate self-attention mechanism, ELSA achieves a geomean speedup of 58.1× as well as over three orders of magnitude improvements in energy efficiency compared to GPU on self-attention computation in modern NN models while maintaining less than 1% loss in the accuracy metric.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The self-attention mechanism is rapidly emerging as one of the most important key primitives in neural networks (NNs) for its ability to identify the relations within input entities. The self-attention-oriented NN models such as Google Transformer and its variants have established the state-of-the-art on a very wide range of natural language processing tasks, and many other self-attention-oriented models are achieving competitive results in computer vision and recommender systems as well. Unfortunately, despite its great benefits, the self-attention mechanism is an expensive operation whose cost increases quadratically with the number of input entities that it processes, and thus accounts for a significant portion of the inference runtime. Thus, this paper presents ELSA (Efficient, Lightweight Self-Attention), a hardware-software co-designed solution to substantially reduce the runtime as well as energy spent on the self-attention mechanism. Specifically, based on the intuition that not all relations are equal, we devise a novel approximation scheme that significantly reduces the amount of computation by efficiently filtering out relations that are unlikely to affect the final output. With the specialized hardware for this approximate self-attention mechanism, ELSA achieves a geomean speedup of 58.1× as well as over three orders of magnitude improvements in energy efficiency compared to GPU on self-attention computation in modern NN models while maintaining less than 1% loss in the accuracy metric.",
"fno": "333300a692",
"keywords": [
"Computer Vision",
"Hardware Software Codesign",
"Inference Mechanisms",
"Natural Language Processing",
"Neural Nets",
"Recommender Systems",
"Neural Networks",
"Input Entities",
"Self Attention Oriented NN Models",
"Natural Language Processing Tasks",
"Computer Vision",
"Recommender Systems",
"Approximate Self Attention Mechanism",
"ELSA",
"Hardware Software Co Design",
"Lightweight Self Attention Mechanism",
"Key Primitives",
"Inference Runtime",
"Runtime",
"Computational Modeling",
"Graphics Processing Units",
"Artificial Neural Networks",
"Hardware",
"Energy Efficiency",
"Natural Language Processing",
"Attention",
"Hardware Accelerator",
"Neural Network"
],
"authors": [
{
"affiliation": "Seoul National University",
"fullName": "Tae Jun Ham",
"givenName": "Tae Jun",
"surname": "Ham",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Seoul National University",
"fullName": "Yejin Lee",
"givenName": "Yejin",
"surname": "Lee",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Seoul National University",
"fullName": "Seong Hoon Seo",
"givenName": "Seong Hoon",
"surname": "Seo",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Seoul National University",
"fullName": "Soosung Kim",
"givenName": "Soosung",
"surname": "Kim",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Seoul National University",
"fullName": "Hyunji Choi",
"givenName": "Hyunji",
"surname": "Choi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Seoul National University",
"fullName": "Sung Jun Jung",
"givenName": "Sung Jun",
"surname": "Jung",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Seoul National University",
"fullName": "Jae W. Lee",
"givenName": "Jae W.",
"surname": "Lee",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "isca",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-06-01T00:00:00",
"pubType": "proceedings",
"pages": "692-705",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-3333-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "333300a679",
"articleId": "1vNjH1Bi7Ju",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "333300a706",
"articleId": "1vNjDWVoisw",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icbk/2018/9125/0/912500a268",
"title": "Short-Attention Mechanism for Generative Dialogue System",
"doi": null,
"abstractUrl": "/proceedings-article/icbk/2018/912500a268/17D45XeKgsP",
"parentPublication": {
"id": "proceedings/icbk/2018/9125/0",
"title": "2018 IEEE International Conference on Big Knowledge (ICBK)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dcabes/2021/2889/0/288900a140",
"title": "An effective lightweight attention mechanism",
"doi": null,
"abstractUrl": "/proceedings-article/dcabes/2021/288900a140/1AqwxXyic5G",
"parentPublication": {
"id": "proceedings/dcabes/2021/2889/0",
"title": "2021 20th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/micro/2022/6272/0/627200a599",
"title": "Adaptable Butterfly Accelerator for Attention-based NNs via Hardware and Algorithm Co-design",
"doi": null,
"abstractUrl": "/proceedings-article/micro/2022/627200a599/1HMSyobzBKM",
"parentPublication": {
"id": "proceedings/micro/2022/6272/0",
"title": "2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icedcs/2022/5541/0/554100a318",
"title": "The Advance of Deep Learning and Attention Mechanism",
"doi": null,
"abstractUrl": "/proceedings-article/icedcs/2022/554100a318/1JC1xobB6HS",
"parentPublication": {
"id": "proceedings/icedcs/2022/5541/0",
"title": "2022 International Conference on Electronics and Devices, Computational Science (ICEDCS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "letters/ca/2023/01/10005793",
"title": "HAMMER: Hardware-Friendly Approximate Computing for Self-Attention With Mean-Redistribution And Linearization",
"doi": null,
"abstractUrl": "/journal/ca/2023/01/10005793/1JF3UavFgo8",
"parentPublication": {
"id": "letters/ca",
"title": "IEEE Computer Architecture Letters",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpca/2023/7652/0/10070997",
"title": "CTA: Hardware-Software Co-design for Compressed Token Attention Mechanism",
"doi": null,
"abstractUrl": "/proceedings-article/hpca/2023/10070997/1LMbCvc9Cwg",
"parentPublication": {
"id": "proceedings/hpca/2023/7652/0",
"title": "2023 IEEE International Symposium on High-Performance Computer Architecture (HPCA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093341",
"title": "ULSAM: Ultra-Lightweight Subspace Attention Module for Compact Convolutional Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093341/1jPbbM2slBS",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iiai-aai/2020/7397/0/739700a110",
"title": "Multiple Perspective Caption Generation with Attention Mechanism",
"doi": null,
"abstractUrl": "/proceedings-article/iiai-aai/2020/739700a110/1tGcjfnt0eQ",
"parentPublication": {
"id": "proceedings/iiai-aai/2020/7397/0",
"title": "2020 9th International Congress on Advanced Applied Informatics (IIAI-AAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412456",
"title": "On the Global Self-attention Mechanism for Graph Convolutional Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412456/1tmjchGcGvS",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaa/2021/3730/0/373000a115",
"title": "Intra-and-inter Sentence Attention Model for Enhanced Question Answering System",
"doi": null,
"abstractUrl": "/proceedings-article/icaa/2021/373000a115/1zL1KEDp80U",
"parentPublication": {
"id": "proceedings/icaa/2021/3730/0",
"title": "2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1yeHGyRsuys",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1yeMjVGljFK",
"doi": "10.1109/CVPR46437.2021.00223",
"title": "A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts",
"normalizedTitle": "A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts",
"abstract": "Despite substantial progress in applying neural networks (NN) to a wide variety of areas, they still largely suffer from a lack of transparency and interpretability. While recent developments in explainable artificial intelligence attempt to bridge this gap (e.g., by visualizing the correlation between input pixels and final outputs), these approaches are limited to explaining low-level relationships, and crucially, do not provide insights on error correction. In this work, we propose a framework (VRX) to interpret classification NNs with intuitive structural visual concepts. Given a trained classification model, the proposed VRX extracts relevant class-specific visual concepts and organizes them using structural concept graphs (SCG) based on pairwise concept relationships. By means of knowledge distillation, we show VRX can take a step towards mimicking the reasoning process of NNs and provide logical, concept-level explanations for final model decisions. With extensive experiments, we empirically show VRX can meaningfully answer \"why\" and \"why not\" questions about the prediction, providing easy-to-understand insights about the reasoning process. We also show that these insights can potentially provide guidance on improving NN’s performance.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Despite substantial progress in applying neural networks (NN) to a wide variety of areas, they still largely suffer from a lack of transparency and interpretability. While recent developments in explainable artificial intelligence attempt to bridge this gap (e.g., by visualizing the correlation between input pixels and final outputs), these approaches are limited to explaining low-level relationships, and crucially, do not provide insights on error correction. In this work, we propose a framework (VRX) to interpret classification NNs with intuitive structural visual concepts. Given a trained classification model, the proposed VRX extracts relevant class-specific visual concepts and organizes them using structural concept graphs (SCG) based on pairwise concept relationships. By means of knowledge distillation, we show VRX can take a step towards mimicking the reasoning process of NNs and provide logical, concept-level explanations for final model decisions. With extensive experiments, we empirically show VRX can meaningfully answer \"why\" and \"why not\" questions about the prediction, providing easy-to-understand insights about the reasoning process. We also show that these insights can potentially provide guidance on improving NN’s performance.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Despite substantial progress in applying neural networks (NN) to a wide variety of areas, they still largely suffer from a lack of transparency and interpretability. While recent developments in explainable artificial intelligence attempt to bridge this gap (e.g., by visualizing the correlation between input pixels and final outputs), these approaches are limited to explaining low-level relationships, and crucially, do not provide insights on error correction. In this work, we propose a framework (VRX) to interpret classification NNs with intuitive structural visual concepts. Given a trained classification model, the proposed VRX extracts relevant class-specific visual concepts and organizes them using structural concept graphs (SCG) based on pairwise concept relationships. By means of knowledge distillation, we show VRX can take a step towards mimicking the reasoning process of NNs and provide logical, concept-level explanations for final model decisions. With extensive experiments, we empirically show VRX can meaningfully answer \"why\" and \"why not\" questions about the prediction, providing easy-to-understand insights about the reasoning process. We also show that these insights can potentially provide guidance on improving NN’s performance.",
"fno": "450900c195",
"keywords": [
"Graph Theory",
"Inference Mechanisms",
"Learning Artificial Intelligence",
"Neural Nets",
"Pattern Classification",
"Transparency",
"Explainable Artificial Intelligence",
"Input Pixels",
"Final Outputs",
"Low Level Relationships",
"Error Correction",
"VRX",
"Classification NN",
"Intuitive Structural Visual Concepts",
"Trained Classification Model",
"Structural Concept Graphs",
"Pairwise Concept Relationships",
"Reasoning Process",
"Logical Concept Level Explanations",
"Model Decisions",
"Neural Network Reasoning",
"Deep Learning",
"Bridges",
"Visualization",
"Computer Vision",
"Correlation",
"Decision Making",
"Artificial Neural Networks"
],
"authors": [
{
"affiliation": "United Imaging Intelligence,Cambridge,MA",
"fullName": "Yunhao Ge",
"givenName": "Yunhao",
"surname": "Ge",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Southern California,Los Angeles,CA",
"fullName": "Yao Xiao",
"givenName": "Yao",
"surname": "Xiao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Southern California,Los Angeles,CA",
"fullName": "Zhi Xu",
"givenName": "Zhi",
"surname": "Xu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "United Imaging Intelligence,Cambridge,MA",
"fullName": "Meng Zheng",
"givenName": "Meng",
"surname": "Zheng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "United Imaging Intelligence,Cambridge,MA",
"fullName": "Srikrishna Karanam",
"givenName": "Srikrishna",
"surname": "Karanam",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "United Imaging Intelligence,Cambridge,MA",
"fullName": "Terrence Chen",
"givenName": "Terrence",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Southern California,Los Angeles,CA",
"fullName": "Laurent Itti",
"givenName": "Laurent",
"surname": "Itti",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "United Imaging Intelligence,Cambridge,MA",
"fullName": "Ziyan Wu",
"givenName": "Ziyan",
"surname": "Wu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-06-01T00:00:00",
"pubType": "proceedings",
"pages": "2195-2204",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-4509-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1yeMjRSb3s4",
"name": "pcvpr202145090-09578537s1-mm_450900c195.zip",
"size": "198 kB",
"location": "https://www.computer.org/csdl/api/v1/extra/pcvpr202145090-09578537s1-mm_450900c195.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "450900c185",
"articleId": "1yeM0lkFgTm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "450900c205",
"articleId": "1yeJdwRZbfa",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icmlc/2003/7865/4/01259954",
"title": "Evaluating design concepts by ranking fuzzy numbers",
"doi": null,
"abstractUrl": "/proceedings-article/icmlc/2003/01259954/12OmNBCqbFS",
"parentPublication": {
"id": "proceedings/icmlc/2003/7865/4",
"title": "Proceedings of the 2003 International Conference on Machine Learning and Cybernetics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2015/7644/0/7644a967",
"title": "The Evaluation Model of the Bridge Approach Design Scheme Based on the Life",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2015/7644a967/12OmNC943Hy",
"parentPublication": {
"id": "proceedings/icicta/2015/7644/0",
"title": "2015 8th International Conference on Intelligent Computation Technology and Automation (ICICTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgc/2013/5114/0/5114a249",
"title": "Rated Tags: Adding Rating Capability to Collaborative Tagging",
"doi": null,
"abstractUrl": "/proceedings-article/cgc/2013/5114a249/12OmNro0IcV",
"parentPublication": {
"id": "proceedings/cgc/2013/5114/0",
"title": "2013 International Conference on Cloud and Green Computing (CGC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iat/2006/2748/0/04052983",
"title": "Comparing the Performance of MLP and RBF Neural Networks Employed by Negotiating Intelligent Agents",
"doi": null,
"abstractUrl": "/proceedings-article/iat/2006/04052983/12OmNz2kqmD",
"parentPublication": {
"id": "proceedings/iat/2006/2748/0",
"title": "2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fskd/2009/3735/6/3735f153",
"title": "Conceptual Space and Reasoning Method of Intelligent System",
"doi": null,
"abstractUrl": "/proceedings-article/fskd/2009/3735f153/12OmNzCWG0K",
"parentPublication": {
"id": "proceedings/fskd/2009/3735/6",
"title": "Fuzzy Systems and Knowledge Discovery, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wetice/2018/6916/0/691601a148",
"title": "Investigating Plausible Reasoning Over Knowledge Graphs for Semantics-Based Health Data Analytics",
"doi": null,
"abstractUrl": "/proceedings-article/wetice/2018/691601a148/17D45WaTkdS",
"parentPublication": {
"id": "proceedings/wetice/2018/6916/0",
"title": "2018 IEEE 27th International Conference on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2017/2715/0/08258380",
"title": "Understanding data quality: Ensuring data quality by design in the rail industry",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2017/08258380/17D45WrVfZT",
"parentPublication": {
"id": "proceedings/big-data/2017/2715/0",
"title": "2017 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2007/2755/0/04076482",
"title": "Knowledge Management in Decision Making: Instance-Based Cognitive Mapping",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2007/04076482/17D45XeKgtC",
"parentPublication": {
"id": "proceedings/hicss/2007/2755/0",
"title": "2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2022/9062/0/09956394",
"title": "Neural Network Decision-Making Criteria Consistency Analysis via Inputs Sensitivity",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2022/09956394/1IHpt1QvdwA",
"parentPublication": {
"id": "proceedings/icpr/2022/9062/0",
"title": "2022 26th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aike/2019/1488/0/148800a187",
"title": "Hierarchical Clustering for Discrimination Discovery: A Top-Down Approach",
"doi": null,
"abstractUrl": "/proceedings-article/aike/2019/148800a187/1ckrCbCAPXa",
"parentPublication": {
"id": "proceedings/aike/2019/1488/0",
"title": "2019 IEEE Second International Conference on Artificial Intelligence and Knowledge Engineering (AIKE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1LSP2uFcspi",
"title": "2022 5th International Conference on Computing and Big Data (ICCBD)",
"acronym": "iccbd",
"groupId": "1848994",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1LSP47RLwFq",
"doi": "10.1109/ICCBD56965.2022.10079964",
"title": "Multiple Magnification Spatial Super-Resolution Network for Light Field Images Based on EPI Solid",
"normalizedTitle": "Multiple Magnification Spatial Super-Resolution Network for Light Field Images Based on EPI Solid",
"abstract": "The Light field (LF) imaging technology can obtain the spatial information and angular information of light simultaneously. Since, the sensor captures multiple images from different angular directions, the spatial resolution of each view image is limited. LF image super-resolution (SR) methods based on deep-learning have been proposed to solve this problem. However, correlation of LF image at two angular dimensions have not been fully exploited in algorithms that based on epipolar plane images (EPIs). In this paper, we propose a joint LF image SR network by combining a multiple magnification single image SR (SISR) network and an inpainting network for EPI solids. The EPI solids, which contain information of both angular dimensions, are extracted from the output of SISR network and used as input data of the inpainting network. The inpainting network uses channel attention mechanism in feature extraction module to extracting line and gradient feature contained by EPI solids and correlations between EPI slices of EPI sold for restoring the geometric continuity of different views. Experimental results show that the proposed multiple magnification spatial LF image SR network which is trained by dataset with mixed magnifications has better performance than other approaches that are specially trained at each magnification.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The Light field (LF) imaging technology can obtain the spatial information and angular information of light simultaneously. Since, the sensor captures multiple images from different angular directions, the spatial resolution of each view image is limited. LF image super-resolution (SR) methods based on deep-learning have been proposed to solve this problem. However, correlation of LF image at two angular dimensions have not been fully exploited in algorithms that based on epipolar plane images (EPIs). In this paper, we propose a joint LF image SR network by combining a multiple magnification single image SR (SISR) network and an inpainting network for EPI solids. The EPI solids, which contain information of both angular dimensions, are extracted from the output of SISR network and used as input data of the inpainting network. The inpainting network uses channel attention mechanism in feature extraction module to extracting line and gradient feature contained by EPI solids and correlations between EPI slices of EPI sold for restoring the geometric continuity of different views. Experimental results show that the proposed multiple magnification spatial LF image SR network which is trained by dataset with mixed magnifications has better performance than other approaches that are specially trained at each magnification.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The Light field (LF) imaging technology can obtain the spatial information and angular information of light simultaneously. Since, the sensor captures multiple images from different angular directions, the spatial resolution of each view image is limited. LF image super-resolution (SR) methods based on deep-learning have been proposed to solve this problem. However, correlation of LF image at two angular dimensions have not been fully exploited in algorithms that based on epipolar plane images (EPIs). In this paper, we propose a joint LF image SR network by combining a multiple magnification single image SR (SISR) network and an inpainting network for EPI solids. The EPI solids, which contain information of both angular dimensions, are extracted from the output of SISR network and used as input data of the inpainting network. The inpainting network uses channel attention mechanism in feature extraction module to extracting line and gradient feature contained by EPI solids and correlations between EPI slices of EPI sold for restoring the geometric continuity of different views. Experimental results show that the proposed multiple magnification spatial LF image SR network which is trained by dataset with mixed magnifications has better performance than other approaches that are specially trained at each magnification.",
"fno": "10079964",
"keywords": [
"Deep Learning Artificial Intelligence",
"Feature Extraction",
"Image Reconstruction",
"Image Resolution",
"Image Restoration",
"Angular Dimensions",
"Angular Information",
"Different Angular Directions",
"EPI Solid",
"Epipolar Plane Images",
"Imaging Technology",
"Inpainting Network",
"Joint LF Image SR Network",
"LF Image Super Resolution Methods",
"Light Field Images",
"Multiple Images",
"Multiple Magnification Single Image SR Network",
"Multiple Magnification Spatial LF Image SR Network",
"Multiple Magnification Spatial Super Resolution Network",
"SISR Network",
"Spatial Information",
"Spatial Resolution",
"View Image",
"Correlation",
"Three Dimensional Displays",
"Superresolution",
"Training Data",
"Imaging",
"Solids",
"Feature Extraction",
"Epipolar Plane Image",
"Light Field",
"Network",
"Superresolution"
],
"authors": [
{
"affiliation": "School of Instrumentation and Optoelectronics Engineering Beihang University,Beijing,China",
"fullName": "Lijuan Su",
"givenName": "Lijuan",
"surname": "Su",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "TowardPi (Beijing) Medical Technology Co., Ltd,Beijing,China",
"fullName": "Zimu Ye",
"givenName": "Zimu",
"surname": "Ye",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Instrumentation and Optoelectronics Engineering Beihang University,Beijing,China",
"fullName": "Yan Yuan",
"givenName": "Yan",
"surname": "Yuan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Instrumentation and Optoelectronics Engineering Beihang University,Beijing,China",
"fullName": "Yuxiao Sui",
"givenName": "Yuxiao",
"surname": "Sui",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Instrumentation and Optoelectronics Engineering Beihang University,Beijing,China",
"fullName": "Deqian Kong",
"givenName": "Deqian",
"surname": "Kong",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Shanghai Electro-Mechanical Engineering Institute,Shanghai,China",
"fullName": "Yue Xu",
"givenName": "Yue",
"surname": "Xu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccbd",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-12-01T00:00:00",
"pubType": "proceedings",
"pages": "151-159",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-5716-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "10080143",
"articleId": "1LSP6Gri3S0",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "10080596",
"articleId": "1LSP64kds0U",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icmew/2015/7079/0/07169836",
"title": "Light field depth estimation exploiting linear structure in EPI",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2015/07169836/12OmNC4eSyV",
"parentPublication": {
"id": "proceedings/icmew/2015/7079/0",
"title": "2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2017/0457/0/0457b638",
"title": "Light Field Reconstruction Using Deep Convolutional Network on EPI",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2017/0457b638/12OmNyL0TKK",
"parentPublication": {
"id": "proceedings/cvpr/2017/0457/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2017/1032/0/1032c271",
"title": "Neural EPI-Volume Networks for Shape from Light Field",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/1032c271/12OmNzIl3zs",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2019/07/08375807",
"title": "Light Field Reconstruction Using Convolutional Network on EPI and Extended Applications",
"doi": null,
"abstractUrl": "/journal/tp/2019/07/08375807/13rRUIIVllP",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/01/09716806",
"title": "Disentangling Light Fields for Super-Resolution and Disparity Estimation",
"doi": null,
"abstractUrl": "/journal/tp/2023/01/09716806/1B5WzcrxgIM",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09798876",
"title": "Deep Light Field Spatial Super-Resolution Using Heterogeneous Imaging",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09798876/1Eho8QXQucg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmew/2022/7218/0/09859373",
"title": "LFC-SASR: Light Field Coding Using Spatial and Angular Super-Resolution",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2022/09859373/1G4F0ndbVoQ",
"parentPublication": {
"id": "proceedings/icmew/2022/7218/0",
"title": "2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09889219",
"title": "Learning Reliable Gradients From Undersampled Circular Light Field for 3D Reconstruction",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09889219/1GDryH066Lm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmew/2020/1485/0/09105975",
"title": "No-Reference Quality Evaluation of Light Field Content Based on Structural Representation of The Epipolar Plane Image",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2020/09105975/1kwqzhoeyQM",
"parentPublication": {
"id": "proceedings/icmew/2020/1485/0",
"title": "2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800c257",
"title": "Light Field Spatial Super-Resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800c257/1m3npj9GAZa",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1m3n9N02qgE",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1m3npj9GAZa",
"doi": "10.1109/CVPR42600.2020.00233",
"title": "Light Field Spatial Super-Resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization",
"normalizedTitle": "Light Field Spatial Super-Resolution via Deep Combinatorial Geometry Embedding and Structural Consistency Regularization",
"abstract": "Light field (LF) images acquired by hand-held devices usually suffer from low spatial resolution as the limited sampling resources have to be shared with the angular dimension. LF spatial super-resolution (SR) thus becomes an indispensable part of the LF camera processing pipeline. The high-dimensionality characteristic and complex geometrical structure of LF images makes the problem more challenging than traditional single-image SR. The performance of existing methods are still limited as they fail to thoroughly explore the coherence among LF views and are insufficient in accurately preserving the parallax structure of the scene. In this paper, we propose a novel learning-based LF spatial SR framework, in which each view of an LF image is first individually super-resolved by exploring the complementary information among views with combinatorial geometry embedding. For accurate preservation of the parallax structure among the reconstructed views, a regularization network trained over a structure-aware loss function is subsequently appended to enforce correct parallax relationships over the intermediate estimation. Our proposed approach is evaluated over datasets with a large number of testing images including both synthetic and real-world scenes. Experimental results demonstrate the advantage of our approach over state-of-the-art methods, i.e., our method not only improves the average PSNR by more than 1.0 dB but also preserves more accurate parallax details, at a lower computation cost.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Light field (LF) images acquired by hand-held devices usually suffer from low spatial resolution as the limited sampling resources have to be shared with the angular dimension. LF spatial super-resolution (SR) thus becomes an indispensable part of the LF camera processing pipeline. The high-dimensionality characteristic and complex geometrical structure of LF images makes the problem more challenging than traditional single-image SR. The performance of existing methods are still limited as they fail to thoroughly explore the coherence among LF views and are insufficient in accurately preserving the parallax structure of the scene. In this paper, we propose a novel learning-based LF spatial SR framework, in which each view of an LF image is first individually super-resolved by exploring the complementary information among views with combinatorial geometry embedding. For accurate preservation of the parallax structure among the reconstructed views, a regularization network trained over a structure-aware loss function is subsequently appended to enforce correct parallax relationships over the intermediate estimation. Our proposed approach is evaluated over datasets with a large number of testing images including both synthetic and real-world scenes. Experimental results demonstrate the advantage of our approach over state-of-the-art methods, i.e., our method not only improves the average PSNR by more than 1.0 dB but also preserves more accurate parallax details, at a lower computation cost.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Light field (LF) images acquired by hand-held devices usually suffer from low spatial resolution as the limited sampling resources have to be shared with the angular dimension. LF spatial super-resolution (SR) thus becomes an indispensable part of the LF camera processing pipeline. The high-dimensionality characteristic and complex geometrical structure of LF images makes the problem more challenging than traditional single-image SR. The performance of existing methods are still limited as they fail to thoroughly explore the coherence among LF views and are insufficient in accurately preserving the parallax structure of the scene. In this paper, we propose a novel learning-based LF spatial SR framework, in which each view of an LF image is first individually super-resolved by exploring the complementary information among views with combinatorial geometry embedding. For accurate preservation of the parallax structure among the reconstructed views, a regularization network trained over a structure-aware loss function is subsequently appended to enforce correct parallax relationships over the intermediate estimation. Our proposed approach is evaluated over datasets with a large number of testing images including both synthetic and real-world scenes. Experimental results demonstrate the advantage of our approach over state-of-the-art methods, i.e., our method not only improves the average PSNR by more than 1.0 dB but also preserves more accurate parallax details, at a lower computation cost.",
"fno": "716800c257",
"keywords": [
"Cameras",
"Computational Geometry",
"Image Enhancement",
"Image Reconstruction",
"Image Resolution",
"Learning Artificial Intelligence",
"Regularization Network",
"Structure Aware Loss Function",
"Correct Parallax Relationships",
"Light Field Spatial Super Resolution",
"Deep Combinatorial Geometry Embedding",
"Structural Consistency Regularization",
"Light Field Images",
"Hand Held Devices",
"Sampling Resources",
"Angular Dimension",
"LF Spatial Super Resolution",
"LF Camera Processing Pipeline",
"LF Image",
"Single Image SR",
"Learning Based LF Spatial SR Framework",
"Spatial Resolution",
"Geometry",
"Image Reconstruction",
"Correlation",
"Learning Systems",
"Two Dimensional Displays"
],
"authors": [
{
"affiliation": "City University of Hong Kong",
"fullName": "Jing Jin",
"givenName": "Jing",
"surname": "Jin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "City University of Hong Kong",
"fullName": "Junhui Hou",
"givenName": "Junhui",
"surname": "Hou",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Hong Kong Baptist University",
"fullName": "Jie Chen",
"givenName": "Jie",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "City University of Hong Kong",
"fullName": "Sam Kwong",
"givenName": "Sam",
"surname": "Kwong",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-06-01T00:00:00",
"pubType": "proceedings",
"pages": "2257-2266",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-7168-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "716800c247",
"articleId": "1m3nv28d9bq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "716800c267",
"articleId": "1m3nQsEkgAE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/2016/8851/0/8851b646",
"title": "Accurate Image Super-Resolution Using Very Deep Convolutional Networks",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2016/8851b646/12OmNApu5eJ",
"parentPublication": {
"id": "proceedings/cvpr/2016/8851/0",
"title": "2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2014/4761/0/06890144",
"title": "Content adaptive image superresolution with gradient consistency and anisotropic regularization",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2014/06890144/12OmNqIzhaS",
"parentPublication": {
"id": "proceedings/icme/2014/4761/0",
"title": "2014 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccp/2014/5188/0/06831814",
"title": "Improving resolution and depth-of-field of light field cameras using a hybrid imaging system",
"doi": null,
"abstractUrl": "/proceedings-article/iccp/2014/06831814/12OmNyaoDEw",
"parentPublication": {
"id": "proceedings/iccp/2014/5188/0",
"title": "2014 IEEE International Conference on Computational Photography (ICCP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/01/09716806",
"title": "Disentangling Light Fields for Super-Resolution and Disparity Estimation",
"doi": null,
"abstractUrl": "/journal/tp/2023/01/09716806/1B5WzcrxgIM",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200c430",
"title": "Learning Dynamic Interpolation for Extremely Sparse Light Fields with Wide Baselines",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200c430/1BmFg4NKuJ2",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09798876",
"title": "Deep Light Field Spatial Super-Resolution Using Heterogeneous Imaging",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09798876/1Eho8QXQucg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccbd/2022/5716/0/10079964",
"title": "Multiple Magnification Spatial Super-Resolution Network for Light Field Images Based on EPI Solid",
"doi": null,
"abstractUrl": "/proceedings-article/iccbd/2022/10079964/1LSP47RLwFq",
"parentPublication": {
"id": "proceedings/iccbd/2022/5716/0",
"title": "2022 5th International Conference on Computing and Big Data (ICCBD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2019/9552/0/955200a586",
"title": "Difficulty-Aware Image Super Resolution via Deep Adaptive Dual-Network",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2019/955200a586/1cdOMCKVc1W",
"parentPublication": {
"id": "proceedings/icme/2019/9552/0",
"title": "2019 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/04/09204825",
"title": "Deep Coarse-to-Fine Dense Light Field Reconstruction With Flexible Sampling and Geometry-Aware Fusion",
"doi": null,
"abstractUrl": "/journal/tp/2022/04/09204825/1nmdSsM9aQ8",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/10/09448470",
"title": "Deep Spatial-Angular Regularization for Light Field Imaging, Denoising, and Super-Resolution",
"doi": null,
"abstractUrl": "/journal/tp/2022/10/09448470/1ugE5vtunqo",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1yeHGyRsuys",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1yeISN5Dx4c",
"doi": "10.1109/CVPR46437.2021.00988",
"title": "Light Field Super-Resolution with Zero-Shot Learning",
"normalizedTitle": "Light Field Super-Resolution with Zero-Shot Learning",
"abstract": "Deep learning provides a new avenue for light field super-resolution (SR). However, the domain gap caused by drastically different light field acquisition conditions poses a main obstacle in practice. To fill this gap, we propose a zero-shot learning framework for light field SR, which learns a mapping to super-resolve the reference view with examples extracted solely from the input low-resolution light field itself. Given highly limited training data under the zero-shot setting, however, we observe that it is difficult to train an end-to-end network successfully. Instead, we divide this challenging task into three sub-tasks, i.e., pre-upsampling, view alignment, and multi-view aggregation, and then conquer them separately with simple yet efficient CNNs. Moreover, the proposed framework can be readily extended to finetune the pre-trained model on a source dataset to better adapt to the target input, which further boosts the performance of light field SR in the wild. Experimental results validate that our method not only outperforms classic non-learning-based methods, but also generalizes better to unseen light fields than state-of-the-art deep-learning-based methods when the domain gap is large.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Deep learning provides a new avenue for light field super-resolution (SR). However, the domain gap caused by drastically different light field acquisition conditions poses a main obstacle in practice. To fill this gap, we propose a zero-shot learning framework for light field SR, which learns a mapping to super-resolve the reference view with examples extracted solely from the input low-resolution light field itself. Given highly limited training data under the zero-shot setting, however, we observe that it is difficult to train an end-to-end network successfully. Instead, we divide this challenging task into three sub-tasks, i.e., pre-upsampling, view alignment, and multi-view aggregation, and then conquer them separately with simple yet efficient CNNs. Moreover, the proposed framework can be readily extended to finetune the pre-trained model on a source dataset to better adapt to the target input, which further boosts the performance of light field SR in the wild. Experimental results validate that our method not only outperforms classic non-learning-based methods, but also generalizes better to unseen light fields than state-of-the-art deep-learning-based methods when the domain gap is large.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Deep learning provides a new avenue for light field super-resolution (SR). However, the domain gap caused by drastically different light field acquisition conditions poses a main obstacle in practice. To fill this gap, we propose a zero-shot learning framework for light field SR, which learns a mapping to super-resolve the reference view with examples extracted solely from the input low-resolution light field itself. Given highly limited training data under the zero-shot setting, however, we observe that it is difficult to train an end-to-end network successfully. Instead, we divide this challenging task into three sub-tasks, i.e., pre-upsampling, view alignment, and multi-view aggregation, and then conquer them separately with simple yet efficient CNNs. Moreover, the proposed framework can be readily extended to finetune the pre-trained model on a source dataset to better adapt to the target input, which further boosts the performance of light field SR in the wild. Experimental results validate that our method not only outperforms classic non-learning-based methods, but also generalizes better to unseen light fields than state-of-the-art deep-learning-based methods when the domain gap is large.",
"fno": "450900k0005",
"keywords": [
"Deep Learning Artificial Intelligence",
"Image Resolution",
"Image Sampling",
"Object Recognition",
"Light Field Superresolution",
"Deep Learning",
"Domain Gap",
"Zero Shot Learning Framework",
"Light Field SR",
"Nonlearning Based Methods",
"End To End Network",
"Preupsampling",
"View Alignment",
"Multiview Aggregation",
"CNN",
"Input Low Resolution Light Field Acquisition Condition",
"Deep Learning",
"Computer Vision",
"Adaptation Models",
"Superresolution",
"Training Data",
"Light Fields",
"Data Mining"
],
"authors": [
{
"affiliation": "University of Science and Technology of China",
"fullName": "Zhen Cheng",
"givenName": "Zhen",
"surname": "Cheng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Science and Technology of China",
"fullName": "Zhiwei Xiong",
"givenName": "Zhiwei",
"surname": "Xiong",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Science and Technology of China",
"fullName": "Chang Chen",
"givenName": "Chang",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Science and Technology of China",
"fullName": "Dong Liu",
"givenName": "Dong",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Science and Technology of China",
"fullName": "Zheng-Jun Zha",
"givenName": "Zheng-Jun",
"surname": "Zha",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-06-01T00:00:00",
"pubType": "proceedings",
"pages": "10005-10014",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-4509-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1yeISH4EC9q",
"name": "pcvpr202145090-09577269s1-mm_450900k0005.zip",
"size": "9.93 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pcvpr202145090-09577269s1-mm_450900k0005.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "450900j995",
"articleId": "1yeKp0Bm4JG",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "450900k0015",
"articleId": "1yeLv22h6SY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cvpr/2018/6420/0/642000d118",
"title": "Zero-Shot Super-Resolution Using Deep Internal Learning",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000d118/17D45WgziR6",
"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/2020/05/08620368",
"title": "Light Field Super-Resolution Using a Low-Rank Prior and Deep Convolutional Neural Networks",
"doi": null,
"abstractUrl": "/journal/tp/2020/05/08620368/17D45Wt3Exc",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/9.15E43",
"title": "Hyperspectral Image Super-Resolution with RGB Image Super-Resolution as an Auxiliary Task",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/9.15E43/1B13KOWVC7u",
"parentPublication": {
"id": "proceedings/wacv/2022/0915/0",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09798876",
"title": "Deep Light Field Spatial Super-Resolution Using Heterogeneous Imaging",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09798876/1Eho8QXQucg",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmew/2022/7218/0/09859373",
"title": "LFC-SASR: Light Field Coding Using Spatial and Angular Super-Resolution",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2022/09859373/1G4F0ndbVoQ",
"parentPublication": {
"id": "proceedings/icmew/2022/7218/0",
"title": "2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccbd/2022/5716/0/10079964",
"title": "Multiple Magnification Spatial Super-Resolution Network for Light Field Images Based on EPI Solid",
"doi": null,
"abstractUrl": "/proceedings-article/iccbd/2022/10079964/1LSP47RLwFq",
"parentPublication": {
"id": "proceedings/iccbd/2022/5716/0",
"title": "2022 5th International Conference on Computing and Big Data (ICCBD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2019/2506/0/250600b804",
"title": "Light Field Super-Resolution: A Benchmark",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2019/250600b804/1iTvo7kjJFm",
"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/tg/2021/09/09043741",
"title": "4D Light Field Segmentation From Light Field Super-Pixel Hypergraph Representation",
"doi": null,
"abstractUrl": "/journal/tg/2021/09/09043741/1ilQLDcivHa",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2021/12/09099445",
"title": "CrossNet++: Cross-Scale Large-Parallax Warping for Reference-Based Super-Resolution",
"doi": null,
"abstractUrl": "/journal/tp/2021/12/09099445/1k7oyvQ9LzO",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/019100d676",
"title": "Super-resolution for in situ Plankton Images",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100d676/1yNhonHAzlK",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyoiYVr",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2017",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNqyUUwV",
"doi": "10.1109/CVPR.2017.595",
"title": "Convex Global 3D Registration with Lagrangian Duality",
"normalizedTitle": "Convex Global 3D Registration with Lagrangian Duality",
"abstract": "The registration of 3D models by a Euclidean transformation is a fundamental task at the core of many application in computer vision. This problem is non-convex due to the presence of rotational constraints, making traditional local optimization methods prone to getting stuck in local minima. This paper addresses finding the globally optimal transformation in various 3D registration problems by a unified formulation that integrates common geometric registration modalities (namely point-to-point, point-to-line and point-to-plane). This formulation renders the optimization problem independent of both the number and nature of the correspondences. The main novelty of our proposal is the introduction of a strengthened Lagrangian dual relaxation for this problem, which surpasses previous similar approaches [32] in effectiveness. In fact, even though with no theoretical guarantees, exhaustive empirical evaluation in both synthetic and real experiments always resulted on a tight relaxation that allowed to recover a guaranteed globally optimal solution by exploiting duality theory. Thus, our approach allows for effectively solving the 3D registration with global optimality guarantees while running at a fraction of the time for the state-of-the-art alternative [34], based on a more computationally intensive Branch and Bound method.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The registration of 3D models by a Euclidean transformation is a fundamental task at the core of many application in computer vision. This problem is non-convex due to the presence of rotational constraints, making traditional local optimization methods prone to getting stuck in local minima. This paper addresses finding the globally optimal transformation in various 3D registration problems by a unified formulation that integrates common geometric registration modalities (namely point-to-point, point-to-line and point-to-plane). This formulation renders the optimization problem independent of both the number and nature of the correspondences. The main novelty of our proposal is the introduction of a strengthened Lagrangian dual relaxation for this problem, which surpasses previous similar approaches [32] in effectiveness. In fact, even though with no theoretical guarantees, exhaustive empirical evaluation in both synthetic and real experiments always resulted on a tight relaxation that allowed to recover a guaranteed globally optimal solution by exploiting duality theory. Thus, our approach allows for effectively solving the 3D registration with global optimality guarantees while running at a fraction of the time for the state-of-the-art alternative [34], based on a more computationally intensive Branch and Bound method.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The registration of 3D models by a Euclidean transformation is a fundamental task at the core of many application in computer vision. This problem is non-convex due to the presence of rotational constraints, making traditional local optimization methods prone to getting stuck in local minima. This paper addresses finding the globally optimal transformation in various 3D registration problems by a unified formulation that integrates common geometric registration modalities (namely point-to-point, point-to-line and point-to-plane). This formulation renders the optimization problem independent of both the number and nature of the correspondences. The main novelty of our proposal is the introduction of a strengthened Lagrangian dual relaxation for this problem, which surpasses previous similar approaches [32] in effectiveness. In fact, even though with no theoretical guarantees, exhaustive empirical evaluation in both synthetic and real experiments always resulted on a tight relaxation that allowed to recover a guaranteed globally optimal solution by exploiting duality theory. Thus, our approach allows for effectively solving the 3D registration with global optimality guarantees while running at a fraction of the time for the state-of-the-art alternative [34], based on a more computationally intensive Branch and Bound method.",
"fno": "0457f612",
"keywords": [
"Computer Vision",
"Concave Programming",
"Convex Programming",
"Duality Mathematics",
"Image Registration",
"Lagrangian Duality",
"Euclidean Transformation",
"Computer Vision",
"Rotational Constraints",
"Local Minima",
"Globally Optimal Transformation",
"Unified Formulation",
"Common Geometric Registration Modalities",
"Optimization Problem",
"Duality Theory",
"Global Optimality Guarantees",
"Local Optimization Methods",
"Globally Optimal Solution",
"Lagrangian Dual Relaxation",
"Convex Global 3 D Registration",
"Nonconvex Problem",
"Point To Line Modality",
"Point To Point Modality",
"Point To Plane Modality",
"Three Dimensional Displays",
"Optimization",
"Computer Vision",
"Proposals",
"Pipelines",
"Simultaneous Localization And Mapping"
],
"authors": [
{
"affiliation": null,
"fullName": "Jesus Briales",
"givenName": "Jesus",
"surname": "Briales",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Javier Gonzalez-Jimenez",
"givenName": "Javier",
"surname": "Gonzalez-Jimenez",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2017-07-01T00:00:00",
"pubType": "proceedings",
"pages": "5612-5621",
"year": "2017",
"issn": "1063-6919",
"isbn": "978-1-5386-0457-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "0457f603",
"articleId": "12OmNBoNroW",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "0457f622",
"articleId": "12OmNyVes0x",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2016/0641/0/07477656",
"title": "The generalized relative pose and scale problem: View-graph fusion via 2D-2D registration",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2016/07477656/12OmNzWx0bQ",
"parentPublication": {
"id": "proceedings/wacv/2016/0641/0",
"title": "2016 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/visapp/2014/8133/3/07295128",
"title": "Towards robust image registration for underwater visual SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/visapp/2014/07295128/12OmNzcPAsA",
"parentPublication": {
"id": "proceedings/visapp/2014/8133/2",
"title": "2014 International Conference on Computer Vision Theory and Applications (VISAPP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2014/04/ttg201404531",
"title": "Global Localization from Monocular SLAM on a Mobile Phone",
"doi": null,
"abstractUrl": "/journal/tg/2014/04/ttg201404531/13rRUwdrdSA",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09797054",
"title": "Compact World Anchors: Registration Using Parametric Primitives as Scene Description",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09797054/1EexleVk9kk",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscer/2022/8478/0/847800a161",
"title": "Point cloud registration method based on 3DMatch network and improved ISS algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/iscer/2022/847800a161/1HbbuMbRyqA",
"parentPublication": {
"id": "proceedings/iscer/2022/8478/0",
"title": "2022 International Symposium on Control Engineering and Robotics (ISCER)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a077",
"title": "Point cloud to BIM registration for robot localization and Augmented Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a077/1J7WmGwePGU",
"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/cis/2019/6092/0/609200a132",
"title": "Point Cloud Registration Algorithm Based on Combination of NDT and PLICP",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2019/609200a132/1i5m6DnRNsc",
"parentPublication": {
"id": "proceedings/cis/2019/6092/0",
"title": "2019 15th International Conference on Computational Intelligence and Security (CIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800c511",
"title": "Deep Global Registration",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800c511/1m3o1HPZIli",
"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/2021/4509/0/450900h125",
"title": "UnsupervisedR&R: Unsupervised Point Cloud Registration via Differentiable Rendering",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900h125/1yeI1ICFJTy",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaa/2021/3730/0/373000a145",
"title": "Improved Loop Detection Method Based on ICP and NDT Registration Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/icaa/2021/373000a145/1zL1Mh20NnG",
"parentPublication": {
"id": "proceedings/icaa/2021/3730/0",
"title": "2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyS6RMH",
"title": "2016 13th Conference on Computer and Robot Vision (CRV)",
"acronym": "crv",
"groupId": "1001794",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNx1IwdI",
"doi": "10.1109/CRV.2016.69",
"title": "Texture-Aware SLAM Using Stereo Imagery and Inertial Information",
"normalizedTitle": "Texture-Aware SLAM Using Stereo Imagery and Inertial Information",
"abstract": "We present a gaze control method that augments an existing stereo and inertial Simultaneous Localization And Mapping (SLAM) system by directing the stereo camera towards feature-rich regions of the scene. Our integrated active SLAM system is based on careful triangulation of visual features, existing successful nonlinear optimization, and visual loop closing frameworks. It relies on the tight coupling of IMU measurements with constraints imposed by visual correspondences from both stereo and motion. Alongside the SLAM system, the gaze control module also runs in real-time and includes an efficient online classifier that segments the scene into texture classes and assigns a quality score to each class that correlates with the availability of reliable features for tracking. Based on this quality score, the gaze selection module controls a pan-tilt unit that directs the camera to focus on high-reward texture classes. We validate our system in both indoor and outdoor spaces, and we show that active gaze control crucially improves the robustness and long-term operation of the localization system.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We present a gaze control method that augments an existing stereo and inertial Simultaneous Localization And Mapping (SLAM) system by directing the stereo camera towards feature-rich regions of the scene. Our integrated active SLAM system is based on careful triangulation of visual features, existing successful nonlinear optimization, and visual loop closing frameworks. It relies on the tight coupling of IMU measurements with constraints imposed by visual correspondences from both stereo and motion. Alongside the SLAM system, the gaze control module also runs in real-time and includes an efficient online classifier that segments the scene into texture classes and assigns a quality score to each class that correlates with the availability of reliable features for tracking. Based on this quality score, the gaze selection module controls a pan-tilt unit that directs the camera to focus on high-reward texture classes. We validate our system in both indoor and outdoor spaces, and we show that active gaze control crucially improves the robustness and long-term operation of the localization system.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We present a gaze control method that augments an existing stereo and inertial Simultaneous Localization And Mapping (SLAM) system by directing the stereo camera towards feature-rich regions of the scene. Our integrated active SLAM system is based on careful triangulation of visual features, existing successful nonlinear optimization, and visual loop closing frameworks. It relies on the tight coupling of IMU measurements with constraints imposed by visual correspondences from both stereo and motion. Alongside the SLAM system, the gaze control module also runs in real-time and includes an efficient online classifier that segments the scene into texture classes and assigns a quality score to each class that correlates with the availability of reliable features for tracking. Based on this quality score, the gaze selection module controls a pan-tilt unit that directs the camera to focus on high-reward texture classes. We validate our system in both indoor and outdoor spaces, and we show that active gaze control crucially improves the robustness and long-term operation of the localization system.",
"fno": "2491a456",
"keywords": [
"Simultaneous Localization And Mapping",
"Cameras",
"Visualization",
"Optimization",
"Robustness",
"Robot Vision Systems",
"Active Sensing",
"Robotics",
"Vision",
"SLAM"
],
"authors": [
{
"affiliation": null,
"fullName": "Travis Manderson",
"givenName": "Travis",
"surname": "Manderson",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Florian Shkurti",
"givenName": "Florian",
"surname": "Shkurti",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Gregory Dudek",
"givenName": "Gregory",
"surname": "Dudek",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "crv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-06-01T00:00:00",
"pubType": "proceedings",
"pages": "456-463",
"year": "2016",
"issn": null,
"isbn": "978-1-5090-2491-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "2491a448",
"articleId": "12OmNyQpgYQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "2491a464",
"articleId": "12OmNrAdsEL",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccvw/2015/9711/0/5720a148",
"title": "Fusion of Inertial and Visual Measurements for RGB-D SLAM on Mobile Devices",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2015/5720a148/12OmNy7h36Q",
"parentPublication": {
"id": "proceedings/iccvw/2015/9711/0",
"title": "2015 IEEE International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000b974",
"title": "ICE-BA: Incremental, Consistent and Efficient Bundle Adjustment for Visual-Inertial SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000b974/17D45XH89pm",
"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/2022/9062/0/09956355",
"title": "Semantic Texture Complexity Model for Feature Generation and Selection in Visual SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2022/09956355/1IHpdEjUUZG",
"parentPublication": {
"id": "proceedings/icpr/2022/9062/0",
"title": "2022 26th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2019/3131/0/313100a574",
"title": "Mobile Photometric Stereo with Keypoint-Based SLAM for Dense 3D Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2019/313100a574/1ezREwjZfFe",
"parentPublication": {
"id": "proceedings/3dv/2019/3131/0",
"title": "2019 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cyberc/2019/2542/0/254200a131",
"title": "Contrast Limited Adaptive Histogram Equalization for an Advanced Stereo Visual SLAM System",
"doi": null,
"abstractUrl": "/proceedings-article/cyberc/2019/254200a131/1gjRXW2KHni",
"parentPublication": {
"id": "proceedings/cyberc/2019/2542/0",
"title": "2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412341",
"title": "Learning to Segment Dynamic Objects using SLAM Outliers",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412341/1tmjm0W44yQ",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2020/0497/0/049700a101",
"title": "Improved ORB-SLAM Based 3D Dense Reconstruction for Monocular Endoscopic Image",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2020/049700a101/1vg8aYQPZi8",
"parentPublication": {
"id": "proceedings/icvrv/2020/0497/0",
"title": "2020 International Conference on Virtual Reality and Visualization (ICVRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900c814",
"title": "Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900c814/1yeIHPaF1WU",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a171",
"title": "COVINS: Visual-Inertial SLAM for Centralized Collaboration",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a171/1yeQzCgd2GQ",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2021/2688/0/268800b362",
"title": "DSP-SLAM: Object Oriented SLAM with Deep Shape Priors",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2021/268800b362/1zWEhxN28YU",
"parentPublication": {
"id": "proceedings/3dv/2021/2688/0",
"title": "2021 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1qyxi3OgORy",
"title": "2020 International Conference on 3D Vision (3DV)",
"acronym": "3dv",
"groupId": "1800494",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1qyxjlMBUYw",
"doi": "10.1109/3DV50981.2020.00106",
"title": "FC-vSLAM: Integrating Feature Credibility in Visual SLAM",
"normalizedTitle": "FC-vSLAM: Integrating Feature Credibility in Visual SLAM",
"abstract": "Feature-based visual SLAM (vSLAM) systems compute camera poses and scene maps by detecting and matching 2D features, mostly being points and line segments, from image sequences. These systems often suffer from unreliable detections. In this paper, we define feature credibility (FC) for both points and line segments, formulate it into vSLAMs and develop an FC-vSLAM system based on the widely used ORB-SLAM framework. Compared with existing credibility definitions, the proposed one, considering both temporal observation stability and perspective triangulation reliability, is more comprehensive. We formulate the credibility in our SLAM system to suppress the influences from unreliable features on the pose and map optimization. We also present a way to improve the line end observations by their multi-view correspondences, to improve the integrity of the 3D maps. Experiments on both the TUM and 7-Scenes datasets demonstrate that our feature credibility and the multi-view line optimization are effective; the developed FC-vSLAM system outperforms existing popular feature-based systems in both localization and mapping.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Feature-based visual SLAM (vSLAM) systems compute camera poses and scene maps by detecting and matching 2D features, mostly being points and line segments, from image sequences. These systems often suffer from unreliable detections. In this paper, we define feature credibility (FC) for both points and line segments, formulate it into vSLAMs and develop an FC-vSLAM system based on the widely used ORB-SLAM framework. Compared with existing credibility definitions, the proposed one, considering both temporal observation stability and perspective triangulation reliability, is more comprehensive. We formulate the credibility in our SLAM system to suppress the influences from unreliable features on the pose and map optimization. We also present a way to improve the line end observations by their multi-view correspondences, to improve the integrity of the 3D maps. Experiments on both the TUM and 7-Scenes datasets demonstrate that our feature credibility and the multi-view line optimization are effective; the developed FC-vSLAM system outperforms existing popular feature-based systems in both localization and mapping.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Feature-based visual SLAM (vSLAM) systems compute camera poses and scene maps by detecting and matching 2D features, mostly being points and line segments, from image sequences. These systems often suffer from unreliable detections. In this paper, we define feature credibility (FC) for both points and line segments, formulate it into vSLAMs and develop an FC-vSLAM system based on the widely used ORB-SLAM framework. Compared with existing credibility definitions, the proposed one, considering both temporal observation stability and perspective triangulation reliability, is more comprehensive. We formulate the credibility in our SLAM system to suppress the influences from unreliable features on the pose and map optimization. We also present a way to improve the line end observations by their multi-view correspondences, to improve the integrity of the 3D maps. Experiments on both the TUM and 7-Scenes datasets demonstrate that our feature credibility and the multi-view line optimization are effective; the developed FC-vSLAM system outperforms existing popular feature-based systems in both localization and mapping.",
"fno": "812800a959",
"keywords": [
"Cameras",
"Computational Geometry",
"Feature Extraction",
"Image Matching",
"Image Sequences",
"Optimisation",
"Pose Estimation",
"SLAM Robots",
"Multiview Line Optimization",
"Feature Credibility",
"Feature Based Visual SLAM Systems",
"Scene Maps",
"Line Segments",
"Unreliable Detections",
"ORB SLAM Framework",
"Temporal Observation Stability",
"Perspective Triangulation Reliability",
"SLAM System",
"Unreliable Features",
"Line End Observations",
"Credibility Definitions",
"FC V SLAM System",
"Camera Pose Computation",
"2 D Feature Detection",
"2 D Feature Matching",
"Image Sequences",
"7 Scenes Dataset",
"TUM Dataset",
"Three Dimensional Displays",
"Feature Extraction",
"Simultaneous Localization And Mapping",
"Optimization",
"Cameras",
"Visualization",
"Location Awareness"
],
"authors": [
{
"affiliation": "Beijing University of Technology",
"fullName": "Shuai Xie",
"givenName": "Shuai",
"surname": "Xie",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Beijing University of Technology",
"fullName": "Wei Ma",
"givenName": "Wei",
"surname": "Ma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Peking University",
"fullName": "Qiuyuan Wang",
"givenName": "Qiuyuan",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Beijing University of Technology",
"fullName": "Ruchang Xu",
"givenName": "Ruchang",
"surname": "Xu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Peking University",
"fullName": "Hongbin Zha",
"givenName": "Hongbin",
"surname": "Zha",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "3dv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-11-01T00:00:00",
"pubType": "proceedings",
"pages": "959-967",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-8128-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "812800a949",
"articleId": "1qyxnEJMyoo",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "812800a968",
"articleId": "1qyxkzWv9JK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cvprw/2018/6100/0/610000a371",
"title": "Mask-SLAM: Robust Feature-Based Monocular SLAM by Masking Using Semantic Segmentation",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2018/610000a371/17D45Wda7fo",
"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": "trans/tm/5555/01/09866716",
"title": "Edge Assisted Mobile Semantic Visual SLAM",
"doi": null,
"abstractUrl": "/journal/tm/5555/01/09866716/1G6fkNkibbq",
"parentPublication": {
"id": "trans/tm",
"title": "IEEE Transactions on Mobile Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdiime/2022/9009/0/900900a157",
"title": "Research of Visual SLAM in Dynamic Environment using Convolutional Neural Network",
"doi": null,
"abstractUrl": "/proceedings-article/icdiime/2022/900900a157/1Iz536ZwFBm",
"parentPublication": {
"id": "proceedings/icdiime/2022/9009/0",
"title": "2022 International Conference on 3D Immersion, Interaction and Multi-sensory Experiences (ICDIIME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mass/2022/7180/0/718000a458",
"title": "PRE-SLAM: Persistence Reasoning in Edge-assisted Visual SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/mass/2022/718000a458/1JeEgLf35ks",
"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/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": "proceedings/icoin/2023/6268/0/10048921",
"title": "Offloading Visual SLAM Processing to the Edge: An Energy Perspective",
"doi": null,
"abstractUrl": "/proceedings-article/icoin/2023/10048921/1KYsNUybYRO",
"parentPublication": {
"id": "proceedings/icoin/2023/6268/0",
"title": "2023 International Conference on Information Networking (ICOIN)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigcomp/2020/6034/0/603400a474",
"title": "A Comparative Study of Recent Real Time Semantic Segmentation Algorithms for Visual Semantic SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/bigcomp/2020/603400a474/1jdDA8d1ypy",
"parentPublication": {
"id": "proceedings/bigcomp/2020/6034/0",
"title": "2020 IEEE International Conference on Big Data and Smart Computing (BigComp)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcce/2020/2314/0/231400c072",
"title": "VSLAM based on instance segmentation",
"doi": null,
"abstractUrl": "/proceedings-article/icmcce/2020/231400c072/1tzyLKi1FGo",
"parentPublication": {
"id": "proceedings/icmcce/2020/2314/0",
"title": "2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icaie/2021/2492/0/249200a226",
"title": "A Review of Visual SLAM Based on Unmanned Systems",
"doi": null,
"abstractUrl": "/proceedings-article/icaie/2021/249200a226/1wV1DLLTFUQ",
"parentPublication": {
"id": "proceedings/icaie/2021/2492/0",
"title": "2021 2nd International Conference on Artificial Intelligence and Education (ICAIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icwcsg/2021/2598/0/259800a327",
"title": "Visual SLAM algorithm based on RGB-D",
"doi": null,
"abstractUrl": "/proceedings-article/icwcsg/2021/259800a327/1yQB8ogDPRm",
"parentPublication": {
"id": "proceedings/icwcsg/2021/2598/0",
"title": "2021 International Conference on Wireless Communications and Smart Grid (ICWCSG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1xCb6DPhKiA",
"title": "2021 24th Euromicro Conference on Digital System Design (DSD)",
"acronym": "dsd",
"groupId": "1000208",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1xCbcVVffhK",
"doi": "10.1109/DSD53832.2021.00013",
"title": "An efficient FPGA-based co-processor for feature point detection and tracking",
"normalizedTitle": "An efficient FPGA-based co-processor for feature point detection and tracking",
"abstract": "The use of mobile agents is propagating throughout various industries. Nevertheless, the success of novel applications relies on the utilization of novel computing platforms and algorithms, including acceleration technology and onboard localization. We propose an FPGA-based sparse optical flow computing accelerator based on the FAST feature detection and BRIEF feature descriptor. The correspondences are found by splitting the image into static regions, where for each region, the feature points are tracked in-between the frames. The accelerator is fully pipelined and achieves a performance of 300 fps with VGA resolution images. The experimentation with the default configuration of the accelerator shows to support a reliable measurement of frame-to-frame image plane rotation of 9 degrees and translation of 24 pixels, with the total error below 0.4 degrees and 0.16 pixels.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The use of mobile agents is propagating throughout various industries. Nevertheless, the success of novel applications relies on the utilization of novel computing platforms and algorithms, including acceleration technology and onboard localization. We propose an FPGA-based sparse optical flow computing accelerator based on the FAST feature detection and BRIEF feature descriptor. The correspondences are found by splitting the image into static regions, where for each region, the feature points are tracked in-between the frames. The accelerator is fully pipelined and achieves a performance of 300 fps with VGA resolution images. The experimentation with the default configuration of the accelerator shows to support a reliable measurement of frame-to-frame image plane rotation of 9 degrees and translation of 24 pixels, with the total error below 0.4 degrees and 0.16 pixels.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The use of mobile agents is propagating throughout various industries. Nevertheless, the success of novel applications relies on the utilization of novel computing platforms and algorithms, including acceleration technology and onboard localization. We propose an FPGA-based sparse optical flow computing accelerator based on the FAST feature detection and BRIEF feature descriptor. The correspondences are found by splitting the image into static regions, where for each region, the feature points are tracked in-between the frames. The accelerator is fully pipelined and achieves a performance of 300 fps with VGA resolution images. The experimentation with the default configuration of the accelerator shows to support a reliable measurement of frame-to-frame image plane rotation of 9 degrees and translation of 24 pixels, with the total error below 0.4 degrees and 0.16 pixels.",
"fno": "270300a024",
"keywords": [
"Feature Extraction",
"Field Programmable Gate Arrays",
"Image Resolution",
"Image Sequences",
"Efficient FPGA Based Co Processor",
"Frame To Frame Image Plane Rotation",
"VGA Resolution Images",
"Feature Points",
"Static Regions",
"Sparse Optical Flow",
"Onboard Localization",
"Acceleration Technology",
"Novel Computing Platforms",
"Mobile Agents",
"Feature Point Detection",
"Location Awareness",
"Image Resolution",
"Simultaneous Localization And Mapping",
"Target Tracking",
"Life Estimation",
"Streaming Media",
"Feature Extraction",
"Optical Flow",
"Acceleration",
"FAST",
"BRIEF",
"FPGA",
"So C"
],
"authors": [
{
"affiliation": "Institute of Electronics and Computer Science,Robotics and Machine Perception Laboratory,Riga,Latvia,LV-1006",
"fullName": "Toms Stūrmanis",
"givenName": "Toms",
"surname": "Stūrmanis",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Institute of Electronics and Computer Science,Robotics and Machine Perception Laboratory,Riga,Latvia,LV-1006",
"fullName": "Rihards Novickis",
"givenName": "Rihards",
"surname": "Novickis",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "dsd",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-09-01T00:00:00",
"pubType": "proceedings",
"pages": "24-29",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-2703-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "270300a018",
"articleId": "1xCb9t3bnzO",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "270300a030",
"articleId": "1xCbd2rJDDG",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2017/1032/0/1032d923",
"title": "Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/1032d923/12OmNApLGr1",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2017/1034/0/1034a851",
"title": "Semantic Texture for Robust Dense Tracking",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2017/1034a851/12OmNwCsdKC",
"parentPublication": {
"id": "proceedings/iccvw/2017/1034/0",
"title": "2017 IEEE International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2017/2610/0/261001a347",
"title": "Direct Multichannel Tracking",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2017/261001a347/12OmNxWui9l",
"parentPublication": {
"id": "proceedings/3dv/2017/2610/0",
"title": "2017 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2014/4985/0/06835731",
"title": "Segmentation and tracking of partial planar templates",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2014/06835731/12OmNzTYC2D",
"parentPublication": {
"id": "proceedings/wacv/2014/4985/0",
"title": "2014 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a077",
"title": "Point cloud to BIM registration for robot localization and Augmented Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a077/1J7WmGwePGU",
"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/mass/2022/7180/0/718000a458",
"title": "PRE-SLAM: Persistence Reasoning in Edge-assisted Visual SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/mass/2022/718000a458/1JeEgLf35ks",
"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": "trans/tc/5555/01/09994649",
"title": "An Energy Efficient and Runtime Reconfigurable Accelerator for Robotic Localization",
"doi": null,
"abstractUrl": "/journal/tc/5555/01/09994649/1JgwdIifWfe",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2020/02/08946871",
"title": "A Flexible and Efficient Real-Time ORB-Based Full-HD Image Feature Extraction Accelerator",
"doi": null,
"abstractUrl": "/journal/si/2020/02/08946871/1gd8RqQsqhq",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fccm/2020/5803/0/09114849",
"title": "CNN-based Feature-point Extraction for Real-time Visual SLAM on Embedded FPGA",
"doi": null,
"abstractUrl": "/proceedings-article/fccm/2020/09114849/1kzGayKjqW4",
"parentPublication": {
"id": "proceedings/fccm/2020/5803/0",
"title": "2020 IEEE 28th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2020/8128/0/812800a959",
"title": "FC-vSLAM: Integrating Feature Credibility in Visual SLAM",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2020/812800a959/1qyxjlMBUYw",
"parentPublication": {
"id": "proceedings/3dv/2020/8128/0",
"title": "2020 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1zL1CunfrGM",
"title": "2021 International Conference on Intelligent Computing, Automation and Applications (ICAA)",
"acronym": "icaa",
"groupId": "1842748",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1zL1Mh20NnG",
"doi": "10.1109/ICAA53760.2021.00034",
"title": "Improved Loop Detection Method Based on ICP and NDT Registration Algorithm",
"normalizedTitle": "Improved Loop Detection Method Based on ICP and NDT Registration Algorithm",
"abstract": "In the process of constructing a three-dimensional environment in a large scene, the problem of large accumulated errors is likely to occur, which makes it impossible to construct a globally consistent map. To solve this problem, this paper proposes a loop detection method based on NDT and ICP registration algorithms. The NDT algorithm is used for the initial registration, which can quickly reduce the number of the candidate loop frames and provide the initial pose. On the basis of the initial pose provided by the NDT algorithm, ICP algorithom is performed to determine the precise loopback frame. In this paper, the proposed loop detection algorithm is added to the SLAM framework, verified on the inspection robot platform, and compared with the LOAM and LeGO-LOAM algorithms. Experiments show that the proposed loop detection algorithm can effectively eliminate the cumulative error in the construction of the large environment, build a global consistency map, and have high realtime performance.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In the process of constructing a three-dimensional environment in a large scene, the problem of large accumulated errors is likely to occur, which makes it impossible to construct a globally consistent map. To solve this problem, this paper proposes a loop detection method based on NDT and ICP registration algorithms. The NDT algorithm is used for the initial registration, which can quickly reduce the number of the candidate loop frames and provide the initial pose. On the basis of the initial pose provided by the NDT algorithm, ICP algorithom is performed to determine the precise loopback frame. In this paper, the proposed loop detection algorithm is added to the SLAM framework, verified on the inspection robot platform, and compared with the LOAM and LeGO-LOAM algorithms. Experiments show that the proposed loop detection algorithm can effectively eliminate the cumulative error in the construction of the large environment, build a global consistency map, and have high realtime performance.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In the process of constructing a three-dimensional environment in a large scene, the problem of large accumulated errors is likely to occur, which makes it impossible to construct a globally consistent map. To solve this problem, this paper proposes a loop detection method based on NDT and ICP registration algorithms. The NDT algorithm is used for the initial registration, which can quickly reduce the number of the candidate loop frames and provide the initial pose. On the basis of the initial pose provided by the NDT algorithm, ICP algorithom is performed to determine the precise loopback frame. In this paper, the proposed loop detection algorithm is added to the SLAM framework, verified on the inspection robot platform, and compared with the LOAM and LeGO-LOAM algorithms. Experiments show that the proposed loop detection algorithm can effectively eliminate the cumulative error in the construction of the large environment, build a global consistency map, and have high realtime performance.",
"fno": "373000a145",
"keywords": [
"Image Registration",
"Inspection",
"Iterative Methods",
"Mobile Robots",
"Robot Vision",
"SLAM Robots",
"Loop Detection Method",
"NDT Registration Algorithm",
"Three Dimensional Environment",
"Accumulated Errors",
"Globally Consistent Map",
"NDT Algorithm",
"Initial Registration",
"Candidate Loop Frames",
"ICP Algorithom",
"Precise Loopback Frame",
"Loop Detection Algorithm",
"Le GO LOAM Algorithms",
"Global Consistency Map",
"Simultaneous Localization And Mapping",
"Automation",
"Inspection",
"Detection Algorithms",
"Robots"
],
"authors": [
{
"affiliation": "School of Automation,Southeast University,NanJing,JiangSu",
"fullName": "Xue Bao",
"givenName": "Xue",
"surname": "Bao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Automation,Southeast University,NanJing,JiangSu",
"fullName": "Yingzi Tan",
"givenName": "Yingzi",
"surname": "Tan",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icaa",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-06-01T00:00:00",
"pubType": "proceedings",
"pages": "145-150",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-3730-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "373000a140",
"articleId": "1zL1I5YcCd2",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "373000a151",
"articleId": "1zL1YQhsqyI",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ecmsm/2013/6298/0/06648973",
"title": "ICP-SLAM methods implementation on a bi-steerable mobile robot",
"doi": null,
"abstractUrl": "/proceedings-article/ecmsm/2013/06648973/12OmNBVIUA9",
"parentPublication": {
"id": "proceedings/ecmsm/2013/6298/0",
"title": "2013 IEEE 11th International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aqtr/2012/0701/0/06237755",
"title": "Simultaneous localization and mapping using adaptive appearance based loop-closing detection",
"doi": null,
"abstractUrl": "/proceedings-article/aqtr/2012/06237755/12OmNqIzh1x",
"parentPublication": {
"id": "proceedings/aqtr/2012/0701/0",
"title": "International Conference on Automation, Quality and Testing, Robotics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecmsm/2015/6972/0/07208683",
"title": "FAST ICP-SLAM for a bi-steerable mobile robot in large environments",
"doi": null,
"abstractUrl": "/proceedings-article/ecmsm/2015/07208683/12OmNz2C1rh",
"parentPublication": {
"id": "proceedings/ecmsm/2015/6972/0",
"title": "2015 IEEE International Workshop of Electronics, Control, Measurement, Signals and their application to Mechatronics (ECMSM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/irc/2019/9245/0/924500a417",
"title": "Point-Cloud Mapping and Merging Using Mobile Laser Scanner",
"doi": null,
"abstractUrl": "/proceedings-article/irc/2019/924500a417/18M7dgLsWCk",
"parentPublication": {
"id": "proceedings/irc/2019/9245/0",
"title": "2019 Third IEEE International Conference on Robotic Computing (IRC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscer/2022/8478/0/847800a161",
"title": "Point cloud registration method based on 3DMatch network and improved ISS algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/iscer/2022/847800a161/1HbbuMbRyqA",
"parentPublication": {
"id": "proceedings/iscer/2022/8478/0",
"title": "2022 International Symposium on Control Engineering and Robotics (ISCER)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2019/6092/0/609200a132",
"title": "Point Cloud Registration Algorithm Based on Combination of NDT and PLICP",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2019/609200a132/1i5m6DnRNsc",
"parentPublication": {
"id": "proceedings/cis/2019/6092/0",
"title": "2019 15th International Conference on Computational Intelligence and Security (CIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccnea/2020/7083/0/708300a106",
"title": "Comparison of Initial Registration Algorithms Suitable for ICP Algorithm",
"doi": null,
"abstractUrl": "/proceedings-article/iccnea/2020/708300a106/1oCn59P9wsM",
"parentPublication": {
"id": "proceedings/iccnea/2020/7083/0",
"title": "2020 International Conference on Computer Network, Electronic and Automation (ICCNEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvidl/2020/9481/0/948100a360",
"title": "A SLAM Loop Closure Algorithm of BoW Incorporating the Gray Level of Pixel",
"doi": null,
"abstractUrl": "/proceedings-article/cvidl/2020/948100a360/1pbe5dauC8E",
"parentPublication": {
"id": "proceedings/cvidl/2020/9481/0",
"title": "2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiea/2021/3265/0/326500a269",
"title": "A loop closure detection method based on semantic segmentation and convolutional neural network",
"doi": null,
"abstractUrl": "/proceedings-article/aiea/2021/326500a269/1wzsBM0pXeU",
"parentPublication": {
"id": "proceedings/aiea/2021/3265/0",
"title": "2021 International Conference on Artificial Intelligence and Electromechanical Automation (AIEA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icisce/2020/6406/0/640600c453",
"title": "Visual closed loop in laser SLAM research",
"doi": null,
"abstractUrl": "/proceedings-article/icisce/2020/640600c453/1x3kvwmfPmU",
"parentPublication": {
"id": "proceedings/icisce/2020/6406/0",
"title": "2020 7th International Conference on Information Science and Control Engineering (ICISCE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1BmEezmpGrm",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"acronym": "iccv",
"groupId": "1000149",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1BmL39Zkm9G",
"doi": "10.1109/ICCV48922.2021.01284",
"title": "Multiresolution Deep Implicit Functions for 3D Shape Representation",
"normalizedTitle": "Multiresolution Deep Implicit Functions for 3D Shape Representation",
"abstract": "We introduce Multiresolution Deep Implicit Functions (MDIF), a hierarchical representation that can recover fine geometry detail, while being able to perform global operations such as shape completion. Our model represents a complex 3D shape with a hierarchy of latent grids, which can be decoded into different levels of detail and also achieve better accuracy. For shape completion, we propose latent grid dropout to simulate partial data in the latent space and therefore defer the completing functionality to the decoder side. This along with our multires design significantly improves the shape completion quality under decoder-only latent optimization. To the best of our knowledge, MDIF is the first deep implicit function model that can at the same time (1) represent different levels of detail and allow progressive decoding; (2) support both encoder-decoder inference and decoder-only latent optimization, and fulfill multiple applications; (3) perform detailed decoder-only shape completion. Experiments demonstrate its superior performance against prior art in various 3D reconstruction tasks.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We introduce Multiresolution Deep Implicit Functions (MDIF), a hierarchical representation that can recover fine geometry detail, while being able to perform global operations such as shape completion. Our model represents a complex 3D shape with a hierarchy of latent grids, which can be decoded into different levels of detail and also achieve better accuracy. For shape completion, we propose latent grid dropout to simulate partial data in the latent space and therefore defer the completing functionality to the decoder side. This along with our multires design significantly improves the shape completion quality under decoder-only latent optimization. To the best of our knowledge, MDIF is the first deep implicit function model that can at the same time (1) represent different levels of detail and allow progressive decoding; (2) support both encoder-decoder inference and decoder-only latent optimization, and fulfill multiple applications; (3) perform detailed decoder-only shape completion. Experiments demonstrate its superior performance against prior art in various 3D reconstruction tasks.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We introduce Multiresolution Deep Implicit Functions (MDIF), a hierarchical representation that can recover fine geometry detail, while being able to perform global operations such as shape completion. Our model represents a complex 3D shape with a hierarchy of latent grids, which can be decoded into different levels of detail and also achieve better accuracy. For shape completion, we propose latent grid dropout to simulate partial data in the latent space and therefore defer the completing functionality to the decoder side. This along with our multires design significantly improves the shape completion quality under decoder-only latent optimization. To the best of our knowledge, MDIF is the first deep implicit function model that can at the same time (1) represent different levels of detail and allow progressive decoding; (2) support both encoder-decoder inference and decoder-only latent optimization, and fulfill multiple applications; (3) perform detailed decoder-only shape completion. Experiments demonstrate its superior performance against prior art in various 3D reconstruction tasks.",
"fno": "281200n3067",
"keywords": [
"Geometry",
"Point Cloud Compression",
"Solid Modeling",
"Three Dimensional Displays",
"Shape",
"Superresolution",
"Decoding"
],
"authors": [
{
"affiliation": "Google",
"fullName": "Zhang Chen",
"givenName": "Zhang",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Yinda Zhang",
"givenName": "Yinda",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Kyle Genova",
"givenName": "Kyle",
"surname": "Genova",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Sean Fanello",
"givenName": "Sean",
"surname": "Fanello",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Sofien Bouaziz",
"givenName": "Sofien",
"surname": "Bouaziz",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Christian Häne",
"givenName": "Christian",
"surname": "Häne",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Ruofei Du",
"givenName": "Ruofei",
"surname": "Du",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Cem Keskin",
"givenName": "Cem",
"surname": "Keskin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Thomas Funkhouser",
"givenName": "Thomas",
"surname": "Funkhouser",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Google",
"fullName": "Danhang Tang",
"givenName": "Danhang",
"surname": "Tang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-10-01T00:00:00",
"pubType": "proceedings",
"pages": "13067-13076",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-2812-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "281200n3056",
"articleId": "1BmIHpCUsSY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "281200n3077",
"articleId": "1BmLhm8T88E",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"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": "trans/tg/5555/01/09729524",
"title": "Unsupervised Category-Specific Partial Point Set Registration via Joint Shape Completion and Registration",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09729524/1Bya8dlokw0",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2022/8739/0/873900c957",
"title": "Multimodal Shape Completion via Implicit Maximum Likelihood Estimation",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2022/873900c957/1G56CoCgc5W",
"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": "proceedings/cvpr/2022/6946/0/694600f533",
"title": "Learning a Structured Latent Space for Unsupervised Point Cloud Completion",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600f533/1H0KOsU2FZC",
"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/cvpr/2022/6946/0/694600g229",
"title": "ShapeFormer: Transformer-based Shape Completion via Sparse Representation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600g229/1H1hxuCj6xy",
"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/cvpr/2022/6946/0/694600s8593",
"title": "UNIST: Unpaired Neural Implicit Shape Translation Network",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600s8593/1H1kv6nHUFq",
"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/tg/5555/01/10093999",
"title": "ANISE: Assembly-based Neural Implicit Surface rEconstruction",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10093999/1M80HueHnJS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800e856",
"title": "Local Deep Implicit Functions for 3D Shape",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800e856/1m3ngGoPx5u",
"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/2021/2688/0/268800b269",
"title": "GASCN: Graph Attention Shape Completion Network",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2021/268800b269/1zWEc53kN9u",
"parentPublication": {
"id": "proceedings/3dv/2021/2688/0",
"title": "2021 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2021/2688/0/268800b054",
"title": "AIR-Nets: An Attention-Based Framework for Locally Conditioned Implicit Representations",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2021/268800b054/1zWEkt7SgUg",
"parentPublication": {
"id": "proceedings/3dv/2021/2688/0",
"title": "2021 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1BmEezmpGrm",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"acronym": "iccv",
"groupId": "1000149",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1BmLiNnsKo8",
"doi": "10.1109/ICCV48922.2021.01242",
"title": "Deep Implicit Surface Point Prediction Networks",
"normalizedTitle": "Deep Implicit Surface Point Prediction Networks",
"abstract": "Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit representations using meshes and point clouds. However, most such approaches focus on representing closed shapes. Unsigned distance function (UDF) based approaches have been proposed recently as a promising alternative to represent both open and closed shapes. However, since the gradients of UDFs vanish on the surface, it is challenging to estimate local (differential) geometric properties like the normals and tangent planes which are needed for many downstream applications in vision and graphics. There are additional challenges in computing these properties efficiently with a low-memory footprint. This paper presents a novel approach that models such surfaces using a new class of implicit representations called the closest surface-point (CSP) representation. We show that CSP allows us to represent complex surfaces of any topology (open or closed) with high fidelity. It also allows for accurate and efficient computation of local geometric properties. We further demonstrate that it leads to efficient implementation of downstream algorithms like sphere-tracing for rendering the 3D surface as well as to create explicit mesh-based representations. Extensive experimental evaluation on the ShapeNet dataset validate the above contributions with results surpassing the state-of-the-art. Code and data are available at https://sites.google.com/view/cspnet.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit representations using meshes and point clouds. However, most such approaches focus on representing closed shapes. Unsigned distance function (UDF) based approaches have been proposed recently as a promising alternative to represent both open and closed shapes. However, since the gradients of UDFs vanish on the surface, it is challenging to estimate local (differential) geometric properties like the normals and tangent planes which are needed for many downstream applications in vision and graphics. There are additional challenges in computing these properties efficiently with a low-memory footprint. This paper presents a novel approach that models such surfaces using a new class of implicit representations called the closest surface-point (CSP) representation. We show that CSP allows us to represent complex surfaces of any topology (open or closed) with high fidelity. It also allows for accurate and efficient computation of local geometric properties. We further demonstrate that it leads to efficient implementation of downstream algorithms like sphere-tracing for rendering the 3D surface as well as to create explicit mesh-based representations. Extensive experimental evaluation on the ShapeNet dataset validate the above contributions with results surpassing the state-of-the-art. Code and data are available at https://sites.google.com/view/cspnet.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Deep neural representations of 3D shapes as implicit functions have been shown to produce high fidelity models surpassing the resolution-memory trade-off faced by the explicit representations using meshes and point clouds. However, most such approaches focus on representing closed shapes. Unsigned distance function (UDF) based approaches have been proposed recently as a promising alternative to represent both open and closed shapes. However, since the gradients of UDFs vanish on the surface, it is challenging to estimate local (differential) geometric properties like the normals and tangent planes which are needed for many downstream applications in vision and graphics. There are additional challenges in computing these properties efficiently with a low-memory footprint. This paper presents a novel approach that models such surfaces using a new class of implicit representations called the closest surface-point (CSP) representation. We show that CSP allows us to represent complex surfaces of any topology (open or closed) with high fidelity. It also allows for accurate and efficient computation of local geometric properties. We further demonstrate that it leads to efficient implementation of downstream algorithms like sphere-tracing for rendering the 3D surface as well as to create explicit mesh-based representations. Extensive experimental evaluation on the ShapeNet dataset validate the above contributions with results surpassing the state-of-the-art. Code and data are available at https://sites.google.com/view/cspnet.",
"fno": "281200m2633",
"keywords": [
"Point Cloud Compression",
"Solid Modeling",
"Three Dimensional Displays",
"Shape",
"Computational Modeling",
"Predictive Models",
"Rendering Computer Graphics",
"3 D From A Single Image And Shape From X",
"Representation Learning",
"Stereo",
"3 D From Multiview And Other Sensors"
],
"authors": [
{
"affiliation": "Carnegie Mellon University,Pittsburgh,PA,USA",
"fullName": "Rahul Venkatesh",
"givenName": "Rahul",
"surname": "Venkatesh",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Indian Institute of Science,Bengaluru,India",
"fullName": "Tejan Karmali",
"givenName": "Tejan",
"surname": "Karmali",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Verisk Analytics,Jersey City,NJ,USA",
"fullName": "Sarthak Sharma",
"givenName": "Sarthak",
"surname": "Sharma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Verisk Analytics,Jersey City,NJ,USA",
"fullName": "Aurobrata Ghosh",
"givenName": "Aurobrata",
"surname": "Ghosh",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Indian Institute of Science,Bengaluru,India",
"fullName": "R. Venkatesh Babu",
"givenName": "R. Venkatesh",
"surname": "Babu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University,Pittsburgh,PA,USA",
"fullName": "Lászlό A. Jeni",
"givenName": "Lászlό A.",
"surname": "Jeni",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Verisk Analytics,Jersey City,NJ,USA",
"fullName": "Maneesh Singh",
"givenName": "Maneesh",
"surname": "Singh",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-10-01T00:00:00",
"pubType": "proceedings",
"pages": "12633-12642",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-2812-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "281200m2622",
"articleId": "1BmGGqXuyac",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "281200m2643",
"articleId": "1BmKY1g44Kc",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2021/2812/0/281200g752",
"title": "DeepCAD: A Deep Generative Network for Computer-Aided Design Models",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200g752/1BmHANMNcoE",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmew/2022/7218/0/09859360",
"title": "Deep Point Cloud Normal Estimation via Triplet Learning (Demonstration)",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2022/09859360/1G4F1NSQSEo",
"parentPublication": {
"id": "proceedings/icmew/2022/7218/0",
"title": "2022 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2022/8563/0/09859844",
"title": "Deep Point Cloud Normal Estimation Via Triplet Learning",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2022/09859844/1G9EiyfHOKY",
"parentPublication": {
"id": "proceedings/icme/2022/8563/0",
"title": "2022 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600t9301",
"title": "DiGS : Divergence guided shape implicit neural representation for unoriented point clouds",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600t9301/1H0KAEvXEdy",
"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/cvpr/2022/6946/0/694600l1840",
"title": "Point2Cyl: Reverse Engineering 3D Objects from Point Clouds to Extrusion Cylinders",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600l1840/1H1hCbGOBbi",
"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/cvpr/2022/6946/0/694600s8644",
"title": "DeepCurrents: Learning Implicit Representations of Shapes with Boundaries",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600s8644/1H1hvx4136E",
"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/cvpr/2022/6946/0/694600s8920",
"title": "Surface Representation for Point Clouds",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600s8920/1H1jmGGv0eQ",
"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/cvpr/2022/6946/0/694600t9291",
"title": "Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600t9291/1H1mPsA11XW",
"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/tg/5555/01/10093999",
"title": "ANISE: Assembly-based Neural Implicit Surface rEconstruction",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10093999/1M80HueHnJS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2020/8128/0/812800a452",
"title": "Learning Implicit Surface Light Fields",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2020/812800a452/1qyxkR2YxGM",
"parentPublication": {
"id": "proceedings/3dv/2020/8128/0",
"title": "2020 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1H1gVMlkl32",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1H0KHzfm1Ta",
"doi": "10.1109/CVPR52688.2022.01249",
"title": "GIFS: Neural Implicit Function for General Shape Representation",
"normalizedTitle": "GIFS: Neural Implicit Function for General Shape Representation",
"abstract": "Recent development of neural implicit function has shown tremendous success on high-quality 3D shape re-construction. However, most works divide the space into inside and outside of the shape, which limits their repre-senting power to single-layer and watertight shapes. This limitation leads to tedious data processing (converting non-watertight raw data to watertight) as well as the incapability of representing general object shapes in the real world. In this work, we propose a novel method to represent general shapes including non-watertight shapes and shapes with multi-layer surfaces. We introduce General Implicit Function for 3D Shape (GIFS), which models the relationships between every two points instead of the relationships between points and surfaces. Instead of dividing 3D space into predefined inside-outside regions, GIFS encodes whether two points are separated by any surface. Experiments on ShapeNet show that GIFS outperforms previous state-of-the-art methods in terms of reconstruction quality, rendering efficiency, and visual fidelity. Project page is available at https://jianglongye.com/gifs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recent development of neural implicit function has shown tremendous success on high-quality 3D shape re-construction. However, most works divide the space into inside and outside of the shape, which limits their repre-senting power to single-layer and watertight shapes. This limitation leads to tedious data processing (converting non-watertight raw data to watertight) as well as the incapability of representing general object shapes in the real world. In this work, we propose a novel method to represent general shapes including non-watertight shapes and shapes with multi-layer surfaces. We introduce General Implicit Function for 3D Shape (GIFS), which models the relationships between every two points instead of the relationships between points and surfaces. Instead of dividing 3D space into predefined inside-outside regions, GIFS encodes whether two points are separated by any surface. Experiments on ShapeNet show that GIFS outperforms previous state-of-the-art methods in terms of reconstruction quality, rendering efficiency, and visual fidelity. Project page is available at https://jianglongye.com/gifs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recent development of neural implicit function has shown tremendous success on high-quality 3D shape re-construction. However, most works divide the space into inside and outside of the shape, which limits their repre-senting power to single-layer and watertight shapes. This limitation leads to tedious data processing (converting non-watertight raw data to watertight) as well as the incapability of representing general object shapes in the real world. In this work, we propose a novel method to represent general shapes including non-watertight shapes and shapes with multi-layer surfaces. We introduce General Implicit Function for 3D Shape (GIFS), which models the relationships between every two points instead of the relationships between points and surfaces. Instead of dividing 3D space into predefined inside-outside regions, GIFS encodes whether two points are separated by any surface. Experiments on ShapeNet show that GIFS outperforms previous state-of-the-art methods in terms of reconstruction quality, rendering efficiency, and visual fidelity. Project page is available at https://jianglongye.com/gifs.",
"fno": "694600m2819",
"keywords": [
"CAD",
"Computational Geometry",
"Computer Animation",
"Computer Vision",
"Feature Extraction",
"Image Recognition",
"Image Reconstruction",
"Image Representation",
"Knowledge Representation",
"Neural Nets",
"Object Recognition",
"Rendering Computer Graphics",
"Solid Modelling",
"General Object Shapes",
"General Shapes",
"Nonwatertight Shapes",
"Multilayer Surfaces",
"General Implicit Function",
"Neural Implicit Function",
"General Shape Representation",
"Tremendous Success",
"High Quality 3 D Shape",
"Repre Senting Power",
"Watertight Shapes",
"Tedious Data Processing",
"Converting Nonwatertight Raw Data",
"Surface Reconstruction",
"Solid Modeling",
"Three Dimensional Displays",
"Shape",
"Neural Networks",
"Visual Effects",
"Rendering Computer Graphics"
],
"authors": [
{
"affiliation": "UC San Diego",
"fullName": "Jianglong Ye",
"givenName": "Jianglong",
"surname": "Ye",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "TuSimple",
"fullName": "Yuntao Chen",
"givenName": "Yuntao",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "TuSimple",
"fullName": "Naiyan Wang",
"givenName": "Naiyan",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "UC San Diego",
"fullName": "Xiaolong Wang",
"givenName": "Xiaolong",
"surname": "Wang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-06-01T00:00:00",
"pubType": "proceedings",
"pages": "12819-12829",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6946-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1H0KHuAontu",
"name": "pcvpr202269460-09879357s1-mm_694600m2819.zip",
"size": "1.42 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pcvpr202269460-09879357s1-mm_694600m2819.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "694600m2809",
"articleId": "1H1hLUvZH0c",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "694600m2830",
"articleId": "1H1kbtVJZbq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icpr/2008/2174/0/04761591",
"title": "3D shape reconstruction from incomplete silhouettes in multiple frames",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2008/04761591/12OmNy5zsoX",
"parentPublication": {
"id": "proceedings/icpr/2008/2174/0",
"title": "ICPR 2008 19th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2018/07/07956272",
"title": "Sparse Geometric Representation Through Local Shape Probing",
"doi": null,
"abstractUrl": "/journal/tg/2018/07/07956272/13rRUB7a1g1",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2018/6100/0/610000a516",
"title": "Principal Curvature Guided Surface Geometry Aware Global Shape Representation",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2018/610000a516/17D45XacGiC",
"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/iccv/2021/2812/0/281200m2426",
"title": "3DIAS: 3D Shape Reconstruction with Implicit Algebraic Surfaces",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200m2426/1BmI9u6tRSw",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09797843",
"title": "Learning Implicit Glyph Shape Representation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09797843/1EfIX5LNd5e",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09969571",
"title": "Vox-Surf: Voxel-Based Implicit Surface Representation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09969571/1IMidH7hZhC",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2022/5670/0/567000a526",
"title": "Any-Shot GIN: Generalizing Implicit Networks for Reconstructing Novel Classes",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2022/567000a526/1KYswF3kEsE",
"parentPublication": {
"id": "proceedings/3dv/2022/5670/0",
"title": "2022 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800e856",
"title": "Local Deep Implicit Functions for 3D Shape",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800e856/1m3ngGoPx5u",
"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/2020/7168/0/716800h628",
"title": "DualSDF: Semantic Shape Manipulation Using a Two-Level Representation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800h628/1m3ns8ZCtH2",
"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/2020/7168/0/716800b248",
"title": "SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimization",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800b248/1m3nwOmON4Q",
"parentPublication": {
"id": "proceedings/cvpr/2020/7168/0",
"title": "2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1H1gVMlkl32",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1H1kv6nHUFq",
"doi": "10.1109/CVPR52688.2022.01806",
"title": "UNIST: Unpaired Neural Implicit Shape Translation Network",
"normalizedTitle": "UNIST: Unpaired Neural Implicit Shape Translation Network",
"abstract": "We introduce UNIST, the first deep neural implicit model for general-purpose, unpaired shape-to-shape translation, in both 2D and 3D domains. Our model is built on autoencoding implicit fields, rather than point clouds which represents the state of the art. Furthermore, our translation network is trained to perform the task over a latent grid representation which combines the merits of both latent-space processing and position awareness, to not only enable drastic shape transforms but also well preserve spatial features and fine local details for natural shape translations. With the same network architecture and only dictated by the input domain pairs, our model can learn both style-preserving content alteration and content-preserving style transfer. We demonstrate the generality and quality of the translation results, and compare them to well-known baselines. Code is available at https://qiminchen.github.io/unist/.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We introduce UNIST, the first deep neural implicit model for general-purpose, unpaired shape-to-shape translation, in both 2D and 3D domains. Our model is built on autoencoding implicit fields, rather than point clouds which represents the state of the art. Furthermore, our translation network is trained to perform the task over a latent grid representation which combines the merits of both latent-space processing and position awareness, to not only enable drastic shape transforms but also well preserve spatial features and fine local details for natural shape translations. With the same network architecture and only dictated by the input domain pairs, our model can learn both style-preserving content alteration and content-preserving style transfer. We demonstrate the generality and quality of the translation results, and compare them to well-known baselines. Code is available at https://qiminchen.github.io/unist/.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We introduce UNIST, the first deep neural implicit model for general-purpose, unpaired shape-to-shape translation, in both 2D and 3D domains. Our model is built on autoencoding implicit fields, rather than point clouds which represents the state of the art. Furthermore, our translation network is trained to perform the task over a latent grid representation which combines the merits of both latent-space processing and position awareness, to not only enable drastic shape transforms but also well preserve spatial features and fine local details for natural shape translations. With the same network architecture and only dictated by the input domain pairs, our model can learn both style-preserving content alteration and content-preserving style transfer. We demonstrate the generality and quality of the translation results, and compare them to well-known baselines. Code is available at https://qiminchen.github.io/unist/.",
"fno": "694600s8593",
"keywords": [
"Deep Learning Artificial Intelligence",
"Feature Extraction",
"Image Representation",
"Solid Modelling",
"Content Preserving Style Transfer",
"Unpaired Neural Implicit Shape Translation Network",
"Deep Neural Implicit Model",
"Autoencoding Implicit Fields",
"Grid Representation",
"Latent Space Processing",
"Position Awareness",
"Network Architecture",
"UNIST",
"Shape Translations",
"Point Cloud Compression",
"Solid Modeling",
"Computer Vision",
"Three Dimensional Displays",
"Shape",
"Computational Modeling",
"Transforms"
],
"authors": [
{
"affiliation": "Simon Fraser University",
"fullName": "Qimin Chen",
"givenName": "Qimin",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Simon Fraser University",
"fullName": "Johannes Merz",
"givenName": "Johannes",
"surname": "Merz",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Autodesk AI Lab",
"fullName": "Aditya Sanghi",
"givenName": "Aditya",
"surname": "Sanghi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Autodesk AI Lab",
"fullName": "Hooman Shayani",
"givenName": "Hooman",
"surname": "Shayani",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Simon Fraser University",
"fullName": "Ali Mahdavi-Amiri",
"givenName": "Ali",
"surname": "Mahdavi-Amiri",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Simon Fraser University",
"fullName": "Hao Zhang",
"givenName": "Hao",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-06-01T00:00:00",
"pubType": "proceedings",
"pages": "18593-18601",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6946-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1H1kv1fvzR6",
"name": "pcvpr202269460-09879507s1-mm_694600s8593.zip",
"size": "13.9 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pcvpr202269460-09879507s1-mm_694600s8593.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "694600s8582",
"articleId": "1H1j9Ooe3Xq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "694600s8602",
"articleId": "1H1k6KZq9tm",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2022/0915/0/091500a277",
"title": "Mending Neural Implicit Modeling for 3D Vehicle Reconstruction in the Wild",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500a277/1B13xn8f1Bu",
"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/iccv/2021/2812/0/281200n3067",
"title": "Multiresolution Deep Implicit Functions for 3D Shape Representation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200n3067/1BmL39Zkm9G",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09797843",
"title": "Learning Implicit Glyph Shape Representation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09797843/1EfIX5LNd5e",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600t9301",
"title": "DiGS : Divergence guided shape implicit neural representation for unoriented point clouds",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600t9301/1H0KAEvXEdy",
"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/cvpr/2022/6946/0/694600m2819",
"title": "GIFS: Neural Implicit Function for General Shape Representation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600m2819/1H0KHzfm1Ta",
"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/2023/9346/0/9.346E214",
"title": "Learning Style Subspaces for Controllable Unpaired Domain Translation",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/9.346E214/1La4JaMnIgE",
"parentPublication": {
"id": "proceedings/wacv/2023/9346/0",
"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10093999",
"title": "ANISE: Assembly-based Neural Implicit Surface rEconstruction",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10093999/1M80HueHnJS",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900q6413",
"title": "Unpaired Image-to-Image Translation via Latent Energy Transport",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900q6413/1yeJeBYZ2YU",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2021/2688/0/268800b259",
"title": "Neighborhood-based Neural Implicit Reconstruction from Point Clouds",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2021/268800b259/1zWEcdiPXxK",
"parentPublication": {
"id": "proceedings/3dv/2021/2688/0",
"title": "2021 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2021/2688/0/268800b054",
"title": "AIR-Nets: An Attention-Based Framework for Locally Conditioned Implicit Representations",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2021/268800b054/1zWEkt7SgUg",
"parentPublication": {
"id": "proceedings/3dv/2021/2688/0",
"title": "2021 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1KOuVybvP20",
"title": "2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG)",
"acronym": "fg",
"groupId": "1000065",
"volume": "0",
"displayVolume": "0",
"year": "2023",
"__typename": "ProceedingType"
},
"article": {
"id": "1KOuYhOxDmo",
"doi": "10.1109/FG57933.2023.10042505",
"title": "Facial Geometric Detail Recovery via Implicit Representation",
"normalizedTitle": "Facial Geometric Detail Recovery via Implicit Representation",
"abstract": "Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries through facial prior while learning details as additional displacement maps or personalized basis. However, these techniques typically require vast datasets of paired multi-view data or 3D scans, whereas such datasets are scarce and expensive. To alleviate heavy data dependency, we present a robust texture-guided geometric detail recovery approach using only a single in-the-wild facial image. Specifically, we inpaint occluded facial parts, generate complete textures, and build an accurate multi-view dataset of the target subject. In order to estimate the detailed geometry, we define an implicit signed distance function and employ a physically-based implicit renderer to reconstruct fine geometric details from the generated multiview images. Our method not only recovers accurate facial details but also decomposes the diffuse and specular albedo, normals and shading components in a self-supervised way. Finally, we register the implicit shape details to a 3D Morphable Model template, which can be used in traditional modeling and rendering pipelines. Extensive experiments demonstrate that the proposed approach can reconstruct impressive facial details from a single image, especially when compared with state-of-the-art methods trained on large datasets.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries through facial prior while learning details as additional displacement maps or personalized basis. However, these techniques typically require vast datasets of paired multi-view data or 3D scans, whereas such datasets are scarce and expensive. To alleviate heavy data dependency, we present a robust texture-guided geometric detail recovery approach using only a single in-the-wild facial image. Specifically, we inpaint occluded facial parts, generate complete textures, and build an accurate multi-view dataset of the target subject. In order to estimate the detailed geometry, we define an implicit signed distance function and employ a physically-based implicit renderer to reconstruct fine geometric details from the generated multiview images. Our method not only recovers accurate facial details but also decomposes the diffuse and specular albedo, normals and shading components in a self-supervised way. Finally, we register the implicit shape details to a 3D Morphable Model template, which can be used in traditional modeling and rendering pipelines. Extensive experiments demonstrate that the proposed approach can reconstruct impressive facial details from a single image, especially when compared with state-of-the-art methods trained on large datasets.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Learning a dense 3D model with fine-scale details from a single facial image is highly challenging and ill-posed. To address this problem, many approaches fit smooth geometries through facial prior while learning details as additional displacement maps or personalized basis. However, these techniques typically require vast datasets of paired multi-view data or 3D scans, whereas such datasets are scarce and expensive. To alleviate heavy data dependency, we present a robust texture-guided geometric detail recovery approach using only a single in-the-wild facial image. Specifically, we inpaint occluded facial parts, generate complete textures, and build an accurate multi-view dataset of the target subject. In order to estimate the detailed geometry, we define an implicit signed distance function and employ a physically-based implicit renderer to reconstruct fine geometric details from the generated multiview images. Our method not only recovers accurate facial details but also decomposes the diffuse and specular albedo, normals and shading components in a self-supervised way. Finally, we register the implicit shape details to a 3D Morphable Model template, which can be used in traditional modeling and rendering pipelines. Extensive experiments demonstrate that the proposed approach can reconstruct impressive facial details from a single image, especially when compared with state-of-the-art methods trained on large datasets.",
"fno": "10042505",
"keywords": [
"Face Recognition",
"Feature Extraction",
"Geometry",
"Image Reconstruction",
"Image Representation",
"Image Texture",
"Learning Artificial Intelligence",
"Rendering Computer Graphics",
"Solid Modelling",
"3 D Morphable Model Template",
"Additional Displacement Maps",
"Complete Textures",
"Dense 3 D Model",
"Detailed Geometry",
"Facial Geometric Detail Recovery",
"Facial Parts",
"Fine Geometric Details",
"Fine Scale Details",
"Generated Multiview Images",
"Heavy Data Dependency",
"Implicit Renderer",
"Implicit Representation",
"Implicit Shape Details",
"Implicit Signed Distance Function",
"Impressive Facial Details",
"In The Wild Facial Image",
"Method Not Only Recovers Accurate Facial Details",
"Multiview Dataset",
"Normals",
"Paired Multiview Data",
"Personalized Basis",
"Robust Texture Guided Geometric Detail Recovery Approach",
"Shading Components",
"Single Facial Image",
"Single Image",
"Smooth Geometries",
"Traditional Modeling Rendering Pipelines",
"Vast Datasets",
"Geometry",
"Solid Modeling",
"Three Dimensional Displays",
"Shape",
"Face Recognition",
"Pipelines",
"Rendering Computer Graphics"
],
"authors": [
{
"affiliation": "AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,Shanghai,China",
"fullName": "Xingyu Ren",
"givenName": "Xingyu",
"surname": "Ren",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Imperial College London,London,U.K",
"fullName": "Alexandros Lattas",
"givenName": "Alexandros",
"surname": "Lattas",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,Shanghai,China",
"fullName": "Baris Gecer",
"givenName": "Baris",
"surname": "Gecer",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Huawei CBG,China",
"fullName": "Jiankang Deng",
"givenName": "Jiankang",
"surname": "Deng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,Shanghai,China",
"fullName": "Chao Ma",
"givenName": "Chao",
"surname": "Ma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "AI Institute, Shanghai Jiao Tong University,MoE Key Lab of Artificial Intelligence,Shanghai,China",
"fullName": "Xiaokang Yang",
"givenName": "Xiaokang",
"surname": "Yang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "fg",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2023-01-01T00:00:00",
"pubType": "proceedings",
"pages": "1-8",
"year": "2023",
"issn": null,
"isbn": "979-8-3503-4544-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "10042701",
"articleId": "1KOv4VsB1Be",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "10042713",
"articleId": "1KOuX36iVRm",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccvw/2017/1034/0/1034a777",
"title": "Realtime Dynamic 3D Facial Reconstruction for Monocular Video In-the-Wild",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2017/1034a777/12OmNxaNGhz",
"parentPublication": {
"id": "proceedings/iccvw/2017/1034/0",
"title": "2017 IEEE International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2011/348/0/06012122",
"title": "3D facial mesh detection using geometric saliency of surface",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2011/06012122/12OmNy6ZrWg",
"parentPublication": {
"id": "proceedings/icme/2011/348/0",
"title": "2011 IEEE International Conference on Multimedia and Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09756299",
"title": "Semantically Disentangled Variational Autoencoder for Modeling 3D Facial Details",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09756299/1CvQiJgja2k",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600u0321",
"title": "Physically-guided Disentangled Implicit Rendering for 3D Face Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600u0321/1H0NYm0sks8",
"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/cvpr/2022/6946/0/694600u0311",
"title": "ImFace: A Nonlinear 3D Morphable Face Model with Implicit Neural Representations",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600u0311/1H1i4mff8pq",
"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/cvpr/2022/6946/0/694600u0301",
"title": "FaceVerse: a Fine-grained and Detail-controllable 3D Face Morphable Model from a Hybrid Dataset",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600u0301/1H1m3T29fFu",
"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/2023/9346/0/934600g107",
"title": "ReEnFP: Detail-Preserving Face Reconstruction by Encoding Facial Priors",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600g107/1L8qsoyYuhG",
"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/cvpr/2020/7168/0/716800a737",
"title": "Lightweight Photometric Stereo for Facial Details Recovery",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800a737/1m3nsjiR8Ck",
"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/2021/4509/0/450900k0241",
"title": "D<sup>2</sup>IM-Net: Learning Detail Disentangled Implicit Fields from Single Images",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900k0241/1yeIv3o1GDe",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2021/2688/0/268800a815",
"title": "SIDER: Single-Image Neural Optimization for Facial Geometric Detail Recovery",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2021/268800a815/1zWE94Zh1Ru",
"parentPublication": {
"id": "proceedings/3dv/2021/2688/0",
"title": "2021 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1kuHFd2k9Ow",
"title": "2020 International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS)",
"acronym": "icitbs",
"groupId": "1811384",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1kuHOo4XaPm",
"doi": "10.1109/ICITBS49701.2020.00212",
"title": "A Word Representation Method Based on Glyph of Chinese Character",
"normalizedTitle": "A Word Representation Method Based on Glyph of Chinese Character",
"abstract": "The quality of words representation has an important impact on natural language processing tasks. Aiming at the problems in the current Chinese word representation method: the training data set is huge, the model quality depends on the data set, and the model stability is poor, a word representation method based on the glyph of Chinese character, Glyph2Vec, is proposed. Taking full advantage of the semantic information contained in Chinese characters, a glyph auto-encoder is constructed based on a convolutional auto-encoder. The glyph auto-encoder is used to obtain Chinese character embedding by mapping the glyph of Chinese character in the potential low-dimensional semantic space. In the Chinese named entity recognition task experiment, Glyph2Vec improves the accuracy to F1 score by 0.77%, 1.84%, and 1.31% respectively, compared with Word2Vec. The experimental results show that the method proposed is better than the existing results, which proves the effectiveness of this method.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The quality of words representation has an important impact on natural language processing tasks. Aiming at the problems in the current Chinese word representation method: the training data set is huge, the model quality depends on the data set, and the model stability is poor, a word representation method based on the glyph of Chinese character, Glyph2Vec, is proposed. Taking full advantage of the semantic information contained in Chinese characters, a glyph auto-encoder is constructed based on a convolutional auto-encoder. The glyph auto-encoder is used to obtain Chinese character embedding by mapping the glyph of Chinese character in the potential low-dimensional semantic space. In the Chinese named entity recognition task experiment, Glyph2Vec improves the accuracy to F1 score by 0.77%, 1.84%, and 1.31% respectively, compared with Word2Vec. The experimental results show that the method proposed is better than the existing results, which proves the effectiveness of this method.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The quality of words representation has an important impact on natural language processing tasks. Aiming at the problems in the current Chinese word representation method: the training data set is huge, the model quality depends on the data set, and the model stability is poor, a word representation method based on the glyph of Chinese character, Glyph2Vec, is proposed. Taking full advantage of the semantic information contained in Chinese characters, a glyph auto-encoder is constructed based on a convolutional auto-encoder. The glyph auto-encoder is used to obtain Chinese character embedding by mapping the glyph of Chinese character in the potential low-dimensional semantic space. In the Chinese named entity recognition task experiment, Glyph2Vec improves the accuracy to F1 score by 0.77%, 1.84%, and 1.31% respectively, compared with Word2Vec. The experimental results show that the method proposed is better than the existing results, which proves the effectiveness of this method.",
"fno": "669800a954",
"keywords": [
"Computational Linguistics",
"Convolutional Neural Nets",
"Natural Language Processing",
"Text Analysis",
"Chinese Character",
"Glyph 2 Vec",
"Glyph Auto Encoder",
"Word 2 Vec",
"Chinese Word Representation",
"Natural Language Processing",
"Semantic Information",
"Convolutional Auto Encoder",
"Low Dimensional Semantic Space",
"Chinese Named Entity Recognition",
"Smart Cities",
"Semantics",
"Training Data",
"Data Models",
"Stability Analysis",
"Natural Language Processing",
"Task Analysis",
"Chinese Character",
"Word Embedding",
"Auto Encoder"
],
"authors": [
{
"affiliation": "Xian University of Science & Technology, China",
"fullName": "Shancheng Tang",
"givenName": "Shancheng",
"surname": "Tang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xian University of Science & Technology, China",
"fullName": "Puyue Zhang",
"givenName": "Puyue",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xian University of Science & Technology, China",
"fullName": "Xiongxiong Chen",
"givenName": "Xiongxiong",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xian University of Science & Technology, China",
"fullName": "Hanbo Wang",
"givenName": "Hanbo",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xian University of Science & Technology, China",
"fullName": "Ming Chen",
"givenName": "Ming",
"surname": "Chen",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icitbs",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-01-01T00:00:00",
"pubType": "proceedings",
"pages": "954-957",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-6698-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "669800a950",
"articleId": "1kuHNL4wMBG",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "669800a958",
"articleId": "1kuHGnFEgq4",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/etcs/2009/3557/2/3557c674",
"title": "An XML-Based Approach for Chinese Character Glyph Description",
"doi": null,
"abstractUrl": "/proceedings-article/etcs/2009/3557c674/12OmNAle6li",
"parentPublication": {
"id": null,
"title": null,
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cit-iucc-dasc-picom/2015/0154/0/07363143",
"title": "Ontology Description of Chinese Character Semantics",
"doi": null,
"abstractUrl": "/proceedings-article/cit-iucc-dasc-picom/2015/07363143/12OmNBiygxw",
"parentPublication": {
"id": "proceedings/cit-iucc-dasc-picom/2015/0154/0",
"title": "2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing (CIT/IUCC/DASC/PICOM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2017/3586/1/3586a597",
"title": "Glyph-Based Data Augmentation for Accurate Kanji Character Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2017/3586a597/12OmNC1Y5lk",
"parentPublication": {
"id": "proceedings/icdar/2017/3586/1",
"title": "2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icect/2009/3559/0/3559a245",
"title": "A Structure Character Modeling for Chinese Character Glyph Description",
"doi": null,
"abstractUrl": "/proceedings-article/icect/2009/3559a245/12OmNwJgAEX",
"parentPublication": {
"id": "proceedings/icect/2009/3559/0",
"title": "2009 International Conference on Electronic Computer Technology. ICECT 2009",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2005/876/0/04118559",
"title": "Resolving the unencoded character problem for chinese digital libraries",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2005/04118559/12OmNyYm2pL",
"parentPublication": {
"id": "proceedings/jcdl/2005/876/0",
"title": "Proceedings of the 5th ACM/IEEE Joint Conference on Digital Libraries",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/alpit/2008/3273/0/3273a269",
"title": "A Research on the Stroke-Segment-Mesh (SSM) Glyph Depiction Method of Chinese Character",
"doi": null,
"abstractUrl": "/proceedings-article/alpit/2008/3273a269/12OmNyrIazq",
"parentPublication": {
"id": "proceedings/alpit/2008/3273/0",
"title": "Advanced Language Processing and Web Information Technology, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icbk/2021/3858/0/385800a462",
"title": "A Character-Word Graph Attention Networks for Chinese Text Classification",
"doi": null,
"abstractUrl": "/proceedings-article/icbk/2021/385800a462/1A9X4N5ktag",
"parentPublication": {
"id": "proceedings/icbk/2021/3858/0",
"title": "2021 IEEE International Conference on Big Knowledge (ICBK)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2019/3014/0/301400a178",
"title": "TH-GAN: Generative Adversarial Network Based Transfer Learning for Historical Chinese Character Recognition",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2019/301400a178/1h81u6jDzSE",
"parentPublication": {
"id": "proceedings/icdar/2019/3014/0",
"title": "2019 International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cyberc/2020/8448/0/844800a138",
"title": "Information Extraction Method based on Dilated Convolution and Character-Enhanced Word Embedding",
"doi": null,
"abstractUrl": "/proceedings-article/cyberc/2020/844800a138/1qJugPgOoHC",
"parentPublication": {
"id": "proceedings/cyberc/2020/8448/0",
"title": "2020 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icis-fall/2021/7679/0/09627454",
"title": "Chinese Word Segmentation for Sub-character Representation",
"doi": null,
"abstractUrl": "/proceedings-article/icis-fall/2021/09627454/1z7dPtWBZZK",
"parentPublication": {
"id": "proceedings/icis-fall/2021/7679/0",
"title": "2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1qyxi3OgORy",
"title": "2020 International Conference on 3D Vision (3DV)",
"acronym": "3dv",
"groupId": "1800494",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1qyxkR2YxGM",
"doi": "10.1109/3DV50981.2020.00055",
"title": "Learning Implicit Surface Light Fields",
"normalizedTitle": "Learning Implicit Surface Light Fields",
"abstract": "Implicit representations of 3D objects have recently achieved impressive results on learning-based 3D reconstruction tasks. While existing works use simple texture models to represent object appearance, photo-realistic image synthesis requires reasoning about the complex interplay of light, geometry and surface properties. In this work, we propose a novel implicit representation for capturing the visual appearance of an object in terms of its surface light field. In contrast to existing representations, our implicit model represents surface light fields in a continuous fashion and independent of the geometry. Moreover, we condition the surface light field with respect to the location and color of a small light source. Compared to traditional surface light field models, this allows us to manipulate the light source and relight the object using environment maps. We further demonstrate the capabilities of our model to predict the visual appearance of an unseen object from a single real RGB image and corresponding 3D shape information. As evidenced by our experiments, our model is able to infer rich visual appearance including shadows and specular reflections. Finally, we show that the proposed representation can be embedded into a variational auto-encoder for generating novel appearances that conform to the specified illumination conditions.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Implicit representations of 3D objects have recently achieved impressive results on learning-based 3D reconstruction tasks. While existing works use simple texture models to represent object appearance, photo-realistic image synthesis requires reasoning about the complex interplay of light, geometry and surface properties. In this work, we propose a novel implicit representation for capturing the visual appearance of an object in terms of its surface light field. In contrast to existing representations, our implicit model represents surface light fields in a continuous fashion and independent of the geometry. Moreover, we condition the surface light field with respect to the location and color of a small light source. Compared to traditional surface light field models, this allows us to manipulate the light source and relight the object using environment maps. We further demonstrate the capabilities of our model to predict the visual appearance of an unseen object from a single real RGB image and corresponding 3D shape information. As evidenced by our experiments, our model is able to infer rich visual appearance including shadows and specular reflections. Finally, we show that the proposed representation can be embedded into a variational auto-encoder for generating novel appearances that conform to the specified illumination conditions.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Implicit representations of 3D objects have recently achieved impressive results on learning-based 3D reconstruction tasks. While existing works use simple texture models to represent object appearance, photo-realistic image synthesis requires reasoning about the complex interplay of light, geometry and surface properties. In this work, we propose a novel implicit representation for capturing the visual appearance of an object in terms of its surface light field. In contrast to existing representations, our implicit model represents surface light fields in a continuous fashion and independent of the geometry. Moreover, we condition the surface light field with respect to the location and color of a small light source. Compared to traditional surface light field models, this allows us to manipulate the light source and relight the object using environment maps. We further demonstrate the capabilities of our model to predict the visual appearance of an unseen object from a single real RGB image and corresponding 3D shape information. As evidenced by our experiments, our model is able to infer rich visual appearance including shadows and specular reflections. Finally, we show that the proposed representation can be embedded into a variational auto-encoder for generating novel appearances that conform to the specified illumination conditions.",
"fno": "812800a452",
"keywords": [
"Image Colour Analysis",
"Image Reconstruction",
"Image Representation",
"Image Texture",
"Learning Artificial Intelligence",
"Light Sources",
"Lighting",
"Neural Nets",
"Realistic Images",
"Rendering Computer Graphics",
"Solid Modelling",
"Learning Based 3 D Reconstruction Tasks",
"Texture Models",
"Object Appearance",
"Geometry",
"Surface Properties",
"Light Source",
"Visual Appearance",
"Implicit Representations",
"Surface Light Field Models",
"Learning Implicit Surface Light Fields",
"3 D Objects",
"Photo Realistic Image Synthesis",
"Single Real RGB Image",
"3 D Shape Information",
"Specular Reflections",
"Variational Auto Encoder",
"Illumination Conditions",
"Three Dimensional Displays",
"Solid Modeling",
"Lighting",
"Rendering Computer Graphics",
"Image Color Analysis",
"Shape",
"Geometry",
"Appearance Modelling",
"Implicit Functions",
"3 D Deep Learning",
"Novel View Synthesis"
],
"authors": [
{
"affiliation": "Max Planck Institute for Intelligent Systems and University of Tübingen",
"fullName": "Michael Oechsle",
"givenName": "Michael",
"surname": "Oechsle",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Max Planck Institute for Intelligent Systems and University of Tübingen",
"fullName": "Michael Niemeyer",
"givenName": "Michael",
"surname": "Niemeyer",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Max Planck Institute for Intelligent Systems and University of Tübingen",
"fullName": "Christian Reiser",
"givenName": "Christian",
"surname": "Reiser",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Max Planck Institute for Intelligent Systems and University of Tübingen",
"fullName": "Lars Mescheder",
"givenName": "Lars",
"surname": "Mescheder",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "ETAS GmbH, Bosch Group,Stuttgart",
"fullName": "Thilo Strauss",
"givenName": "Thilo",
"surname": "Strauss",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Max Planck Institute for Intelligent Systems and University of Tübingen",
"fullName": "Andreas Geiger",
"givenName": "Andreas",
"surname": "Geiger",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "3dv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-11-01T00:00:00",
"pubType": "proceedings",
"pages": "452-462",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-8128-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "812800a443",
"articleId": "1qyxmVBQtgs",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "812800a463",
"articleId": "1qyxlwr0ly0",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cvprw/2017/0733/0/0733b754",
"title": "Light Field Convergency: Implicit Photometric Consistency on Transparent Surface",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2017/0733b754/12OmNC4eSug",
"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/mipr/2018/1857/0/185701a321",
"title": "Robust Surface Light Field Modeling",
"doi": null,
"abstractUrl": "/proceedings-article/mipr/2018/185701a321/12OmNrIJqDf",
"parentPublication": {
"id": "proceedings/mipr/2018/1857/0",
"title": "2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2016/0836/0/07504763",
"title": "Using Chromo-coded light fields for augmented reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2016/07504763/12OmNy5zsmT",
"parentPublication": {
"id": "proceedings/vr/2016/0836/0",
"title": "2016 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2018/8425/0/842500a012",
"title": "Surface Light Field Fusion",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2018/842500a012/17D45WODasr",
"parentPublication": {
"id": "proceedings/3dv/2018/8425/0",
"title": "2018 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2022/05/09712406",
"title": "Predicting Surface Reflectance Properties of Outdoor Scenes Under Unknown Natural Illumination",
"doi": null,
"abstractUrl": "/magazine/cg/2022/05/09712406/1AZLEpMIeME",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200g505",
"title": "Learning Signed Distance Field for Multi-view Surface Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200g505/1BmFLjuiAKs",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600s8398",
"title": "Neural Point Light Fields",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600s8398/1H1kUbIJXgY",
"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/2023/9346/0/934600e319",
"title": "Recovering Fine Details for Neural Implicit Surface Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600e319/1KxUSVbk6He",
"parentPublication": {
"id": "proceedings/wacv/2023/9346/0",
"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/10077440",
"title": "NeRC: Rendering Planar Caustics by Learning Implicit Neural Representations",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/10077440/1LFQ6PMpeik",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccp/2021/1952/0/09466274",
"title": "View-dependent Scene Appearance Synthesis using Inverse Rendering from Light Fields",
"doi": null,
"abstractUrl": "/proceedings-article/iccp/2021/09466274/1uSSV7tRhSw",
"parentPublication": {
"id": "proceedings/iccp/2021/1952/0",
"title": "2021 IEEE International Conference on Computational Photography (ICCP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1yeHGyRsuys",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1yeLEHLhLEc",
"doi": "10.1109/CVPR46437.2021.00148",
"title": "Deep Implicit Templates for 3D Shape Representation",
"normalizedTitle": "Deep Implicit Templates for 3D Shape Representation",
"abstract": "Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representation power. However, unlike polygon mesh-based templates, it remains a challenge to reason dense correspondences or other semantic relationships across shapes represented by DIFs, which limits its applications in texture transfer, shape analysis and so on. To overcome this limitation and also make DIFs more interpretable, we propose Deep Implicit Templates, a new 3D shape representation that supports explicit correspondence reasoning in deep implicit representations. Our key idea is to formulate DIFs as conditional deformations of a template implicit function. To this end, we propose Spatial Warping LSTM, which de-composes the conditional spatial transformation into multiple point-wise transformations and guarantees generalization capability. Moreover, the training loss is carefully designed in order to achieve high reconstruction accuracy while learning a plausible template with accurate correspondences in an unsupervised manner. Experiments show that our method can not only learn a common implicit tem-plate for a collection of shapes, but also establish dense correspondences across all the shapes simultaneously with-out any supervision.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representation power. However, unlike polygon mesh-based templates, it remains a challenge to reason dense correspondences or other semantic relationships across shapes represented by DIFs, which limits its applications in texture transfer, shape analysis and so on. To overcome this limitation and also make DIFs more interpretable, we propose Deep Implicit Templates, a new 3D shape representation that supports explicit correspondence reasoning in deep implicit representations. Our key idea is to formulate DIFs as conditional deformations of a template implicit function. To this end, we propose Spatial Warping LSTM, which de-composes the conditional spatial transformation into multiple point-wise transformations and guarantees generalization capability. Moreover, the training loss is carefully designed in order to achieve high reconstruction accuracy while learning a plausible template with accurate correspondences in an unsupervised manner. Experiments show that our method can not only learn a common implicit tem-plate for a collection of shapes, but also establish dense correspondences across all the shapes simultaneously with-out any supervision.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representation power. However, unlike polygon mesh-based templates, it remains a challenge to reason dense correspondences or other semantic relationships across shapes represented by DIFs, which limits its applications in texture transfer, shape analysis and so on. To overcome this limitation and also make DIFs more interpretable, we propose Deep Implicit Templates, a new 3D shape representation that supports explicit correspondence reasoning in deep implicit representations. Our key idea is to formulate DIFs as conditional deformations of a template implicit function. To this end, we propose Spatial Warping LSTM, which de-composes the conditional spatial transformation into multiple point-wise transformations and guarantees generalization capability. Moreover, the training loss is carefully designed in order to achieve high reconstruction accuracy while learning a plausible template with accurate correspondences in an unsupervised manner. Experiments show that our method can not only learn a common implicit tem-plate for a collection of shapes, but also establish dense correspondences across all the shapes simultaneously with-out any supervision.",
"fno": "450900b429",
"keywords": [
"Computational Geometry",
"Computer Vision",
"Deformation",
"Feature Extraction",
"Image Matching",
"Image Reconstruction",
"Image Representation",
"Image Texture",
"Learning Artificial Intelligence",
"Medical Image Processing",
"Mesh Generation",
"Solid Modelling",
"Common Implicit Tem Plate",
"Deep Implicit Templates",
"3 D Shape Representation",
"Deep Implicit Functions",
"DI Fs",
"3 D Vision Community",
"Strong Representation Power",
"Polygon Mesh Based Templates",
"Reason Dense Correspondences",
"Shape Analysis",
"Explicit Correspondence Reasoning",
"Deep Implicit Representations",
"Template Implicit Function",
"Training",
"Geometry",
"Computer Vision",
"Three Dimensional Displays",
"Shape",
"Semantics",
"Network Architecture"
],
"authors": [
{
"affiliation": "Tsinghua University,Department of Automation,Beijing,China",
"fullName": "Zerong Zheng",
"givenName": "Zerong",
"surname": "Zheng",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tsinghua University,Department of Automation,Beijing,China",
"fullName": "Tao Yu",
"givenName": "Tao",
"surname": "Yu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tsinghua University,Department of Automation,Beijing,China",
"fullName": "Qionghai Dai",
"givenName": "Qionghai",
"surname": "Dai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tsinghua University,Department of Automation,Beijing,China",
"fullName": "Yebin Liu",
"givenName": "Yebin",
"surname": "Liu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-06-01T00:00:00",
"pubType": "proceedings",
"pages": "1429-1439",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-4509-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1yeLEBkbKLu",
"name": "pcvpr202145090-09578218s1-mm_450900b429.zip",
"size": "10.1 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pcvpr202145090-09578218s1-mm_450900b429.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "450900b418",
"articleId": "1yeK2q3X69y",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "450900b440",
"articleId": "1yeJSYxaxKo",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2021/2812/0/281200n3067",
"title": "Multiresolution Deep Implicit Functions for 3D Shape Representation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200n3067/1BmL39Zkm9G",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09797843",
"title": "Learning Implicit Glyph Shape Representation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09797843/1EfIX5LNd5e",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600m2819",
"title": "GIFS: Neural Implicit Function for General Shape Representation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600m2819/1H0KHzfm1Ta",
"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/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/cvpr/2022/6946/0/694600p5840",
"title": "ImplicitAtlas: Learning Deformable Shape Templates in Medical Imaging",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600p5840/1H1kH7TJ3t6",
"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/3dv/2022/5670/0/567000a617",
"title": "HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2022/567000a617/1KYsmgBEd9e",
"parentPublication": {
"id": "proceedings/3dv/2022/5670/0",
"title": "2022 International Conference on 3D Vision (3DV)",
"__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/cvpr/2020/7168/0/716800e856",
"title": "Local Deep Implicit Functions for 3D Shape",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800e856/1m3ngGoPx5u",
"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/2021/4509/0/450900k0281",
"title": "Deformed Implicit Field: Modeling 3D Shapes with Learned Dense Correspondence",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900k0281/1yeJP8p8pgI",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900m2798",
"title": "i3DMM: Deep Implicit 3D Morphable Model of Human Heads",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900m2798/1yeLR7aJqiA",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyFCvOD",
"title": "EUROMICRO Conference",
"acronym": "euromicro",
"groupId": "1000279",
"volume": "2",
"displayVolume": "3",
"year": "1998",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwdbVe3",
"doi": "10.1109/EURMIC.1998.708133",
"title": "Composite Objects: Real-Time Programming with CORBA",
"normalizedTitle": "Composite Objects: Real-Time Programming with CORBA",
"abstract": "The Common Object Request Broker Architecture is a successful, standardized system integration framework based on distributed object technologies. An ongoing effort concerns extensions to CORBA to incorporate realtime computing needs. Although the use of objects in real-time computing is straightforward, the technical challenge lies in the replacement of static real-time computing infrastructures with a flexible real-time computing infrastructure, in which distributed real-time client and server objects can be created and connected as needed during runtime. We propose the concept of ??Composite Objects?? for the integration of real-time and non-real-time computing into a single object-based framework. Within the paper, we present a methodology for creating objects which interface to CORBA without violating real-time assumptions. We present a example scenario which integrates a real-time computing architecture and CORBA components via ??Composite Objects??. Finally, we discuss implementation-related issues based on our experiences with ??Composite Objects??.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The Common Object Request Broker Architecture is a successful, standardized system integration framework based on distributed object technologies. An ongoing effort concerns extensions to CORBA to incorporate realtime computing needs. Although the use of objects in real-time computing is straightforward, the technical challenge lies in the replacement of static real-time computing infrastructures with a flexible real-time computing infrastructure, in which distributed real-time client and server objects can be created and connected as needed during runtime. We propose the concept of ??Composite Objects?? for the integration of real-time and non-real-time computing into a single object-based framework. Within the paper, we present a methodology for creating objects which interface to CORBA without violating real-time assumptions. We present a example scenario which integrates a real-time computing architecture and CORBA components via ??Composite Objects??. Finally, we discuss implementation-related issues based on our experiences with ??Composite Objects??.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The Common Object Request Broker Architecture is a successful, standardized system integration framework based on distributed object technologies. An ongoing effort concerns extensions to CORBA to incorporate realtime computing needs. Although the use of objects in real-time computing is straightforward, the technical challenge lies in the replacement of static real-time computing infrastructures with a flexible real-time computing infrastructure, in which distributed real-time client and server objects can be created and connected as needed during runtime. We propose the concept of ??Composite Objects?? for the integration of real-time and non-real-time computing into a single object-based framework. Within the paper, we present a methodology for creating objects which interface to CORBA without violating real-time assumptions. We present a example scenario which integrates a real-time computing architecture and CORBA components via ??Composite Objects??. Finally, we discuss implementation-related issues based on our experiences with ??Composite Objects??.",
"fno": "864620997",
"keywords": [
"Object Based Real Time Computing",
"CORBA",
"Composite Objects",
"Non Interference",
"Interoperability"
],
"authors": [
{
"affiliation": "Humboldt University of Berlin",
"fullName": "Andreas Polze",
"givenName": "Andreas",
"surname": "Polze",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University",
"fullName": "Lui Sha",
"givenName": "Lui",
"surname": "Sha",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "euromicro",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1998-08-01T00:00:00",
"pubType": "proceedings",
"pages": "20997",
"year": "1998",
"issn": "1089-6503",
"isbn": "0-8186-8646-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "864620989",
"articleId": "12OmNzkuKAX",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "864621005",
"articleId": "12OmNCeaPTX",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/isads/1997/7783/0/77830187",
"title": "A Configurable Protocol Architecture for CORBA Environments",
"doi": null,
"abstractUrl": "/proceedings-article/isads/1997/77830187/12OmNAHmOw3",
"parentPublication": {
"id": "proceedings/isads/1997/7783/0",
"title": "Proceedings of the Third International Symposium on Autonomous Decentralized Systems. ISADS 97",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isads/2001/1065/0/10650327",
"title": "TMOES: A CORBA Service Middleware Enabling High-Level Real-Time Object Programming",
"doi": null,
"abstractUrl": "/proceedings-article/isads/2001/10650327/12OmNAYXWAa",
"parentPublication": {
"id": "proceedings/isads/2001/1065/0",
"title": "Proceedings 5th International Symposium on Autonomous Decentralized Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/words/1999/0101/0/01010027",
"title": "Two CORBA Services Enabling TMO Network Programming",
"doi": null,
"abstractUrl": "/proceedings-article/words/1999/01010027/12OmNBRbksM",
"parentPublication": {
"id": "proceedings/words/1999/0101/0",
"title": "Fourth International Workshop on Object-Oriented Real-Time Dependable Systems (WORDS'99)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isorc/1999/0207/0/02070182",
"title": "Towards Predictable CORBA-Based Web-Services",
"doi": null,
"abstractUrl": "/proceedings-article/isorc/1999/02070182/12OmNqAU6t5",
"parentPublication": {
"id": "proceedings/isorc/1999/0207/0",
"title": "Proceedings 2nd IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC'99) (Cat. No.99-61702)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ftcs/1999/0213/0/02130150",
"title": "A Fault Tolerance Framework for CORBA",
"doi": null,
"abstractUrl": "/proceedings-article/ftcs/1999/02130150/12OmNqBKUfd",
"parentPublication": {
"id": "proceedings/ftcs/1999/0213/0",
"title": "Fault-Tolerant Computing, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isorc/2000/0607/0/06070338",
"title": "A Large Scale Distributed Object Architecture - CORBA & COM for Real Time Systems",
"doi": null,
"abstractUrl": "/proceedings-article/isorc/2000/06070338/12OmNxveNH9",
"parentPublication": {
"id": "proceedings/isorc/2000/0607/0",
"title": "Proceedings Third IEEE International Symposium on Object-Oriented Real-Time Distributed Computing (ISORC 2000) (Cat. No. PR00607)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apsec/1999/0509/0/05090530",
"title": "Testing, Reliability, and Interoperability Issues in the CORBA Programming Paradigm",
"doi": null,
"abstractUrl": "/proceedings-article/apsec/1999/05090530/12OmNyXMQjh",
"parentPublication": {
"id": "proceedings/apsec/1999/0509/0",
"title": "Proceedings Sixth Asia Pacific Software Engineering Conference (ASPEC'99) (Cat. No.PR00509)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dexa/1997/8147/0/81470086",
"title": "Manipulation of Image Objects and Their Versions under CORBA Environment",
"doi": null,
"abstractUrl": "/proceedings-article/dexa/1997/81470086/12OmNzYNNmm",
"parentPublication": {
"id": "proceedings/dexa/1997/8147/0",
"title": "Database and Expert Systems Applications. 8th International Conference, DEXA '97. Proceedings",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/rtas/1997/8016/0/80160148",
"title": "Real-time CORBA",
"doi": null,
"abstractUrl": "/proceedings-article/rtas/1997/80160148/12OmNzkMlU6",
"parentPublication": {
"id": "proceedings/rtas/1997/8016/0",
"title": "Third IEEE Real-Time Technology and Applications Symposium (RTAS'97)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2000/10/l1073",
"title": "Real-Time CORBA",
"doi": null,
"abstractUrl": "/journal/td/2000/10/l1073/13rRUxASuFK",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxQOjz3",
"title": "2012 IEEE 36th Annual Computer Software and Applications Conference",
"acronym": "compsac",
"groupId": "1000143",
"volume": "0",
"displayVolume": "0",
"year": "2012",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwnYFYj",
"doi": "10.1109/COMPSAC.2012.64",
"title": "Deriving Specifications for Composite Web Services",
"normalizedTitle": "Deriving Specifications for Composite Web Services",
"abstract": "We address the problem of synthesizing specifications for composite Web services, starting from those of their component services. Unlike related work in programming languages, we assume the definition of the component services (i.e. their code) to be unavailable --- at best, they are known by a specification which (safely) approximates their functional behavior. Within this scenario, we deduce general formula schemes to derive specifications for basic constructs such as sequential, parallel compositions and conditionals and provide details on how to handle the special cases of loops and asynchronous execution. The resulting specifications facilitate service verification and service evolution as well as auditing processes, promoting trust between the involved partners.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We address the problem of synthesizing specifications for composite Web services, starting from those of their component services. Unlike related work in programming languages, we assume the definition of the component services (i.e. their code) to be unavailable --- at best, they are known by a specification which (safely) approximates their functional behavior. Within this scenario, we deduce general formula schemes to derive specifications for basic constructs such as sequential, parallel compositions and conditionals and provide details on how to handle the special cases of loops and asynchronous execution. The resulting specifications facilitate service verification and service evolution as well as auditing processes, promoting trust between the involved partners.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We address the problem of synthesizing specifications for composite Web services, starting from those of their component services. Unlike related work in programming languages, we assume the definition of the component services (i.e. their code) to be unavailable --- at best, they are known by a specification which (safely) approximates their functional behavior. Within this scenario, we deduce general formula schemes to derive specifications for basic constructs such as sequential, parallel compositions and conditionals and provide details on how to handle the special cases of loops and asynchronous execution. The resulting specifications facilitate service verification and service evolution as well as auditing processes, promoting trust between the involved partners.",
"fno": "4736a432",
"keywords": [
"Approximation Methods",
"Web Services",
"Computer Science",
"Semantics",
"Educational Institutions",
"Electronic Mail",
"Service Composition",
"Specification Of Service Compositions",
"Inference Of Specifications"
],
"authors": [
{
"affiliation": null,
"fullName": "George Baryannis",
"givenName": "George",
"surname": "Baryannis",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Manuel Carro",
"givenName": "Manuel",
"surname": "Carro",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Dimitris Plexousakis",
"givenName": "Dimitris",
"surname": "Plexousakis",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "compsac",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2012-07-01T00:00:00",
"pubType": "proceedings",
"pages": "432-437",
"year": "2012",
"issn": "0730-3157",
"isbn": "978-1-4673-1990-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4736a422",
"articleId": "12OmNqJq4wF",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4736a438",
"articleId": "12OmNvTk002",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/niss/2009/3687/0/3687a152",
"title": "Quality and Relation Driven Service Selection for Web Services Composition",
"doi": null,
"abstractUrl": "/proceedings-article/niss/2009/3687a152/12OmNC1Gub5",
"parentPublication": {
"id": "proceedings/niss/2009/3687/0",
"title": "2009 International Conference on New Trends in Information and Service Science (NISS 2009)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/issre/2010/4255/0/4255a348",
"title": "Automata-Based Verification of Security Requirements of Composite Web Services",
"doi": null,
"abstractUrl": "/proceedings-article/issre/2010/4255a348/12OmNCyTyrN",
"parentPublication": {
"id": "proceedings/issre/2010/4255/0",
"title": "2010 IEEE 21st International Symposium on Software Reliability Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aina/2010/4018/0/4018a958",
"title": "From Communities of Web Services to Marts of Composite Web Services",
"doi": null,
"abstractUrl": "/proceedings-article/aina/2010/4018a958/12OmNvSKND0",
"parentPublication": {
"id": "proceedings/aina/2010/4018/0",
"title": "2010 24th IEEE International Conference on Advanced Information Networking and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icstw/2009/3671/0/3671a307",
"title": "Testing Composite Web Services--An Event-Based Approach",
"doi": null,
"abstractUrl": "/proceedings-article/icstw/2009/3671a307/12OmNwcl7As",
"parentPublication": {
"id": "proceedings/icstw/2009/3671/0",
"title": "Software Testing Verification and Validation Workshop, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecows/2005/2484/0/24840170",
"title": "A View-based Approach for Tracking Composite Web Services",
"doi": null,
"abstractUrl": "/proceedings-article/ecows/2005/24840170/12OmNwpoFBJ",
"parentPublication": {
"id": "proceedings/ecows/2005/2484/0",
"title": "Proceedings. Third European Conference on Web Services",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ispa/2010/4190/0/4190a130",
"title": "MTTF of Composite Web Services",
"doi": null,
"abstractUrl": "/proceedings-article/ispa/2010/4190a130/12OmNxYtuc1",
"parentPublication": {
"id": "proceedings/ispa/2010/4190/0",
"title": "International Symposium on Parallel and Distributed Processing with Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/kse/2012/4760/0/4760a060",
"title": "Securing Data in Composite Web Services",
"doi": null,
"abstractUrl": "/proceedings-article/kse/2012/4760a060/12OmNyRPgpJ",
"parentPublication": {
"id": "proceedings/kse/2012/4760/0",
"title": "Knowledge and Systems Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pccc/1993/0922/0/00344448",
"title": "Deriving protocol specifications from service specifications written in LOTOS",
"doi": null,
"abstractUrl": "/proceedings-article/pccc/1993/00344448/12OmNya72tD",
"parentPublication": {
"id": "proceedings/pccc/1993/0922/0",
"title": "Proceedings of Phoenix Conference on Computers and Communications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scc/2008/3283/1/3283a361",
"title": "Composing Web Services through Automatic Reformulation of Service Specifications",
"doi": null,
"abstractUrl": "/proceedings-article/scc/2008/3283a361/12OmNzlUKsD",
"parentPublication": {
"id": "proceedings/scc/2008/3283/2",
"title": "2008 IEEE International Conference on Services Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/co/2006/05/r5024",
"title": "Web Services Interoperability Specifications",
"doi": null,
"abstractUrl": "/magazine/co/2006/05/r5024/13rRUILLkJD",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzUPpvj",
"title": "Acoustics, Speech, and Signal Processing, IEEE International Conference on",
"acronym": "icassp",
"groupId": "1000002",
"volume": "2",
"displayVolume": "0",
"year": "2000",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzA6GS0",
"doi": "10.1109/ICASSP.2000.859055",
"title": "An efficient algorithm to extract components of a composite signal",
"normalizedTitle": "An efficient algorithm to extract components of a composite signal",
"abstract": "An efficient algorithm is proposed to extract components of a composite signal. The proposed approach has two stages of processing in which the time-frequency supports of the individual signal components are identified and then the individual components are estimated by performing a simple time-frequency domain incision on the identified support of the component. The use of a previously developed time-frequency representation significantly improves the performance of the proposed approach by providing a very accurate description on the auto-Wigner terms of the composite signal. Then, simple fractional Fourier domain incision provides reliable estimates for each of the signal components in O(N log N) complexity for a composite signal of duration N.",
"abstracts": [
{
"abstractType": "Regular",
"content": "An efficient algorithm is proposed to extract components of a composite signal. The proposed approach has two stages of processing in which the time-frequency supports of the individual signal components are identified and then the individual components are estimated by performing a simple time-frequency domain incision on the identified support of the component. The use of a previously developed time-frequency representation significantly improves the performance of the proposed approach by providing a very accurate description on the auto-Wigner terms of the composite signal. Then, simple fractional Fourier domain incision provides reliable estimates for each of the signal components in O(N log N) complexity for a composite signal of duration N.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "An efficient algorithm is proposed to extract components of a composite signal. The proposed approach has two stages of processing in which the time-frequency supports of the individual signal components are identified and then the individual components are estimated by performing a simple time-frequency domain incision on the identified support of the component. The use of a previously developed time-frequency representation significantly improves the performance of the proposed approach by providing a very accurate description on the auto-Wigner terms of the composite signal. Then, simple fractional Fourier domain incision provides reliable estimates for each of the signal components in O(N log N) complexity for a composite signal of duration N.",
"fno": "00859055",
"keywords": [],
"authors": [
{
"affiliation": "Dept. of Electr. & Electron. Eng., Bilkent Univ., Ankara, Turkey",
"fullName": "O. Arikan",
"givenName": "O.",
"surname": "Arikan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "A. Kemal Ozdemir",
"givenName": "A.",
"surname": "Kemal Ozdemir",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icassp",
"isOpenAccess": false,
"showRecommendedArticles": false,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2000-06-01T00:00:00",
"pubType": "proceedings",
"pages": "II697-II700",
"year": "2000",
"issn": null,
"isbn": "0-7803-6293-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "00859054",
"articleId": "12OmNrNh0GZ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "00859056",
"articleId": "12OmNvjgWQ9",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNAolGIX",
"title": "Proceedings 1997 International Conference on Network Protocols",
"acronym": "icnp",
"groupId": "1000492",
"volume": "0",
"displayVolume": "0",
"year": "1997",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzdoMX9",
"doi": "10.1109/ICNP.1997.643697",
"title": "A Compositional Approach for Designing Multifunction Time-Dependent Protocols",
"normalizedTitle": "A Compositional Approach for Designing Multifunction Time-Dependent Protocols",
"abstract": "We propose a framework based on the model of timed extended finite state machines for building communication protocols which perform several functions, where each function corresponds to a component protocol. For parallel composition, we specify a conjunctive relation which requires that the execution of events in two component protocols be synchronized. We also propose a predicate strengthening technique to refine the composite composite protocol in a stepwise manner while preserving the invariants of the component protocols. For sequential composition, we present a set of constraints, alternating, ordering and disabling, on the actions of the component protocols, and give sufficient conditions for the composite protocol to retain the safety properties such as freedom from unspecified receptions and freedom from deadlocks. Our sufficient conditions are weaker than those given in previous works.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose a framework based on the model of timed extended finite state machines for building communication protocols which perform several functions, where each function corresponds to a component protocol. For parallel composition, we specify a conjunctive relation which requires that the execution of events in two component protocols be synchronized. We also propose a predicate strengthening technique to refine the composite composite protocol in a stepwise manner while preserving the invariants of the component protocols. For sequential composition, we present a set of constraints, alternating, ordering and disabling, on the actions of the component protocols, and give sufficient conditions for the composite protocol to retain the safety properties such as freedom from unspecified receptions and freedom from deadlocks. Our sufficient conditions are weaker than those given in previous works.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose a framework based on the model of timed extended finite state machines for building communication protocols which perform several functions, where each function corresponds to a component protocol. For parallel composition, we specify a conjunctive relation which requires that the execution of events in two component protocols be synchronized. We also propose a predicate strengthening technique to refine the composite composite protocol in a stepwise manner while preserving the invariants of the component protocols. For sequential composition, we present a set of constraints, alternating, ordering and disabling, on the actions of the component protocols, and give sufficient conditions for the composite protocol to retain the safety properties such as freedom from unspecified receptions and freedom from deadlocks. Our sufficient conditions are weaker than those given in previous works.",
"fno": "80610105",
"keywords": [
"Time Dependent Protocols",
"Protocol Composition"
],
"authors": [
{
"affiliation": "University of Maryland, College Park",
"fullName": "Jun-Cheol Park",
"givenName": "Jun-Cheol",
"surname": "Park",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Maryland, College Park",
"fullName": "Raymond E. Miller",
"givenName": "Raymond E.",
"surname": "Miller",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icnp",
"isOpenAccess": false,
"showRecommendedArticles": false,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1997-10-01T00:00:00",
"pubType": "proceedings",
"pages": "105",
"year": "1997",
"issn": "1092-1648",
"isbn": "0-8186-8061-X",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "80610095",
"articleId": "12OmNybfqWp",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "80610113",
"articleId": "12OmNyFU6XC",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1cI6akLvAuQ",
"title": "2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)",
"acronym": "vr",
"groupId": "1000791",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "1cJ1gPJX2og",
"doi": "10.1109/VR.2019.8798136",
"title": "VR Sickness in Continuous Exposure to Live-action 180°Video",
"normalizedTitle": "VR Sickness in Continuous Exposure to Live-action 180°Video",
"abstract": "The goal of this study was to determine the factors that determine the degree of VR sickness in order to improve the audiovisual experience of VR videos or games. We used a simulator sickness questionnaire to evaluate the degree of VR sickness for nine types of live-action 180-degree videos, with a combination of different movement speeds and fields of view (FOV). Among the 40 participants we tested, those suffering from motion sickness had more serious symptoms than those without motion sickness. Although statistical tests failed to show significant differences related to the movement speeds or fields of view, our results suggested that VR exposure time was the most important factor influencing VR sickness.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The goal of this study was to determine the factors that determine the degree of VR sickness in order to improve the audiovisual experience of VR videos or games. We used a simulator sickness questionnaire to evaluate the degree of VR sickness for nine types of live-action 180-degree videos, with a combination of different movement speeds and fields of view (FOV). Among the 40 participants we tested, those suffering from motion sickness had more serious symptoms than those without motion sickness. Although statistical tests failed to show significant differences related to the movement speeds or fields of view, our results suggested that VR exposure time was the most important factor influencing VR sickness.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The goal of this study was to determine the factors that determine the degree of VR sickness in order to improve the audiovisual experience of VR videos or games. We used a simulator sickness questionnaire to evaluate the degree of VR sickness for nine types of live-action 180-degree videos, with a combination of different movement speeds and fields of view (FOV). Among the 40 participants we tested, those suffering from motion sickness had more serious symptoms than those without motion sickness. Although statistical tests failed to show significant differences related to the movement speeds or fields of view, our results suggested that VR exposure time was the most important factor influencing VR sickness.",
"fno": "08798136",
"keywords": [
"Audio Visual Systems",
"Computer Games",
"Statistical Testing",
"Virtual Reality",
"Simulator Sickness Questionnaire",
"VR Sickness",
"Live Action 180 Degree Videos",
"Motion Sickness",
"VR Exposure Time",
"Continuous Exposure",
"Audiovisual Experience Improvement",
"Movement Speeds",
"Field Of View",
"Statistical Tests",
"Virtual Reality",
"Simulator Sickness Questionnaire",
"Motion Sickness",
"Human Centered Computing",
"Human Computer Interaction HCI",
"Interaction Devices",
"Displays And Imagers",
"Interaction Paradigms"
],
"authors": [
{
"affiliation": "Meiji University",
"fullName": "Sinan Zhang",
"givenName": "Sinan",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "L.A.B Co. Ltd.",
"fullName": "Akiyoshi Kurogi",
"givenName": "Akiyoshi",
"surname": "Kurogi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Meiji University",
"fullName": "Yumie Ono",
"givenName": "Yumie",
"surname": "Ono",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-03-01T00:00:00",
"pubType": "proceedings",
"pages": "1269-1270",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-1377-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08797878",
"articleId": "1cJ0I4GtxhC",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08797838",
"articleId": "1cJ0XpsKvLO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/3dui/2016/0842/0/07460053",
"title": "Combating VR sickness through subtle dynamic field-of-view modification",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2016/07460053/12OmNBubORd",
"parentPublication": {
"id": "proceedings/3dui/2016/0842/0",
"title": "2016 IEEE Symposium on 3D User Interfaces (3DUI)",
"__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/cost/2022/6248/0/624800a169",
"title": "Development of VR Motion Sickness Test Platform Based on UE",
"doi": null,
"abstractUrl": "/proceedings-article/cost/2022/624800a169/1H2pqPKjkAg",
"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/2023/4815/0/481500a094",
"title": "An EEG-based Experiment on VR Sickness and Postural Instability While Walking in Virtual Environments",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2023/481500a094/1MNgWtYsR5S",
"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/2019/1377/0/08798158",
"title": "PhantomLegs: Reducing Virtual Reality Sickness Using Head-Worn Haptic Devices",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798158/1cJ16zT3GdW",
"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/2020/6532/0/09090670",
"title": "SiSiMo: Towards Simulator Sickness Modeling for 360<sup>°</sup> Videos Viewed with an HMD",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2020/09090670/1jIxwAw9Z9C",
"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/vrw/2020/6532/0/09090490",
"title": "Evaluation of Simulator Sickness for 360° Videos on an HMD Subject to Participants’ Experience with Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2020/09090490/1jIxwgIdgsw",
"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/icpr/2021/8808/0/09412423",
"title": "VR Sickness Assessment with Perception Prior and Hybrid Temporal Features",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412423/1tmiMP82mre",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2021/4057/0/405700a735",
"title": "[DC] Towards Universal VR Sickness Mitigation Strategies",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2021/405700a735/1tnXDI2lhHq",
"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/vrw/2021/4057/0/405700a380",
"title": "Evaluating VR Sickness in VR Locomotion Techniques",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2021/405700a380/1tnXc1raaxq",
"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"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzVGcJn",
"title": "2008 8th IEEE International Conference on Automatic Face & Gesture Recognition",
"acronym": "fg",
"groupId": "1000065",
"volume": "0",
"displayVolume": "0",
"year": "2008",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBqv2dy",
"doi": "10.1109/AFGR.2008.4813466",
"title": "A fast and robust 3D head pose and gaze estimation system",
"normalizedTitle": "A fast and robust 3D head pose and gaze estimation system",
"abstract": "We developed a fast and robust head pose and gaze estimation system. This system can detect facial feature points and estimate 3D pose angles and gaze direction in various conditions including changes in facial expression, partial occlusion, etc. The system needs only one face image as input and doesn't need any special devices such as blinking LED or stereo camera. Moreover, no calibration process is needed. It shows 95% of head pose estimation accuracy and 81% of gaze estimation accuracy (when the error margin is 15 degrees). The processing time is approximately 15ms/frame (Pentium4 3.2 GHz). Acceptable range of facial pose is within +/- 60 degrees in yaw (left-right) and within +/- 30 degrees in pitch (up-down).",
"abstracts": [
{
"abstractType": "Regular",
"content": "We developed a fast and robust head pose and gaze estimation system. This system can detect facial feature points and estimate 3D pose angles and gaze direction in various conditions including changes in facial expression, partial occlusion, etc. The system needs only one face image as input and doesn't need any special devices such as blinking LED or stereo camera. Moreover, no calibration process is needed. It shows 95% of head pose estimation accuracy and 81% of gaze estimation accuracy (when the error margin is 15 degrees). The processing time is approximately 15ms/frame (Pentium4 3.2 GHz). Acceptable range of facial pose is within +/- 60 degrees in yaw (left-right) and within +/- 30 degrees in pitch (up-down).",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We developed a fast and robust head pose and gaze estimation system. This system can detect facial feature points and estimate 3D pose angles and gaze direction in various conditions including changes in facial expression, partial occlusion, etc. The system needs only one face image as input and doesn't need any special devices such as blinking LED or stereo camera. Moreover, no calibration process is needed. It shows 95% of head pose estimation accuracy and 81% of gaze estimation accuracy (when the error margin is 15 degrees). The processing time is approximately 15ms/frame (Pentium4 3.2 GHz). Acceptable range of facial pose is within +/- 60 degrees in yaw (left-right) and within +/- 30 degrees in pitch (up-down).",
"fno": "04813466",
"keywords": [
"Face Recognition",
"Pose Estimation",
"Stereo Image Processing",
"Robust 3 D Head Pose Angle Estimation",
"Gaze Estimation System",
"Facial Feature Point Detection",
"Facial Expression",
"Partial Occlusion",
"Face Image",
"LED",
"Stereo Camera",
"Robustness",
"Face Detection",
"Real Time Systems",
"Lighting",
"Head",
"Cameras",
"Facial Features",
"Calibration",
"Universal Serial Bus",
"Streaming Media"
],
"authors": [
{
"affiliation": "Core Technology Center, OMRON Corporation, 9-1, Kizugawadai, Kizugawa-city, Kyoto 619-0283, JAPAN",
"fullName": "Koichi Kinoshita",
"givenName": "Koichi",
"surname": "Kinoshita",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Core Technology Center, OMRON Corporation, 9-1, Kizugawadai, Kizugawa-city, Kyoto 619-0283, JAPAN",
"fullName": "Shihong Lao",
"givenName": "Shihong",
"surname": "Lao",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "fg",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2008-09-01T00:00:00",
"pubType": "proceedings",
"pages": "",
"year": "2008",
"issn": null,
"isbn": "978-1-4244-2153-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "04813465",
"articleId": "12OmNyTwRcY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "04813467",
"articleId": "12OmNqJ8toB",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/motion/2002/1860/0/18600125",
"title": "Comparative Study of Coarse Head Pose Estimation",
"doi": null,
"abstractUrl": "/proceedings-article/motion/2002/18600125/12OmNAGw13Q",
"parentPublication": {
"id": "proceedings/motion/2002/1860/0",
"title": "Proceedings Workshop on Motion and Video Computing (MOTION 2002)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2006/2521/2/252120512",
"title": "Robust Head Pose Estimation Using LGBP",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2006/252120512/12OmNBKW9BM",
"parentPublication": {
"id": "proceedings/icpr/2006/2521/2",
"title": "Pattern Recognition, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigcomp/2014/3919/0/06741444",
"title": "Head pose and gaze direction tracking for detecting a drowsy driver",
"doi": null,
"abstractUrl": "/proceedings-article/bigcomp/2014/06741444/12OmNrkBwsu",
"parentPublication": {
"id": "proceedings/bigcomp/2014/3919/0",
"title": "2014 International Conference on Big Data and Smart Computing (BIGCOMP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2008/2153/0/04813369",
"title": "Accurate single view model-based head pose estimation",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2008/04813369/12OmNwFidf0",
"parentPublication": {
"id": "proceedings/fg/2008/2153/0",
"title": "2008 8th IEEE International Conference on Automatic Face & Gesture Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2015/1727/0/07223361",
"title": "AR-SSVEP for brain-machine interface: Estimating user's gaze in head-mounted display with USB camera",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2015/07223361/12OmNwtEEzT",
"parentPublication": {
"id": "proceedings/vr/2015/1727/0",
"title": "2015 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2015/8391/0/8391b958",
"title": "Fast and Accurate Head Pose Estimation via Random Projection Forests",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2015/8391b958/12OmNy7yEcM",
"parentPublication": {
"id": "proceedings/iccv/2015/8391/0",
"title": "2015 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2010/4109/0/4109d870",
"title": "Visual Gaze Estimation by Joint Head and Eye Information",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2010/4109d870/12OmNyRg4Cq",
"parentPublication": {
"id": "proceedings/icpr/2010/4109/0",
"title": "Pattern Recognition, International Conference on",
"__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/acpr/2017/3354/0/3354a935",
"title": "A Deep Learning Approach to Appearance-Based Gaze Estimation under Head Pose Variations",
"doi": null,
"abstractUrl": "/proceedings-article/acpr/2017/3354a935/17D45XacGif",
"parentPublication": {
"id": "proceedings/acpr/2017/3354/0",
"title": "2017 4th IAPR Asian Conference on Pattern Recognition (ACPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/5555/01/10061572",
"title": "Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control",
"doi": null,
"abstractUrl": "/journal/tp/5555/01/10061572/1Lk2C6ZD2zC",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "13Jkr98ynrg",
"title": "2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)",
"acronym": "icis",
"groupId": "1001200",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "13Jkr9SfNnG",
"doi": "10.1109/ICIS.2018.8466462",
"title": "Image-based Attention Level Estimation of Interaction Scene by Head Pose and Gaze Information",
"normalizedTitle": "Image-based Attention Level Estimation of Interaction Scene by Head Pose and Gaze Information",
"abstract": "In many situations such as chat and discussion, we interact with other people, and interaction analysis is useful for improving communication skills and evaluating a learning effect of education. Although the audio information is possible to analyze the speaker behavior, it is difficult to analyze the non-speaker. On the other hand, the image information is possible to estimate the inside information, such as the concentration level and understanding level of the interaction of the non-speaker not only the speaker by using nodding, face direction, facial expression, and gaze. This paper proposes an image-based method to automatically estimate the attention level of participants for the interaction scene. We collected simulated interaction scenes by using the omnidirectional camera, and applied the proposed method. As a result, we confirmed the effectiveness of the proposed method.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In many situations such as chat and discussion, we interact with other people, and interaction analysis is useful for improving communication skills and evaluating a learning effect of education. Although the audio information is possible to analyze the speaker behavior, it is difficult to analyze the non-speaker. On the other hand, the image information is possible to estimate the inside information, such as the concentration level and understanding level of the interaction of the non-speaker not only the speaker by using nodding, face direction, facial expression, and gaze. This paper proposes an image-based method to automatically estimate the attention level of participants for the interaction scene. We collected simulated interaction scenes by using the omnidirectional camera, and applied the proposed method. As a result, we confirmed the effectiveness of the proposed method.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In many situations such as chat and discussion, we interact with other people, and interaction analysis is useful for improving communication skills and evaluating a learning effect of education. Although the audio information is possible to analyze the speaker behavior, it is difficult to analyze the non-speaker. On the other hand, the image information is possible to estimate the inside information, such as the concentration level and understanding level of the interaction of the non-speaker not only the speaker by using nodding, face direction, facial expression, and gaze. This paper proposes an image-based method to automatically estimate the attention level of participants for the interaction scene. We collected simulated interaction scenes by using the omnidirectional camera, and applied the proposed method. As a result, we confirmed the effectiveness of the proposed method.",
"fno": "08466462",
"keywords": [
"Face",
"Cameras",
"Feature Extraction",
"Pose Estimation",
"Face Detection",
"Interaction Scene",
"Attention Level Estimation",
"Head Pose",
"Gaze",
"Omnidirectional Camera"
],
"authors": [
{
"affiliation": "Kyushu Institute of Technology, Iizuka, 820-8502, Japan",
"fullName": "Rinko Komiya",
"givenName": "Rinko",
"surname": "Komiya",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Kyushu Institute of Technology, Iizuka, 820-8502, Japan",
"fullName": "Takeshi Saitoh",
"givenName": "Takeshi",
"surname": "Saitoh",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Kyushu Institute of Technology, Iizuka, 820-8502, Japan",
"fullName": "Kazutaka Shimada",
"givenName": "Kazutaka",
"surname": "Shimada",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-06-01T00:00:00",
"pubType": "proceedings",
"pages": "497-501",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-5892-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08466509",
"articleId": "13Jkr9ZUXTm",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08466399",
"articleId": "13Jkr98ynrh",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icme/2012/4711/0/4711a794",
"title": "3D Head Pose Estimation Based on Scene Flow and Generic Head Model",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2012/4711a794/12OmNqGitTB",
"parentPublication": {
"id": "proceedings/icme/2012/4711/0",
"title": "2012 IEEE International Conference on Multimedia and Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2011/4419/0/4419a186",
"title": "The Importance of Eye Gaze and Head Pose to Estimating Levels of Attention",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2011/4419a186/12OmNqyDjtb",
"parentPublication": {
"id": "proceedings/vs-games/2011/4419/0",
"title": "Games and Virtual Worlds for Serious Applications, Conference in",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icis/2016/0806/0/07550793",
"title": "Head pose estimation and movement analysis for speech scene",
"doi": null,
"abstractUrl": "/proceedings-article/icis/2016/07550793/12OmNrH1PFd",
"parentPublication": {
"id": "proceedings/icis/2016/0806/0",
"title": "2016 IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigcomp/2014/3919/0/06741444",
"title": "Head pose and gaze direction tracking for detecting a drowsy driver",
"doi": null,
"abstractUrl": "/proceedings-article/bigcomp/2014/06741444/12OmNrkBwsu",
"parentPublication": {
"id": "proceedings/bigcomp/2014/3919/0",
"title": "2014 International Conference on Big Data and Smart Computing (BIGCOMP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/avss/2011/0844/0/06027285",
"title": "Gaze and body pose estimation from a distance",
"doi": null,
"abstractUrl": "/proceedings-article/avss/2011/06027285/12OmNvSKNZj",
"parentPublication": {
"id": "proceedings/avss/2011/0844/0",
"title": "2011 8th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isuc/2008/3433/0/3433a225",
"title": "Analysis by Synthesis of Embodied Communication via VirtualActor with a Nodding Response Model",
"doi": null,
"abstractUrl": "/proceedings-article/isuc/2008/3433a225/12OmNwCsdNk",
"parentPublication": {
"id": "proceedings/isuc/2008/3433/0",
"title": "2008 Second International Symposium on Universal Communication",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2014/01/mcg2014010032",
"title": "Head-Pose-Based Attention Recognition on Large Public Displays",
"doi": null,
"abstractUrl": "/magazine/cg/2014/01/mcg2014010032/13rRUzpzeHK",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__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/fg/2019/0089/0/08756536",
"title": "A CNN Model for Head Pose Recognition using Wholes and Regions",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2019/08756536/1bzYunMam5y",
"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/icme/2019/9552/0/955200b084",
"title": "LPHD: A Large-Scale Head Pose Dataset for RGB Images",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2019/955200b084/1cdOH6kr9mw",
"parentPublication": {
"id": "proceedings/icme/2019/9552/0",
"title": "2019 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1KxUhhFgzlK",
"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"acronym": "wacv",
"groupId": "1000040",
"volume": "0",
"displayVolume": "0",
"year": "2023",
"__typename": "ProceedingType"
},
"article": {
"id": "1L8qk4xmpvW",
"doi": "10.1109/WACV56688.2023.00346",
"title": "Fine Gaze Redirection Learning with Gaze Hardness-aware Transformation",
"normalizedTitle": "Fine Gaze Redirection Learning with Gaze Hardness-aware Transformation",
"abstract": "The gaze redirection is a task to adjust the gaze of a given face or eye image toward the desired direction and aims to learn the gaze direction of a face image through a neural network-based generator. Considering that the prior arts have learned coarse gaze directions, learning fine gaze directions is very challenging. In addition, explicit discriminative learning of high-dimensional gaze features has not been reported yet. This paper presents solutions to overcome the above limitations. First, we propose the feature-level transformation which provides gaze features corresponding to various gaze directions in the latent feature space. Second, we propose a novel loss function for discriminative learning of gaze features. Specifically, features with insignificant or irrelevant effects on gaze (e.g., head pose and appearance) are set as negative pairs, and important gaze features are set as positive pairs, and then pair-wise similarity learning is performed. As a result, the proposed method showed a redirection error of only 2° for the Gaze-Capture dataset. This is a 10% better performance than a state-of-the-art method, i.e., STED. Additionally, the rationale for why latent features of various attributes should be discriminated is presented through activation visualization. Code is available at https://github.com/san9569/Gaze-Redir-Learning",
"abstracts": [
{
"abstractType": "Regular",
"content": "The gaze redirection is a task to adjust the gaze of a given face or eye image toward the desired direction and aims to learn the gaze direction of a face image through a neural network-based generator. Considering that the prior arts have learned coarse gaze directions, learning fine gaze directions is very challenging. In addition, explicit discriminative learning of high-dimensional gaze features has not been reported yet. This paper presents solutions to overcome the above limitations. First, we propose the feature-level transformation which provides gaze features corresponding to various gaze directions in the latent feature space. Second, we propose a novel loss function for discriminative learning of gaze features. Specifically, features with insignificant or irrelevant effects on gaze (e.g., head pose and appearance) are set as negative pairs, and important gaze features are set as positive pairs, and then pair-wise similarity learning is performed. As a result, the proposed method showed a redirection error of only 2° for the Gaze-Capture dataset. This is a 10% better performance than a state-of-the-art method, i.e., STED. Additionally, the rationale for why latent features of various attributes should be discriminated is presented through activation visualization. Code is available at https://github.com/san9569/Gaze-Redir-Learning",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The gaze redirection is a task to adjust the gaze of a given face or eye image toward the desired direction and aims to learn the gaze direction of a face image through a neural network-based generator. Considering that the prior arts have learned coarse gaze directions, learning fine gaze directions is very challenging. In addition, explicit discriminative learning of high-dimensional gaze features has not been reported yet. This paper presents solutions to overcome the above limitations. First, we propose the feature-level transformation which provides gaze features corresponding to various gaze directions in the latent feature space. Second, we propose a novel loss function for discriminative learning of gaze features. Specifically, features with insignificant or irrelevant effects on gaze (e.g., head pose and appearance) are set as negative pairs, and important gaze features are set as positive pairs, and then pair-wise similarity learning is performed. As a result, the proposed method showed a redirection error of only 2° for the Gaze-Capture dataset. This is a 10% better performance than a state-of-the-art method, i.e., STED. Additionally, the rationale for why latent features of various attributes should be discriminated is presented through activation visualization. Code is available at https://github.com/san9569/Gaze-Redir-Learning",
"fno": "934600d453",
"keywords": [
"Face Recognition",
"Feature Extraction",
"Gaze Tracking",
"Learning Artificial Intelligence",
"Coarse Gaze Directions",
"Explicit Discriminative Learning",
"Face Image",
"Feature Level Transformation",
"Fine Gaze Directions",
"Fine Gaze Redirection",
"Gaze Direction",
"Gaze Hardness Aware Transformation",
"Gaze Capture Dataset",
"Given Face",
"High Dimensional Gaze Features",
"Important Gaze Features",
"Latent Feature Space",
"Latent Features",
"Neural Network Based Generator",
"Pair Wise Similarity Learning",
"Representation Learning",
"Computer Vision",
"Visualization",
"Emotion Recognition",
"Costs",
"Codes",
"Face Recognition",
"Algorithms Biometrics",
"Face",
"Gesture",
"Body Pose"
],
"authors": [
{
"affiliation": "Inha University,Incheon,Republic of Korea",
"fullName": "Sangjin Park",
"givenName": "Sangjin",
"surname": "Park",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Inha University,Incheon,Republic of Korea",
"fullName": "Daeha Kim",
"givenName": "Daeha",
"surname": "Kim",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Inha University,Incheon,Republic of Korea",
"fullName": "Byung Cheol Song",
"givenName": "Byung Cheol",
"surname": "Song",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wacv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2023-01-01T00:00:00",
"pubType": "proceedings",
"pages": "3453-3462",
"year": "2023",
"issn": null,
"isbn": "978-1-6654-9346-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "934600d443",
"articleId": "1KxUl0GLfXi",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "934600d463",
"articleId": "1KxVHXYfgeQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iciap/2003/1948/0/19480076",
"title": "Virtual Gaze Redirection in Face Images",
"doi": null,
"abstractUrl": "/proceedings-article/iciap/2003/19480076/12OmNvAAtnK",
"parentPublication": {
"id": "proceedings/iciap/2003/1948/0",
"title": "Image Analysis and Processing, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2018/2335/0/233501a535",
"title": "Semi-Supervised Learning for Monocular Gaze Redirection",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2018/233501a535/12OmNy3Agnw",
"parentPublication": {
"id": "proceedings/fg/2018/2335/0",
"title": "2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2018/11/08010348",
"title": "Photorealistic Monocular Gaze Redirection Using Machine Learning",
"doi": null,
"abstractUrl": "/journal/tp/2018/11/08010348/143fh3uFDe8",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2022/8739/0/873900e997",
"title": "Unsupervised Multi-View Gaze Representation Learning",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2022/873900e997/1G56gozrPk4",
"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": "proceedings/cvpr/2022/6946/0/694600t9354",
"title": "Contrastive Regression for Domain Adaptation on Gaze Estimation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600t9354/1H0OmLK7q5q",
"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/cvpr/2019/3293/0/329300l1929",
"title": "Improving Few-Shot User-Specific Gaze Adaptation via Gaze Redirection Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2019/329300l1929/1gys6XNKVqg",
"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/2019/4803/0/480300g931",
"title": "Photo-Realistic Monocular Gaze Redirection Using Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300g931/1hVloxAEVA4",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800h312",
"title": "Unsupervised Representation Learning for Gaze Estimation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800h312/1m3o4PL98Q0",
"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/wacv/2021/0477/0/047700d664",
"title": "Coarse-to-Fine Gaze Redirection with Numerical and Pictorial Guidance",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700d664/1uqGBx4qqoU",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2021/0477/0/047700a011",
"title": "Subject Guided Eye Image Synthesis with Application to Gaze Redirection",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700a011/1uqGyw32uVq",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1pystLSz19C",
"title": "2020 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"acronym": "ismar",
"groupId": "1000465",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1pystZgPICk",
"doi": "10.1109/ISMAR50242.2020.00030",
"title": "Digital Full-Face Mask Display with Expression Recognition using Embedded Photo Reflective Sensor Arrays",
"normalizedTitle": "Digital Full-Face Mask Display with Expression Recognition using Embedded Photo Reflective Sensor Arrays",
"abstract": "This paper presents a thin digital full-face mask display that can reflect an entire facial expression of a user onto an avatar to support augmented face-to-face communication in real environments. Although camera-based facial expression recognition technology has enabled people to augment their faces with avatars, application was limited to face-to-face communication in virtual environments. To enable digital facial augmentation with an avatar in a real space, we propose a digital face mask display system that integrates a lightweight flexible display with a thin facial expression recognition system. The thin wearable facial expression recognition system was implemented with photo reflective sensor arrays which can measure facial expressions at 40 feature points distributed across an entire face. We investigated a ten-class facial expression identification model based on an SVM training algorithm. The trained model achieved an average accuracy of 79% when identifying the facial expressions of multiple users. User experiments indicated that the proposed thin digital full-face mask display allows the wearer to control the facial expression of the avatar with a fast response rate and create a positive sense of self-agency and self-ownership toward the augmented avatar face.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper presents a thin digital full-face mask display that can reflect an entire facial expression of a user onto an avatar to support augmented face-to-face communication in real environments. Although camera-based facial expression recognition technology has enabled people to augment their faces with avatars, application was limited to face-to-face communication in virtual environments. To enable digital facial augmentation with an avatar in a real space, we propose a digital face mask display system that integrates a lightweight flexible display with a thin facial expression recognition system. The thin wearable facial expression recognition system was implemented with photo reflective sensor arrays which can measure facial expressions at 40 feature points distributed across an entire face. We investigated a ten-class facial expression identification model based on an SVM training algorithm. The trained model achieved an average accuracy of 79% when identifying the facial expressions of multiple users. User experiments indicated that the proposed thin digital full-face mask display allows the wearer to control the facial expression of the avatar with a fast response rate and create a positive sense of self-agency and self-ownership toward the augmented avatar face.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper presents a thin digital full-face mask display that can reflect an entire facial expression of a user onto an avatar to support augmented face-to-face communication in real environments. Although camera-based facial expression recognition technology has enabled people to augment their faces with avatars, application was limited to face-to-face communication in virtual environments. To enable digital facial augmentation with an avatar in a real space, we propose a digital face mask display system that integrates a lightweight flexible display with a thin facial expression recognition system. The thin wearable facial expression recognition system was implemented with photo reflective sensor arrays which can measure facial expressions at 40 feature points distributed across an entire face. We investigated a ten-class facial expression identification model based on an SVM training algorithm. The trained model achieved an average accuracy of 79% when identifying the facial expressions of multiple users. User experiments indicated that the proposed thin digital full-face mask display allows the wearer to control the facial expression of the avatar with a fast response rate and create a positive sense of self-agency and self-ownership toward the augmented avatar face.",
"fno": "850800a101",
"keywords": [
"Avatars",
"Emotion Recognition",
"Face Recognition",
"Feature Extraction",
"Image Sensors",
"Sensor Arrays",
"Support Vector Machines",
"Digital Full Face Mask Display",
"Embedded Photo Reflective Sensor",
"Entire Facial Expression",
"Augmented Face To Face Communication",
"Camera Based Facial Expression Recognition Technology",
"Digital Facial Augmentation",
"Digital Face Mask Display System",
"Wearable Facial Expression Recognition System",
"Photo Reflective Sensor Arrays",
"Ten Class Facial Expression Identification Model",
"Augmented Avatar Face",
"Support Vector Machines",
"Training",
"Face Recognition",
"Avatars",
"Virtual Environments",
"Faces",
"Sensor Arrays",
"Human Centered Computing",
"Visualization",
"Visualization Techniques",
"Treemaps",
"Human Centered Computing",
"Visualization",
"Visualization Design And Evaluation Methods"
],
"authors": [
{
"affiliation": "Future University Hakodate",
"fullName": "Yoshinari Takegawa",
"givenName": "Yoshinari",
"surname": "Takegawa",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Freelance",
"fullName": "Yutaka Tokuda",
"givenName": "Yutaka",
"surname": "Tokuda",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Future University Hakodate",
"fullName": "Akino Umezawa",
"givenName": "Akino",
"surname": "Umezawa",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Keio University",
"fullName": "Katsuhiro Suzuki",
"givenName": "Katsuhiro",
"surname": "Suzuki",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Keio University",
"fullName": "Katsutoshi Masai",
"givenName": "Katsutoshi",
"surname": "Masai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Keio University",
"fullName": "Yuta Sugiura",
"givenName": "Yuta",
"surname": "Sugiura",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Keio University",
"fullName": "Maki Sugimoto",
"givenName": "Maki",
"surname": "Sugimoto",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University College London",
"fullName": "Diego Martinez Plasencia",
"givenName": "Diego Martinez",
"surname": "Plasencia",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University College London",
"fullName": "Sriram Subramanian",
"givenName": "Sriram",
"surname": "Subramanian",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Future University Hakodate",
"fullName": "Keiji Hirata",
"givenName": "Keiji",
"surname": "Hirata",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ismar",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-11-01T00:00:00",
"pubType": "proceedings",
"pages": "101-108",
"year": "2020",
"issn": "1554-7868",
"isbn": "978-1-7281-8508-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "850800a090",
"articleId": "1pysugzeg24",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "850800a109",
"articleId": "1pysuUuZCwM",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/fg/2011/9140/0/05771364",
"title": "Facial expression recognition using emotion avatar image",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2011/05771364/12OmNAi6vUx",
"parentPublication": {
"id": "proceedings/fg/2011/9140/0",
"title": "Face and Gesture 2011",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2015/6026/1/07163173",
"title": "Real-time facial character animation",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2015/07163173/12OmNApcuBK",
"parentPublication": {
"id": "proceedings/fg/2015/6026/5",
"title": "2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgames/2011/1451/0/06000330",
"title": "Artificial human face recognition via Daubechies wavelet transform and SVM",
"doi": null,
"abstractUrl": "/proceedings-article/cgames/2011/06000330/12OmNBlofOE",
"parentPublication": {
"id": "proceedings/cgames/2011/1451/0",
"title": "2011 16th International Conference on Computer Games (CGAMES)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2017/6647/0/07892245",
"title": "Recognition and mapping of facial expressions to avatar by embedded photo reflective sensors in head mounted display",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2017/07892245/12OmNwkR5tU",
"parentPublication": {
"id": "proceedings/vr/2017/6647/0",
"title": "2017 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2008/2570/0/04607657",
"title": "Real-time conversion from a single 2D face image to a 3D text-driven emotive audio-visual avatar",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2008/04607657/12OmNx3HI5p",
"parentPublication": {
"id": "proceedings/icme/2008/2570/0",
"title": "2008 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/2020/02/08319988",
"title": "Emotion Recognition in Simulated Social Interactions",
"doi": null,
"abstractUrl": "/journal/ta/2020/02/08319988/13rRUB7a1ea",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2018/7592/0/08699208",
"title": "Demonstrating Emotion Sharing and Augmentation in Cooperative Virtual Reality Games",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2018/08699208/19F1PYyd2De",
"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/5555/01/09786815",
"title": "Analyzing the Effect of Diverse Gaze and Head Direction on Facial Expression Recognition with Photo-Reflective Sensors Embedded in a Head-Mounted Display",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09786815/1DSumaVNxG8",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2020/05/08998352",
"title": "Using Facial Animation to Increase the Enfacement Illusion and Avatar Self-Identification",
"doi": null,
"abstractUrl": "/journal/tg/2020/05/08998352/1hpPCCB7Bte",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300c575",
"title": "A Realistic Face-to-Face Conversation System Based on Deep Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300c575/1i5mlM6tlks",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxX3uNG",
"title": "2012 IEEE 30th International Conference on Computer Design (ICCD 2012)",
"acronym": "iccd",
"groupId": "1000129",
"volume": "0",
"displayVolume": "0",
"year": "2012",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNx4yvqG",
"doi": "10.1109/ICCD.2012.6378658",
"title": "A spectral transform approach to stochastic circuits",
"normalizedTitle": "A spectral transform approach to stochastic circuits",
"abstract": "Stochastic computing (SC) processes data in the form of long pseudo-random bit-streams denoting probabilities. Its key advantages are simple computational elements and high soft-error tolerance. Recent technology developments have revealed important new SC applications such as image processing and LDPC decoding. Despite its long history, SC still lacks a comprehensive design methodology; existing methods tend to be ad hoc and limited to a few arithmetic functions. We demonstrate a fundamental relation between stochastic circuits and spectral transforms. Based on this, we propose a transform approach to the analysis and synthesis of SC circuits. We illustrate the approach for a variety of basic combinational SC design problems, and show that the area cost associated with stochastic number generation can be significantly reduced.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Stochastic computing (SC) processes data in the form of long pseudo-random bit-streams denoting probabilities. Its key advantages are simple computational elements and high soft-error tolerance. Recent technology developments have revealed important new SC applications such as image processing and LDPC decoding. Despite its long history, SC still lacks a comprehensive design methodology; existing methods tend to be ad hoc and limited to a few arithmetic functions. We demonstrate a fundamental relation between stochastic circuits and spectral transforms. Based on this, we propose a transform approach to the analysis and synthesis of SC circuits. We illustrate the approach for a variety of basic combinational SC design problems, and show that the area cost associated with stochastic number generation can be significantly reduced.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Stochastic computing (SC) processes data in the form of long pseudo-random bit-streams denoting probabilities. Its key advantages are simple computational elements and high soft-error tolerance. Recent technology developments have revealed important new SC applications such as image processing and LDPC decoding. Despite its long history, SC still lacks a comprehensive design methodology; existing methods tend to be ad hoc and limited to a few arithmetic functions. We demonstrate a fundamental relation between stochastic circuits and spectral transforms. Based on this, we propose a transform approach to the analysis and synthesis of SC circuits. We illustrate the approach for a variety of basic combinational SC design problems, and show that the area cost associated with stochastic number generation can be significantly reduced.",
"fno": "315alaghi",
"keywords": [
"Fourier Transforms",
"Vectors",
"Polynomials",
"Tin",
"Parity Check Codes",
"Accuracy",
"Stochastic Computing",
"Design Methodology",
"Logic Synthesis",
"Probabilistic Methods"
],
"authors": [],
"idPrefix": "iccd",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2012-09-01T00:00:00",
"pubType": "proceedings",
"pages": "315-321",
"year": "2012",
"issn": "1063-6404",
"isbn": "978-1-4673-3051-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "309jaksic",
"articleId": "12OmNALUowq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "322zaynoun",
"articleId": "12OmNxdVgS8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccd/2016/5142/0/07753265",
"title": "Isolation-based decorrelation of stochastic circuits",
"doi": null,
"abstractUrl": "/proceedings-article/iccd/2016/07753265/12OmNBQkx2i",
"parentPublication": {
"id": "proceedings/iccd/2016/5142/0",
"title": "2016 IEEE 34th International Conference on Computer Design (ICCD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dsd/2014/5793/0/5793a356",
"title": "Stochastic Logic Realization of Matrix Operations",
"doi": null,
"abstractUrl": "/proceedings-article/dsd/2014/5793a356/12OmNxYtuca",
"parentPublication": {
"id": "proceedings/dsd/2014/5793/0",
"title": "2014 17th Euromicro Conference on Digital System Design (DSD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvlsid/2016/9039/0/9039a116",
"title": "Design of Division Circuits for Stochastic Computing",
"doi": null,
"abstractUrl": "/proceedings-article/isvlsid/2016/9039a116/12OmNxxNbPM",
"parentPublication": {
"id": "proceedings/isvlsid/2016/9039/0",
"title": "2016 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dft/2017/0362/0/08244436",
"title": "Eliminating a hidden error source in stochastic circuits",
"doi": null,
"abstractUrl": "/proceedings-article/dft/2017/08244436/12OmNy3iFju",
"parentPublication": {
"id": "proceedings/dft/2017/0362/0",
"title": "2017 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccd/2013/2987/0/06657023",
"title": "Exploiting correlation in stochastic circuit design",
"doi": null,
"abstractUrl": "/proceedings-article/iccd/2013/06657023/12OmNz2C1yO",
"parentPublication": {
"id": "proceedings/iccd/2013/2987/0",
"title": "2013 IEEE 31st International Conference on Computer Design (ICCD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ec/2019/01/07727954",
"title": "Equivalence Among Stochastic Logic Circuits and its Application to Synthesis",
"doi": null,
"abstractUrl": "/journal/ec/2019/01/07727954/13rRUwInvaR",
"parentPublication": {
"id": "trans/ec",
"title": "IEEE Transactions on Emerging Topics in Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2018/07/08327916",
"title": "Toward Energy-Efficient Stochastic Circuits Using Parallel Sobol Sequences",
"doi": null,
"abstractUrl": "/journal/si/2018/07/08327916/13rRUxYIN1I",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvlsi/2019/3391/0/339100a271",
"title": "Impact of Autocorrelation on Stochastic Circuit Accuracy",
"doi": null,
"abstractUrl": "/proceedings-article/isvlsi/2019/339100a271/1dUnMtNeKnS",
"parentPublication": {
"id": "proceedings/isvlsi/2019/3391/0",
"title": "2019 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/si/2020/08/09119189",
"title": "Deterministic Shuffling Networks to Implement Stochastic Circuits in Parallel",
"doi": null,
"abstractUrl": "/journal/si/2020/08/09119189/1kHULsOlbpe",
"parentPublication": {
"id": "trans/si",
"title": "IEEE Transactions on Very Large Scale Integration (VLSI) Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isvlsi/2020/5775/0/577500a422",
"title": "Efficient Hardware Implementation of Discrete Wavelet Transform Based on Stochastic Computing",
"doi": null,
"abstractUrl": "/proceedings-article/isvlsi/2020/577500a422/1m1iUngSNwc",
"parentPublication": {
"id": "proceedings/isvlsi/2020/5775/0",
"title": "2020 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1B12DGrwoyQ",
"title": "2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"acronym": "wacv",
"groupId": "1000040",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1B12OZCI3JK",
"doi": "10.1109/WACV51458.2022.00103",
"title": "AE-StyleGAN: Improved Training of Style-Based Auto-Encoders",
"normalizedTitle": "AE-StyleGAN: Improved Training of Style-Based Auto-Encoders",
"abstract": "StyleGANs have shown impressive results on data generation and manipulation in recent years, thanks to its disentangled style latent space. A lot of efforts have been made in inverting a pretrained generator, where an encoder is trained ad hoc after the generator is trained in a two-stage fashion. In this paper, we focus on style-based generators asking a scientific question: Does forcing such a generator to reconstruct real data lead to more disentangled latent space and make the inversion process from image to latent space easy? We describe a new methodology to train a style-based autoencoder where the encoder and generator are optimized end-to-end. We show that our proposed model consistently outperforms baselines in terms of image inversion and generation quality. Supplementary, code, and pretrained models are available on the project website<sup>1</sup>.",
"abstracts": [
{
"abstractType": "Regular",
"content": "StyleGANs have shown impressive results on data generation and manipulation in recent years, thanks to its disentangled style latent space. A lot of efforts have been made in inverting a pretrained generator, where an encoder is trained ad hoc after the generator is trained in a two-stage fashion. In this paper, we focus on style-based generators asking a scientific question: Does forcing such a generator to reconstruct real data lead to more disentangled latent space and make the inversion process from image to latent space easy? We describe a new methodology to train a style-based autoencoder where the encoder and generator are optimized end-to-end. We show that our proposed model consistently outperforms baselines in terms of image inversion and generation quality. Supplementary, code, and pretrained models are available on the project website<sup>1</sup>.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "StyleGANs have shown impressive results on data generation and manipulation in recent years, thanks to its disentangled style latent space. A lot of efforts have been made in inverting a pretrained generator, where an encoder is trained ad hoc after the generator is trained in a two-stage fashion. In this paper, we focus on style-based generators asking a scientific question: Does forcing such a generator to reconstruct real data lead to more disentangled latent space and make the inversion process from image to latent space easy? We describe a new methodology to train a style-based autoencoder where the encoder and generator are optimized end-to-end. We show that our proposed model consistently outperforms baselines in terms of image inversion and generation quality. Supplementary, code, and pretrained models are available on the project website1.",
"fno": "091500a955",
"keywords": [
"Data Analysis",
"Encoding",
"Gaussian Processes",
"Learning Artificial Intelligence",
"Neural Nets",
"Style Based Auto Encoders",
"Style GA Ns",
"Data Generation",
"Disentangled Style Latent Space",
"Pretrained Generator",
"Two Stage Fashion",
"Style Based Generators",
"Disentangled Latent Space",
"Style Based Autoencoder",
"Image Inversion",
"Generation Quality",
"Improved Training",
"Training",
"Computer Vision",
"Codes",
"Image Synthesis",
"Generators",
"Image Reconstruction",
"Deep Learning X 003 E Neural Generative Models Autoencoders GA Ns Computational Photography Image And Video Synthesis"
],
"authors": [
{
"affiliation": "Rutgers University",
"fullName": "Ligong Han",
"givenName": "Ligong",
"surname": "Han",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Rutgers University",
"fullName": "Sri Harsha Musunuri",
"givenName": "Sri Harsha",
"surname": "Musunuri",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "NEC Labs America",
"fullName": "Martin Renqiang Min",
"givenName": "Martin",
"surname": "Renqiang Min",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "The University of Texas at Austin",
"fullName": "Ruijiang Gao",
"givenName": "Ruijiang",
"surname": "Gao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Rutgers University",
"fullName": "Yu Tian",
"givenName": "Yu",
"surname": "Tian",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Rutgers University",
"fullName": "Dimitris Metaxas",
"givenName": "Dimitris",
"surname": "Metaxas",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wacv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-01-01T00:00:00",
"pubType": "proceedings",
"pages": "955-964",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-0915-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "091500a944",
"articleId": "1B13AO3WYa4",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "091500a965",
"articleId": "1B13HiwSCBy",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2019/1975/0/197500a848",
"title": "Style and Content Disentanglement in Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2019/197500a848/18j8FazPuwM",
"parentPublication": {
"id": "proceedings/wacv/2019/1975/0",
"title": "2019 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200g701",
"title": "Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200g701/1BmIMPAjiLe",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/03/09792208",
"title": "GAN Inversion: A Survey",
"doi": null,
"abstractUrl": "/journal/tp/2023/03/09792208/1E5LCU0gJAk",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600l1327",
"title": "Style Transformer for Image Inversion and Editing",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600l1327/1H0ND0u1zXi",
"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/2023/9346/0/934600e308",
"title": "SketchInverter: Multi-Class Sketch-Based Image Generation via GAN Inversion",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600e308/1L8qBcO17xe",
"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/iccv/2019/4803/0/480300k0530",
"title": "Image Synthesis From Reconfigurable Layout and Style",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300k0530/1hVlpxVSLMA",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800i107",
"title": "Analyzing and Improving the Image Quality of StyleGAN",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800i107/1m3nK5FMmWI",
"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/2021/4509/0/450900d711",
"title": "StEP: Style-based Encoder Pre-training for Multi-modal Image Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900d711/1yeIcxFg1NK",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900c287",
"title": "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900c287/1yeK0CkwCJ2",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900m2858",
"title": "StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900m2858/1yeLlVDbKDu",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1BmEezmpGrm",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"acronym": "iccv",
"groupId": "1000149",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1BmIpDwamYg",
"doi": "10.1109/ICCV48922.2021.00669",
"title": "Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation",
"normalizedTitle": "Multi-Class Multi-Instance Count Conditioned Adversarial Image Generation",
"abstract": "Image generation has rapidly evolved in recent years. Modern architectures for adversarial training allow to generate even high resolution images with remarkable quality. At the same time, more and more effort is dedicated towards controlling the content of generated images. In this paper, we take one further step in this direction and propose a conditional generative adversarial network (GAN) that generates images with a defined number of objects from given classes. This entails two fundamental abilities (1) being able to generate high-quality images given a complex constraint and (2) being able to count object instances per class in a given image. Our proposed model modularly extends the successful StyleGAN2 architecture with a count-based conditioning as well as with a regression subnetwork to count the number of generated objects per class during training. In experiments on three different datasets, we show that the proposed model learns to generate images according to the given multiple-class count condition even in the presence of complex backgrounds. In particular, we propose a new dataset, CityCount, which is derived from the Cityscapes street scenes dataset, to evaluate our approach in a challenging and practically relevant scenario. An implementation is available at https://github.com/boschresearch/MCCGAN.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Image generation has rapidly evolved in recent years. Modern architectures for adversarial training allow to generate even high resolution images with remarkable quality. At the same time, more and more effort is dedicated towards controlling the content of generated images. In this paper, we take one further step in this direction and propose a conditional generative adversarial network (GAN) that generates images with a defined number of objects from given classes. This entails two fundamental abilities (1) being able to generate high-quality images given a complex constraint and (2) being able to count object instances per class in a given image. Our proposed model modularly extends the successful StyleGAN2 architecture with a count-based conditioning as well as with a regression subnetwork to count the number of generated objects per class during training. In experiments on three different datasets, we show that the proposed model learns to generate images according to the given multiple-class count condition even in the presence of complex backgrounds. In particular, we propose a new dataset, CityCount, which is derived from the Cityscapes street scenes dataset, to evaluate our approach in a challenging and practically relevant scenario. An implementation is available at https://github.com/boschresearch/MCCGAN.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Image generation has rapidly evolved in recent years. Modern architectures for adversarial training allow to generate even high resolution images with remarkable quality. At the same time, more and more effort is dedicated towards controlling the content of generated images. In this paper, we take one further step in this direction and propose a conditional generative adversarial network (GAN) that generates images with a defined number of objects from given classes. This entails two fundamental abilities (1) being able to generate high-quality images given a complex constraint and (2) being able to count object instances per class in a given image. Our proposed model modularly extends the successful StyleGAN2 architecture with a count-based conditioning as well as with a regression subnetwork to count the number of generated objects per class during training. In experiments on three different datasets, we show that the proposed model learns to generate images according to the given multiple-class count condition even in the presence of complex backgrounds. In particular, we propose a new dataset, CityCount, which is derived from the Cityscapes street scenes dataset, to evaluate our approach in a challenging and practically relevant scenario. An implementation is available at https://github.com/boschresearch/MCCGAN.",
"fno": "281200g742",
"keywords": [
"Training",
"Representation Learning",
"Deep Learning",
"Image Resolution",
"Image Synthesis",
"Layout",
"Training Data",
"Neural Generative Models",
"Adversarial Learning"
],
"authors": [
{
"affiliation": "Bosch Center for Artificial Intelligence",
"fullName": "Amrutha Saseendran",
"givenName": "Amrutha",
"surname": "Saseendran",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Bosch Center for Artificial Intelligence",
"fullName": "Kathrin Skubch",
"givenName": "Kathrin",
"surname": "Skubch",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Siegen",
"fullName": "Margret Keuper",
"givenName": "Margret",
"surname": "Keuper",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-10-01T00:00:00",
"pubType": "proceedings",
"pages": "6742-6751",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-2812-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "281200g732",
"articleId": "1BmFEEiiMxO",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "281200g752",
"articleId": "1BmHANMNcoE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iccv/2017/1032/0/1032f908",
"title": "StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/1032f908/12OmNA0MZ6U",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2017/1032/0/1032d430",
"title": "Generative Adversarial Networks Conditioned by Brain Signals",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2017/1032d430/12OmNCd2rEw",
"parentPublication": {
"id": "proceedings/iccv/2017/1032/0",
"title": "2017 IEEE International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2017/0457/0/0457g212",
"title": "Multi-attention Network for One Shot Learning",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2017/0457g212/12OmNx1IweT",
"parentPublication": {
"id": "proceedings/cvpr/2017/0457/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/paap/2018/9403/0/940300a211",
"title": "Face Inpainting with Dilated Skip Architecture and Multi-Scale Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/paap/2018/940300a211/19JE8usg6e4",
"parentPublication": {
"id": "proceedings/paap/2018/9403/0",
"title": "2018 9th International Symposium on Parallel Architectures, Algorithms and Programming (PAAP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibm/2021/0126/0/09669432",
"title": "Automated Nanoparticle Count via Modified BlendMask Instance Segmentation on SEM Images",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2021/09669432/1A9W83paoIo",
"parentPublication": {
"id": "proceedings/bibm/2021/0126/0",
"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2022/0915/0/091500d471",
"title": "Data InStance Prior (DISP) in Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500d471/1B13NlSy9CU",
"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/crv/2019/1838/0/183800a073",
"title": "Hierarchically-Fused Generative Adversarial Network for Text to Realistic Image Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/crv/2019/183800a073/1cMGv40ulTa",
"parentPublication": {
"id": "proceedings/crv/2019/1838/0",
"title": "2019 16th Conference on Computer and Robot Vision (CRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2020/7081/0/708100a479",
"title": "An Feature Image Generation Based on Adversarial Generation Network",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2020/708100a479/1iEREwoRJF6",
"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/cvprw/2020/9360/0/09150661",
"title": "Real-World Super-Resolution using Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2020/09150661/1lPH66Ff2HS",
"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/icpr/2021/8808/0/09412022",
"title": "Attributes Aware Face Generation with Generative Adversarial Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412022/1tmimHQIteE",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1EVihIUabss",
"title": "2021 Ninth International Conference on Advanced Cloud and Big Data (CBD)",
"acronym": "cbd",
"groupId": "1803748",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1EViqpCPS00",
"doi": "10.1109/CBD54617.2021.00033",
"title": "Embedding Chinese Face Painting Into the StyleGAN Latent Space",
"normalizedTitle": "Embedding Chinese Face Painting Into the StyleGAN Latent Space",
"abstract": "We propose an efficient algorithm to embed China’s traditional Chinese painting into the latent space of StyleGAN for the first time in the presence of noise. This embedding allows us to complete the pluralistic image editing of Chinese painting style faces by using only the StyleGAN pretraining face model without the need to retrain new models. Compared to the previous reverse network StyleGAN-Encoder, the new training model can improve the image generation speed under noise by 10% and FID by approximately 21%. We for the first time propose the application of the deep residual shrinkage networks to the image generation problem and verify the effectiveness of the proposed method through experiments on various noises.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose an efficient algorithm to embed China’s traditional Chinese painting into the latent space of StyleGAN for the first time in the presence of noise. This embedding allows us to complete the pluralistic image editing of Chinese painting style faces by using only the StyleGAN pretraining face model without the need to retrain new models. Compared to the previous reverse network StyleGAN-Encoder, the new training model can improve the image generation speed under noise by 10% and FID by approximately 21%. We for the first time propose the application of the deep residual shrinkage networks to the image generation problem and verify the effectiveness of the proposed method through experiments on various noises.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose an efficient algorithm to embed China’s traditional Chinese painting into the latent space of StyleGAN for the first time in the presence of noise. This embedding allows us to complete the pluralistic image editing of Chinese painting style faces by using only the StyleGAN pretraining face model without the need to retrain new models. Compared to the previous reverse network StyleGAN-Encoder, the new training model can improve the image generation speed under noise by 10% and FID by approximately 21%. We for the first time propose the application of the deep residual shrinkage networks to the image generation problem and verify the effectiveness of the proposed method through experiments on various noises.",
"fno": "074500a145",
"keywords": [
"Art",
"Feature Extraction",
"Image Processing",
"Image Texture",
"Painting",
"Rendering Computer Graphics",
"Embedding Chinese Face Painting",
"Style GAN Latent Space",
"Chinas Traditional Chinese Painting",
"Pluralistic Image Editing",
"Chinese Painting Style Faces",
"Style GAN Pretraining Face Model",
"Previous Reverse Network Style GAN Encoder",
"Training Model",
"Deep Residual Shrinkage Networks",
"Image Generation Problem",
"Training",
"Image Synthesis",
"Big Data",
"Search Problems",
"Faces",
"Painting",
"Style GAN",
"China X 2019 S Traditional Chinese Painting",
"Image Editing",
"Embedded Images",
"Deep Residual Shrinkage Networks"
],
"authors": [
{
"affiliation": "Xi’an Polytechnic University,Xi’an,China",
"fullName": "Pengsen Ma",
"givenName": "Pengsen",
"surname": "Ma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Xi’an Polytechnic University,Xi’an,China",
"fullName": "Tao Xue",
"givenName": "Tao",
"surname": "Xue",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cbd",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-03-01T00:00:00",
"pubType": "proceedings",
"pages": "145-150",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-0745-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "074500a139",
"articleId": "1EVimhCVkQw",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "074500a151",
"articleId": "1EVihRuXgBy",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ismar-amh/2009/5508/0/05336722",
"title": "An intuitional interface for invocation of Chinese painting",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-amh/2009/05336722/12OmNAlvI7Q",
"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/cisp/2008/3119/4/3119d570",
"title": "Content-Based Identifying and Classifying Traditional Chinese Painting Images",
"doi": null,
"abstractUrl": "/proceedings-article/cisp/2008/3119d570/12OmNBqdrfJ",
"parentPublication": {
"id": "proceedings/cisp/2008/3119/4",
"title": "Image and Signal Processing, Congress on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pg/2002/1784/0/17840403",
"title": "Two Methods for Creating Chinese Painting",
"doi": null,
"abstractUrl": "/proceedings-article/pg/2002/17840403/12OmNqJZgA3",
"parentPublication": {
"id": "proceedings/pg/2002/1784/0",
"title": "Computer Graphics and Applications, Pacific Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mediacom/2010/4136/0/4136a153",
"title": "A Survey of Rendering of Chinese Painting",
"doi": null,
"abstractUrl": "/proceedings-article/mediacom/2010/4136a153/12OmNrJ11w2",
"parentPublication": {
"id": "proceedings/mediacom/2010/4136/0",
"title": "2010 International Conference on Multimedia Communications (Mediacom 2010)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/etcs/2010/3987/2/3987b777",
"title": "Chinese Painting Education Under the Contemporary Situation",
"doi": null,
"abstractUrl": "/proceedings-article/etcs/2010/3987b777/12OmNs0C9Gn",
"parentPublication": {
"id": "proceedings/etcs/2010/3987/2",
"title": "Education Technology and Computer Science, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2012/4836/0/4836a013",
"title": "An Automatic Rendering Method of Line Strokes for Chinese Landscape Painting",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2012/4836a013/12OmNy3RRF5",
"parentPublication": {
"id": "proceedings/icvrv/2012/4836/0",
"title": "2012 International Conference on Virtual Reality and Visualization",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09784910",
"title": "DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09784910/1DPaE3QYx68",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdar/2019/3014/0/301400a819",
"title": "An Interactive and Generative Approach for Chinese Shanshui Painting Document",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2019/301400a819/1h81Bl0UDNC",
"parentPublication": {
"id": "proceedings/icdar/2019/3014/0",
"title": "2019 International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccst/2020/8138/0/813800a383",
"title": "Feature Fusion based Cross-modal Retrieval for Traditional Chinese Painting",
"doi": null,
"abstractUrl": "/proceedings-article/iccst/2020/813800a383/1p1grPqwumQ",
"parentPublication": {
"id": "proceedings/iccst/2020/8138/0",
"title": "2020 International Conference on Culture-oriented Science & Technology (ICCST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09413063",
"title": "Attentional Wavelet Network for Traditional Chinese Painting Transfer",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09413063/1tmjgT9yL4I",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1H1gVMlkl32",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1H0NNPChQsM",
"doi": "10.1109/CVPR52688.2022.00754",
"title": "Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer",
"normalizedTitle": "Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer",
"abstract": "Recent studies on StyleGAN show high performance on artistic portrait generation by transfer learning with limited data. In this paper, we explore more challenging exemplar-based high-resolution portrait style transfer by introducing a novel DualStyleGAN with flexible control of dual styles of the original face domain and the extended artistic portrait domain. Different from StyleGAN, DualStyleGAN provides a natural way of style transfer by characterizing the content and style of a portrait with an intrinsic style path and a new extrinsic style path, respectively. The del-icately designed extrinsic style path enables our model to modulate both the color and complex structural styles hierarchically to precisely pastiche the style example. Furthermore, a novel progressive fine-tuning scheme is introduced to smoothly transform the generative space of the model to the target domain, even with the above modifications on the network architecture. Experiments demonstrate the superiority of DualStyleGAN over state-of-the-art methods in high-quality portrait style transfer and flexible stylecontrol. Code is available at https://github.com/williamyang1991/DualStyleGAN.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recent studies on StyleGAN show high performance on artistic portrait generation by transfer learning with limited data. In this paper, we explore more challenging exemplar-based high-resolution portrait style transfer by introducing a novel DualStyleGAN with flexible control of dual styles of the original face domain and the extended artistic portrait domain. Different from StyleGAN, DualStyleGAN provides a natural way of style transfer by characterizing the content and style of a portrait with an intrinsic style path and a new extrinsic style path, respectively. The del-icately designed extrinsic style path enables our model to modulate both the color and complex structural styles hierarchically to precisely pastiche the style example. Furthermore, a novel progressive fine-tuning scheme is introduced to smoothly transform the generative space of the model to the target domain, even with the above modifications on the network architecture. Experiments demonstrate the superiority of DualStyleGAN over state-of-the-art methods in high-quality portrait style transfer and flexible stylecontrol. Code is available at https://github.com/williamyang1991/DualStyleGAN.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recent studies on StyleGAN show high performance on artistic portrait generation by transfer learning with limited data. In this paper, we explore more challenging exemplar-based high-resolution portrait style transfer by introducing a novel DualStyleGAN with flexible control of dual styles of the original face domain and the extended artistic portrait domain. Different from StyleGAN, DualStyleGAN provides a natural way of style transfer by characterizing the content and style of a portrait with an intrinsic style path and a new extrinsic style path, respectively. The del-icately designed extrinsic style path enables our model to modulate both the color and complex structural styles hierarchically to precisely pastiche the style example. Furthermore, a novel progressive fine-tuning scheme is introduced to smoothly transform the generative space of the model to the target domain, even with the above modifications on the network architecture. Experiments demonstrate the superiority of DualStyleGAN over state-of-the-art methods in high-quality portrait style transfer and flexible stylecontrol. Code is available at https://github.com/williamyang1991/DualStyleGAN.",
"fno": "694600h683",
"keywords": [
"Art",
"Face Recognition",
"Learning Artificial Intelligence",
"Pastiche Master",
"Style GAN",
"Artistic Portrait Generation",
"Transfer Learning",
"Challenging Exemplar Based High Resolution Portrait Style Transfer",
"Dual Styles",
"Original Face Domain",
"Extended Artistic Portrait Domain",
"Dual Style GAN",
"Content Style",
"Intrinsic Style Path",
"Extrinsic Style Path",
"Complex Structural Styles",
"Style Example",
"High Quality Portrait Style Transfer",
"Computer Vision",
"Codes",
"Image Color Analysis",
"Face Recognition",
"Computational Modeling",
"Transfer Learning",
"Transforms"
],
"authors": [
{
"affiliation": "Nanyang Technological University,S-Lab",
"fullName": "Shuai Yang",
"givenName": "Shuai",
"surname": "Yang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Nanyang Technological University,S-Lab",
"fullName": "Liming Jiang",
"givenName": "Liming",
"surname": "Jiang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Nanyang Technological University,S-Lab",
"fullName": "Ziwei Liu",
"givenName": "Ziwei",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Nanyang Technological University,S-Lab",
"fullName": "Chen Change Loy",
"givenName": "Chen Change",
"surname": "Loy",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-06-01T00:00:00",
"pubType": "proceedings",
"pages": "7683-7692",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6946-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [
{
"id": "1H0NNLzE2BO",
"name": "pcvpr202269460-09880035s1-mm_694600h683.zip",
"size": "13.5 MB",
"location": "https://www.computer.org/csdl/api/v1/extra/pcvpr202269460-09880035s1-mm_694600h683.zip",
"__typename": "WebExtraType"
}
],
"adjacentArticles": {
"previous": {
"fno": "694600h673",
"articleId": "1H1mrnr7FoQ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "694600h693",
"articleId": "1H1hv4owUAE",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icpr/2012/2216/0/06460290",
"title": "Example-based contrast enhancement for portrait photograph",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2012/06460290/12OmNqC2v3G",
"parentPublication": {
"id": "proceedings/icpr/2012/2216/0",
"title": "2012 21st International Conference on Pattern Recognition (ICPR 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2019/02/08640099",
"title": "Automatic Color Sketch Generation Using Deep Style Transfer",
"doi": null,
"abstractUrl": "/magazine/cg/2019/02/08640099/17D45VsBTXm",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000a040",
"title": "PairedCycleGAN: Asymmetric Style Transfer for Applying and Removing Makeup",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000a040/17D45WnnFWY",
"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/tg/5555/01/09754991",
"title": "OrthoAligner: Image-based Teeth Alignment Prediction via Latent Style Manipulation",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09754991/1CubHSuE8bm",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09784910",
"title": "DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09784910/1DPaE3QYx68",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2020/7168/0/716800i214",
"title": "Unpaired Portrait Drawing Generation via Asymmetric Cycle Mapping",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800i214/1m3ncKO9WqQ",
"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/2020/7168/0/716800g141",
"title": "StyleRig: Rigging StyleGAN for 3D Control Over Portrait Images",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800g141/1m3ng5xOC08",
"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/icmew/2021/4989/0/09455949",
"title": "Multi-Style Artistic Portrait Drawing Generation",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2021/09455949/1uCgn6EsRLG",
"parentPublication": {
"id": "proceedings/icmew/2021/4989/0",
"title": "2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/02/09547845",
"title": "Exemplar-Based 3D Portrait Stylization",
"doi": null,
"abstractUrl": "/journal/tg/2023/02/09547845/1x9TLh9tiow",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900g545",
"title": "Spatially-invariant Style-codes Controlled Makeup Transfer",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900g545/1yeKnf5jsgo",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1H1gVMlkl32",
"title": "2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1H1mBYZtG6Y",
"doi": "10.1109/CVPR52688.2022.00752",
"title": "FENeRF: Face Editing in Neural Radiance Fields",
"normalizedTitle": "FENeRF: Face Editing in Neural Radiance Fields",
"abstract": "Previous portrait image generation methods roughly fall into two categories: 2D GANs and 3D-aware GANs. 2D GANs can generate high fidelity portraits but with low view consistency. 3D-aware GAN methods can maintain view consistency but their generated images are not locally editable. To overcome these limitations, we propose FENeRF, a 3D-aware generator that can produce view-consistent and locally-editable portrait images. Our method uses two decoupled latent codes to generate corresponding facial semantics and texture in a spatial-aligned 3D volume with shared geometry. Benefiting from such underlying 3D representation, FENeRF can Jointly render the boundary-aligned image and semantic mask and use the semantic mask to edit the 3D volume via GAN inversion. We further show such 3D representation can be learned from widely available monocular image and semantic mask pairs. Moreover, we reveal that Joint learning semantics and texture helps to generate finer geometry. Our experiments demonstrate that FENeRF outperforms state-of-the-art methods in various face editing tasks. Code is available at https://github.com/MrTornado24/FENeRF.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Previous portrait image generation methods roughly fall into two categories: 2D GANs and 3D-aware GANs. 2D GANs can generate high fidelity portraits but with low view consistency. 3D-aware GAN methods can maintain view consistency but their generated images are not locally editable. To overcome these limitations, we propose FENeRF, a 3D-aware generator that can produce view-consistent and locally-editable portrait images. Our method uses two decoupled latent codes to generate corresponding facial semantics and texture in a spatial-aligned 3D volume with shared geometry. Benefiting from such underlying 3D representation, FENeRF can Jointly render the boundary-aligned image and semantic mask and use the semantic mask to edit the 3D volume via GAN inversion. We further show such 3D representation can be learned from widely available monocular image and semantic mask pairs. Moreover, we reveal that Joint learning semantics and texture helps to generate finer geometry. Our experiments demonstrate that FENeRF outperforms state-of-the-art methods in various face editing tasks. Code is available at https://github.com/MrTornado24/FENeRF.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Previous portrait image generation methods roughly fall into two categories: 2D GANs and 3D-aware GANs. 2D GANs can generate high fidelity portraits but with low view consistency. 3D-aware GAN methods can maintain view consistency but their generated images are not locally editable. To overcome these limitations, we propose FENeRF, a 3D-aware generator that can produce view-consistent and locally-editable portrait images. Our method uses two decoupled latent codes to generate corresponding facial semantics and texture in a spatial-aligned 3D volume with shared geometry. Benefiting from such underlying 3D representation, FENeRF can Jointly render the boundary-aligned image and semantic mask and use the semantic mask to edit the 3D volume via GAN inversion. We further show such 3D representation can be learned from widely available monocular image and semantic mask pairs. Moreover, we reveal that Joint learning semantics and texture helps to generate finer geometry. Our experiments demonstrate that FENeRF outperforms state-of-the-art methods in various face editing tasks. Code is available at https://github.com/MrTornado24/FENeRF.",
"fno": "694600h662",
"keywords": [
"Computer Graphics",
"Face Recognition",
"Feature Extraction",
"Geometry",
"Image Reconstruction",
"Image Representation",
"Image Segmentation",
"Image Texture",
"Learning Artificial Intelligence",
"Rendering Computer Graphics",
"GAN Inversion",
"Widely Available Monocular Image",
"Semantic Mask Pairs",
"Joint Learning Semantics",
"Face Editing Tasks",
"Neural Radiance Fields",
"Previous Portrait Image Generation Methods",
"2 D GA Ns",
"3 D Aware GA Ns",
"High Fidelity Portraits",
"Low View Consistency",
"3 D Aware GAN Methods",
"3 D Aware Generator",
"Locally Editable Portrait Images",
"Decoupled Latent Codes",
"Corresponding Facial Semantics",
"Spatial Aligned 3 D Volume",
"Underlying 3 D Representation",
"Boundary Aligned Image",
"Geometry",
"Three Dimensional Displays",
"Codes",
"Image Resolution",
"Image Synthesis",
"Face Recognition",
"Semantics"
],
"authors": [
{
"affiliation": "University of Illinois at Urbana-Champaign",
"fullName": "Jingxiang Sun",
"givenName": "Jingxiang",
"surname": "Sun",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tencent AI Lab",
"fullName": "Xuan Wang",
"givenName": "Xuan",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tencent AI Lab",
"fullName": "Yong Zhang",
"givenName": "Yong",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tencent AI Lab",
"fullName": "Xiaoyu Li",
"givenName": "Xiaoyu",
"surname": "Li",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tencent AI Lab",
"fullName": "Qi Zhang",
"givenName": "Qi",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tsinghua University",
"fullName": "Yebin Liu",
"givenName": "Yebin",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tencent AI Lab",
"fullName": "Jue Wang",
"givenName": "Jue",
"surname": "Wang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-06-01T00:00:00",
"pubType": "proceedings",
"pages": "7662-7672",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-6946-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "694600h652",
"articleId": "1H0O4UKMVvW",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "694600h673",
"articleId": "1H1mrnr7FoQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2022/0915/0/091500d967",
"title": "Neural Radiance Fields Approach to Deep Multi-View Photometric Stereo",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500d967/1B12MeL2yhW",
"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/iccv/2021/2812/0/281200f826",
"title": "Self-Calibrating Neural Radiance Fields",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200f826/1BmEiCkWfU4",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200f721",
"title": "BARF: Bundle-Adjusting Neural Radiance Fields",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200f721/1BmJaz9pbig",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200f753",
"title": "Editing Conditional Radiance Fields",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200f753/1BmLkbx0k6c",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600s8332",
"title": "NeRF-Editing: Geometry Editing of Neural Radiance Fields",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600s8332/1H0Nn4Xgsne",
"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/fg/2023/4544/0/10042553",
"title": "FLAME-in-NeRF: Neural control of Radiance Fields for Free View Face Animation",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2023/10042553/1KOuZgIV1QI",
"parentPublication": {
"id": "proceedings/fg/2023/4544/0",
"title": "2023 IEEE 17th International Conference on Automatic Face and Gesture Recognition (FG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dv/2022/5670/0/567000a646",
"title": "Controllable Radiance Fields for Dynamic Face Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2022/567000a646/1KYspKZnHMs",
"parentPublication": {
"id": "proceedings/3dv/2022/5670/0",
"title": "2022 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2023/9346/0/934600a724",
"title": "CG-NeRF: Conditional Generative Neural Radiance Fields for 3D-aware Image Synthesis",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600a724/1LiO7xF1g6A",
"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/cvpr/2019/3293/0/329300d431",
"title": "Mask-Guided Portrait Editing With Conditional GANs",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2019/329300d431/1gys1RwVeRq",
"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/cvpr/2021/4509/0/450900e576",
"title": "pixelNeRF: Neural Radiance Fields from One or Few Images",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900e576/1yeL3toqPN6",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1KxUhhFgzlK",
"title": "2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)",
"acronym": "wacv",
"groupId": "1000040",
"volume": "0",
"displayVolume": "0",
"year": "2023",
"__typename": "ProceedingType"
},
"article": {
"id": "1L8qBcO17xe",
"doi": "10.1109/WACV56688.2023.00430",
"title": "SketchInverter: Multi-Class Sketch-Based Image Generation via GAN Inversion",
"normalizedTitle": "SketchInverter: Multi-Class Sketch-Based Image Generation via GAN Inversion",
"abstract": "This paper proposes the first GAN inversion-based method for multi-class sketch-based image generation (MCSBIG). MC-SBIG is a challenging task that requires strong prior knowledge due to the significant domain gap between sketches and natural images. Existing learning-based approaches rely on a large-scale paired dataset to learn the mapping between these two image modalities. However, since the public paired sketch-photo data are scarce, it is struggling for learning-based methods to achieve satisfactory results. In this work, we introduce a new approach based on GAN inversion, which can utilize a powerful pretrained generator to facilitate image generation from a given sketch. Our GAN inversion-based method has two advantages: 1. it can freely take advantage of the prior knowledge of a pretrained image generator; 2. it allows the proposed model to focus on learning the mapping from a sketch to a low-dimension latent code, which is a much easier task than directly mapping to a high-dimension natural image. We also present a novel shape loss to improve generation quality further. Extensive experiments are conducted to show that our method can produce sketch-faithful and photo-realistic images and significantly outperform the baseline methods.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper proposes the first GAN inversion-based method for multi-class sketch-based image generation (MCSBIG). MC-SBIG is a challenging task that requires strong prior knowledge due to the significant domain gap between sketches and natural images. Existing learning-based approaches rely on a large-scale paired dataset to learn the mapping between these two image modalities. However, since the public paired sketch-photo data are scarce, it is struggling for learning-based methods to achieve satisfactory results. In this work, we introduce a new approach based on GAN inversion, which can utilize a powerful pretrained generator to facilitate image generation from a given sketch. Our GAN inversion-based method has two advantages: 1. it can freely take advantage of the prior knowledge of a pretrained image generator; 2. it allows the proposed model to focus on learning the mapping from a sketch to a low-dimension latent code, which is a much easier task than directly mapping to a high-dimension natural image. We also present a novel shape loss to improve generation quality further. Extensive experiments are conducted to show that our method can produce sketch-faithful and photo-realistic images and significantly outperform the baseline methods.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper proposes the first GAN inversion-based method for multi-class sketch-based image generation (MCSBIG). MC-SBIG is a challenging task that requires strong prior knowledge due to the significant domain gap between sketches and natural images. Existing learning-based approaches rely on a large-scale paired dataset to learn the mapping between these two image modalities. However, since the public paired sketch-photo data are scarce, it is struggling for learning-based methods to achieve satisfactory results. In this work, we introduce a new approach based on GAN inversion, which can utilize a powerful pretrained generator to facilitate image generation from a given sketch. Our GAN inversion-based method has two advantages: 1. it can freely take advantage of the prior knowledge of a pretrained image generator; 2. it allows the proposed model to focus on learning the mapping from a sketch to a low-dimension latent code, which is a much easier task than directly mapping to a high-dimension natural image. We also present a novel shape loss to improve generation quality further. Extensive experiments are conducted to show that our method can produce sketch-faithful and photo-realistic images and significantly outperform the baseline methods.",
"fno": "934600e308",
"keywords": [
"Deep Learning Artificial Intelligence",
"Learning Artificial Intelligence",
"Realistic Images",
"Unsupervised Learning",
"Existing Learning Based Approaches",
"GAN Inversion Based Method",
"Given Sketch",
"High Dimension Natural Image",
"Image Modalities",
"Learning Based Methods",
"Multiclass Sketch Based Image Generation",
"Natural Images",
"Photo Realistic Images",
"Powerful Pretrained Generator",
"Pretrained Image Generator",
"Public Paired Sketch Photo Data",
"Sketch Faithful",
"Training",
"Learning Systems",
"Computer Vision",
"Codes",
"Image Synthesis",
"Shape",
"Generators",
"Algorithms Computational Photography",
"Image And Video Synthesis",
"Arts Games Social Media"
],
"authors": [
{
"affiliation": "Beihang University",
"fullName": "Zirui An",
"givenName": "Zirui",
"surname": "An",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Beihang University",
"fullName": "Jingbo Yu",
"givenName": "Jingbo",
"surname": "Yu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Johns Hopkins University",
"fullName": "Runtao Liu",
"givenName": "Runtao",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Beihang University",
"fullName": "Chuang Wang",
"givenName": "Chuang",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Beihang University",
"fullName": "Qian Yu",
"givenName": "Qian",
"surname": "Yu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wacv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2023-01-01T00:00:00",
"pubType": "proceedings",
"pages": "4308-4318",
"year": "2023",
"issn": null,
"isbn": "978-1-6654-9346-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "9.346E303",
"articleId": "1KxVEapauBi",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "934600e319",
"articleId": "1KxUSVbk6He",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2022/0915/0/091500a955",
"title": "AE-StyleGAN: Improved Training of Style-Based Auto-Encoders",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500a955/1B12OZCI3JK",
"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/iccv/2021/2812/0/281200o4030",
"title": "Sketch Your Own GAN",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200o4030/1BmIHZg8uf6",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200n3921",
"title": "GAN Inversion for Out-of-Range Images with Geometric Transformations",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200n3921/1BmLu1Z58CA",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2023/03/09792208",
"title": "GAN Inversion: A Survey",
"doi": null,
"abstractUrl": "/journal/tp/2023/03/09792208/1E5LCU0gJAk",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600l1369",
"title": "High-Fidelity GAN Inversion for Image Attribute Editing",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600l1369/1H0KIV4YYEw",
"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/cvpr/2022/6946/0/694600l1411",
"title": "Dual-path Image Inpainting with Auxiliary GAN Inversion",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600l1411/1H0LiHfmVOw",
"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/cvpr/2022/6946/0/694600l1327",
"title": "Style Transformer for Image Inversion and Editing",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600l1327/1H0ND0u1zXi",
"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/2023/9346/0/934600c966",
"title": "3D GAN Inversion with Pose Optimization",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600c966/1L8quvqCEhO",
"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/iccvw/2021/0191/0/019100d508",
"title": "Multiple GAN Inversion for Exemplar-based Image-to-Image Translation",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100d508/1yNiEgxUAcU",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900d680",
"title": "IMAGINE: Image Synthesis by Image-Guided Model Inversion",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900d680/1yeMaZFSZOM",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1yeHGyRsuys",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"acronym": "cvpr",
"groupId": "1000147",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1yeKSL9mS2I",
"doi": "10.1109/CVPR46437.2021.00229",
"title": "TediGAN: Text-Guided Diverse Face Image Generation and Manipulation",
"normalizedTitle": "TediGAN: Text-Guided Diverse Face Image Generation and Manipulation",
"abstract": "In this work, we propose TediGAN, a novel framework for multi-modal image generation and manipulation with textual descriptions. The proposed method consists of three components: StyleGAN inversion module, visual-linguistic similarity learning, and instance-level optimization. The inversion module maps real images to the latent space of a well-trained StyleGAN. The visual-linguistic similarity learns the text-image matching by mapping the image and text into a common embedding space. The instancelevel optimization is for identity preservation in manipulation. Our model can produce diverse and high-quality images with an unprecedented resolution at 1024<sup>2</sup>. Using a control mechanism based on style-mixing, our TediGAN inherently supports image synthesis with multi-modal inputs, such as sketches or semantic labels, with or without instance guidance. To facilitate text-guided multi-modal synthesis, we propose the Multi-Modal CelebA-HQ, a large-scale dataset consisting of real face images and corresponding semantic segmentation map, sketch, and textual descriptions. Extensive experiments on the introduced dataset demonstrate the superior performance of our proposed method. Code and data are available at https://github.com/weihaox/TediGAN.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this work, we propose TediGAN, a novel framework for multi-modal image generation and manipulation with textual descriptions. The proposed method consists of three components: StyleGAN inversion module, visual-linguistic similarity learning, and instance-level optimization. The inversion module maps real images to the latent space of a well-trained StyleGAN. The visual-linguistic similarity learns the text-image matching by mapping the image and text into a common embedding space. The instancelevel optimization is for identity preservation in manipulation. Our model can produce diverse and high-quality images with an unprecedented resolution at 1024<sup>2</sup>. Using a control mechanism based on style-mixing, our TediGAN inherently supports image synthesis with multi-modal inputs, such as sketches or semantic labels, with or without instance guidance. To facilitate text-guided multi-modal synthesis, we propose the Multi-Modal CelebA-HQ, a large-scale dataset consisting of real face images and corresponding semantic segmentation map, sketch, and textual descriptions. Extensive experiments on the introduced dataset demonstrate the superior performance of our proposed method. Code and data are available at https://github.com/weihaox/TediGAN.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this work, we propose TediGAN, a novel framework for multi-modal image generation and manipulation with textual descriptions. The proposed method consists of three components: StyleGAN inversion module, visual-linguistic similarity learning, and instance-level optimization. The inversion module maps real images to the latent space of a well-trained StyleGAN. The visual-linguistic similarity learns the text-image matching by mapping the image and text into a common embedding space. The instancelevel optimization is for identity preservation in manipulation. Our model can produce diverse and high-quality images with an unprecedented resolution at 10242. Using a control mechanism based on style-mixing, our TediGAN inherently supports image synthesis with multi-modal inputs, such as sketches or semantic labels, with or without instance guidance. To facilitate text-guided multi-modal synthesis, we propose the Multi-Modal CelebA-HQ, a large-scale dataset consisting of real face images and corresponding semantic segmentation map, sketch, and textual descriptions. Extensive experiments on the introduced dataset demonstrate the superior performance of our proposed method. Code and data are available at https://github.com/weihaox/TediGAN.",
"fno": "450900c256",
"keywords": [
"Data Visualisation",
"Face Recognition",
"Feature Extraction",
"Image Classification",
"Image Matching",
"Image Representation",
"Image Segmentation",
"Learning Artificial Intelligence",
"Optimisation",
"Text Analysis",
"Embedding Space",
"Multi Modal Celeb A HQ Dataset",
"Tedi GAN",
"Semantic Segmentation Map",
"Face Images",
"Text Guided Multimodal Synthesis",
"Multimodal Inputs",
"Image Synthesis",
"High Quality Images",
"Text Image Matching",
"Instance Level Optimization",
"Visual Linguistic Similarity Learning",
"Style GAN Inversion Module",
"Textual Descriptions",
"Multimodal Image Generation",
"Text Guided Diverse Face Image Generation",
"Image Segmentation",
"Computer Vision",
"Image Resolution",
"Image Synthesis",
"Face Recognition",
"Semantics",
"Aerospace Electronics"
],
"authors": [
{
"affiliation": "Tsinghua University,Tsinghua Shenzhen International Graduate School,China",
"fullName": "Weihao Xia",
"givenName": "Weihao",
"surname": "Xia",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tsinghua University,Tsinghua Shenzhen International Graduate School,China",
"fullName": "Yujiu Yang",
"givenName": "Yujiu",
"surname": "Yang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University College London,Department of Statistical Science,UK",
"fullName": "Jing-Hao Xue",
"givenName": "Jing-Hao",
"surname": "Xue",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Chinese University of Hongkong,School of Data Science,Shenzhen,China",
"fullName": "Baoyuan Wu",
"givenName": "Baoyuan",
"surname": "Wu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cvpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-06-01T00:00:00",
"pubType": "proceedings",
"pages": "2256-2265",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-4509-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "450900c246",
"articleId": "1yeLYxNry3C",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "450900c266",
"articleId": "1yeM3LNZkru",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/wacv/2022/0915/0/091500d441",
"title": "StyleMC: Multi-Channel Based Fast Text-Guided Image Generation and Manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2022/091500d441/1B12HcraGYM",
"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/iccv/2021/2812/0/281200c065",
"title": "StyleCLIP: Text-Driven Manipulation of StyleGAN Imagery",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200c065/1BmKkMzKY1i",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200m2096",
"title": "Face Image Retrieval with Attribute Manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200m2096/1BmLms5zisU",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09784910",
"title": "DrawingInStyles: Portrait Image Generation and Editing with Spatially Conditioned StyleGAN",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09784910/1DPaE3QYx68",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600d367",
"title": "Sound-Guided Semantic Image Manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600d367/1H0O9To9H7a",
"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/cvpr/2022/6946/0/694600s8490",
"title": "HyperStyle: StyleGAN Inversion with HyperNetworks for Real Image Editing",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600s8490/1H1htgcIy9G",
"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/cvpr/2022/6946/0/694600c416",
"title": "DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600c416/1H1metI0hpe",
"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/cvpr/2022/6946/0/694600s8666",
"title": "AnyFace: Free-style Text-to-Face Synthesis and Manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600s8666/1H1nmZYxzuo",
"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/cvpr/2020/7168/0/716800h877",
"title": "ManiGAN: Text-Guided Image Manipulation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2020/716800h877/1m3nOFPFzb2",
"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/tp/2022/10/09444850",
"title": "Text-Guided Human Image Manipulation via Image-Text Shared Space",
"doi": null,
"abstractUrl": "/journal/tp/2022/10/09444850/1u51vKl5cSk",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxvNZWY",
"title": "2016 19th International Conference on Network-Based Information Systems (NBiS)",
"acronym": "nbis",
"groupId": "1002969",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNCd2rVL",
"doi": "10.1109/NBiS.2016.29",
"title": "Three Dimensional Reconstruction from Single Uniform Texture Image with Unknown Lighting Conditions",
"normalizedTitle": "Three Dimensional Reconstruction from Single Uniform Texture Image with Unknown Lighting Conditions",
"abstract": "An effective method has been proposed in this paper to reconstruct the 3D shape from single texture image with similar appearances and reflectance properties. Two main steps are required: the first is the estimation of lighting parameters, which has been estimated by detecting the largest direction of the brightness change, the second is the 3D reconstruction from single input image, which has been reconstructed by combining the patch matching and optimization methods. Experiment results have verified the effectiveness of the proposed method according to realistic perception.",
"abstracts": [
{
"abstractType": "Regular",
"content": "An effective method has been proposed in this paper to reconstruct the 3D shape from single texture image with similar appearances and reflectance properties. Two main steps are required: the first is the estimation of lighting parameters, which has been estimated by detecting the largest direction of the brightness change, the second is the 3D reconstruction from single input image, which has been reconstructed by combining the patch matching and optimization methods. Experiment results have verified the effectiveness of the proposed method according to realistic perception.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "An effective method has been proposed in this paper to reconstruct the 3D shape from single texture image with similar appearances and reflectance properties. Two main steps are required: the first is the estimation of lighting parameters, which has been estimated by detecting the largest direction of the brightness change, the second is the 3D reconstruction from single input image, which has been reconstructed by combining the patch matching and optimization methods. Experiment results have verified the effectiveness of the proposed method according to realistic perception.",
"fno": "0979a492",
"keywords": [
"Image Reconstruction",
"Three Dimensional Displays",
"Lighting",
"Shape",
"Surface Reconstruction",
"Azimuth",
"Databases",
"Photometric Stereo",
"Texture Image",
"3 D Reconstruction"
],
"authors": [
{
"affiliation": null,
"fullName": "Yujuan Sun",
"givenName": "Yujuan",
"surname": "Sun",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Qiuming Ma",
"givenName": "Qiuming",
"surname": "Ma",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "nbis",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-09-01T00:00:00",
"pubType": "proceedings",
"pages": "492-495",
"year": "2016",
"issn": "2157-0426",
"isbn": "978-1-5090-0979-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "0979a488",
"articleId": "12OmNAWH9vE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "0979a496",
"articleId": "12OmNyO8tKF",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icme/2007/1016/0/04284896",
"title": "Hole Filling on Three-Dimensional Surface Texture",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2007/04284896/12OmNy4IF6j",
"parentPublication": {
"id": "proceedings/icme/2007/1016/0",
"title": "2007 International Conference on Multimedia & Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2017/0457/0/0457a369",
"title": "Polarimetric Multi-view Stereo",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2017/0457a369/12OmNyfdOLS",
"parentPublication": {
"id": "proceedings/cvpr/2017/0457/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvprw/2014/4308/0/4308a433",
"title": "Separating Texture and Illumination for Single-Shot Structured Light Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/cvprw/2014/4308a433/12OmNyq0zJQ",
"parentPublication": {
"id": "proceedings/cvprw/2014/4308/0",
"title": "2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2018/02/07858760",
"title": "Shading-Based Surface Detail Recovery Under General Unknown Illumination",
"doi": null,
"abstractUrl": "/journal/tp/2018/02/07858760/13rRUwdIOW8",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2019/12/08456615",
"title": "Height-from-Polarisation with Unknown Lighting or Albedo",
"doi": null,
"abstractUrl": "/journal/tp/2019/12/08456615/13rRUwh80CL",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2016/02/07121014",
"title": "Texture Illumination Separation for Single-Shot Structured Light Reconstruction",
"doi": null,
"abstractUrl": "/journal/tp/2016/02/07121014/13rRUygBw8h",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a632",
"title": "Material Reflectance Property Estimation of Complex Objects Using an Attention Network",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a632/1CJcD7RtQVq",
"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": "proceedings/3dv/2020/8128/0/812800b147",
"title": "Precomputed Radiance Transfer for Reflectance and Lighting Estimation",
"doi": null,
"abstractUrl": "/proceedings-article/3dv/2020/812800b147/1qyxlpSwLhC",
"parentPublication": {
"id": "proceedings/3dv/2020/8128/0",
"title": "2020 International Conference on 3D Vision (3DV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900k0586",
"title": "Lighting, Reflectance and Geometry Estimation from 360° Panoramic Stereo",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900k0586/1yeIplXJ9wQ",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900q6221",
"title": "Multi-view 3D Reconstruction of a Texture-less Smooth Surface of Unknown Generic Reflectance",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900q6221/1yeJrjY1kl2",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNx5GU1E",
"title": "Intelligent Information and Database Systems, Asian Conference on",
"acronym": "aciids",
"groupId": "1002816",
"volume": "0",
"displayVolume": "0",
"year": "2009",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBkxsv6",
"doi": "10.1109/ACIIDS.2009.65",
"title": "A Similar Music Retrieval Scheme Based on Musical Mood Variation",
"normalizedTitle": "A Similar Music Retrieval Scheme Based on Musical Mood Variation",
"abstract": "Music evokes various human emotions or creates music moods through low level musical features. In fact, typical music consists of one or more moods and this can be used as an important factor for determining the similarity between music. In this paper, we propose a new music retrieval scheme based on the mood change pattern. For this, we first divide music clips into segments based on low level musical features. Then, we apply K-means clustering algorithm for grouping them into clusters with similar features. By assigning a unique mood symbol for each group, each music clip can be represented into a sequence of mood symbols. Then, we estimate the similarity of music based on the similarity of their musical mood sequence using the Longest Common Subsequence (LCS) algorithm. To evaluate the performance of our scheme, we carried out various experiments and measured the user evaluation. We report some of the results.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Music evokes various human emotions or creates music moods through low level musical features. In fact, typical music consists of one or more moods and this can be used as an important factor for determining the similarity between music. In this paper, we propose a new music retrieval scheme based on the mood change pattern. For this, we first divide music clips into segments based on low level musical features. Then, we apply K-means clustering algorithm for grouping them into clusters with similar features. By assigning a unique mood symbol for each group, each music clip can be represented into a sequence of mood symbols. Then, we estimate the similarity of music based on the similarity of their musical mood sequence using the Longest Common Subsequence (LCS) algorithm. To evaluate the performance of our scheme, we carried out various experiments and measured the user evaluation. We report some of the results.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Music evokes various human emotions or creates music moods through low level musical features. In fact, typical music consists of one or more moods and this can be used as an important factor for determining the similarity between music. In this paper, we propose a new music retrieval scheme based on the mood change pattern. For this, we first divide music clips into segments based on low level musical features. Then, we apply K-means clustering algorithm for grouping them into clusters with similar features. By assigning a unique mood symbol for each group, each music clip can be represented into a sequence of mood symbols. Then, we estimate the similarity of music based on the similarity of their musical mood sequence using the Longest Common Subsequence (LCS) algorithm. To evaluate the performance of our scheme, we carried out various experiments and measured the user evaluation. We report some of the results.",
"fno": "3580a167",
"keywords": [
"Similar Music Retrieval",
"Music Mood",
"Longest Common Subsequence",
"Feature Extraction",
"K Means Clustering Algorithm"
],
"authors": [
{
"affiliation": null,
"fullName": "Sanghoon Jun",
"givenName": "Sanghoon",
"surname": "Jun",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Byeong-jun Han",
"givenName": "Byeong-jun",
"surname": "Han",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Eenjun Hwang",
"givenName": "Eenjun",
"surname": "Hwang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "aciids",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2009-04-01T00:00:00",
"pubType": "proceedings",
"pages": "167-172",
"year": "2009",
"issn": null,
"isbn": "978-0-7695-3580-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "3580a161",
"articleId": "12OmNqAU6DE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "3580a173",
"articleId": "12OmNzvhvwg",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ams/2012/4730/0/4730a007",
"title": "Automatic Mood Classification Model for Indian Popular Music",
"doi": null,
"abstractUrl": "/proceedings-article/ams/2012/4730a007/12OmNqAU6DC",
"parentPublication": {
"id": "proceedings/ams/2012/4730/0",
"title": "Asia International Conference on Modelling & Simulation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/kse/2009/3846/0/3846a144",
"title": "Machine Learning Approaches for Mood Classification of Songs toward Music Search Engine",
"doi": null,
"abstractUrl": "/proceedings-article/kse/2009/3846a144/12OmNqIQS5H",
"parentPublication": {
"id": "proceedings/kse/2009/3846/0",
"title": "Knowledge and Systems Engineering, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cisp/2008/3119/5/3119e148",
"title": "Discriminating Mood Taxonomy of Chinese Traditional Music and Western Classical Music with Content Feature Sets",
"doi": null,
"abstractUrl": "/proceedings-article/cisp/2008/3119e148/12OmNvSbBkI",
"parentPublication": {
"id": "proceedings/cisp/2008/3119/5",
"title": "International Congress on Image and Signal Processing (CISP 2008)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2008/3495/0/3495a688",
"title": "Multimodal Music Mood Classification Using Audio and Lyrics",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2008/3495a688/12OmNvkGWa0",
"parentPublication": {
"id": "proceedings/icmla/2008/3495/0",
"title": "2008 Seventh International Conference on Machine Learning and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2004/8603/3/01394664",
"title": "Graphical expression of the mood of music",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2004/01394664/12OmNwc3wBv",
"parentPublication": {
"id": "proceedings/icme/2004/8603/3",
"title": "2004 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbmi/2009/3662/0/3662a156",
"title": "Music Mood Annotator Design and Integration",
"doi": null,
"abstractUrl": "/proceedings-article/cbmi/2009/3662a156/12OmNzICEL3",
"parentPublication": {
"id": "proceedings/cbmi/2009/3662/0",
"title": "Content-Based Multimedia Indexing, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmew/2013/1604/0/06618436",
"title": "Semantic models of musical mood: Comparison between crowd-sourced and curated editorial tags",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2013/06618436/12OmNzlD9si",
"parentPublication": {
"id": "proceedings/icmew/2013/1604/0",
"title": "2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icds/2009/3526/0/3526a304",
"title": "Music Ontology for Mood and Situation Reasoning to Support Music Retrieval and Recommendation",
"doi": null,
"abstractUrl": "/proceedings-article/icds/2009/3526a304/12OmNzmtWzm",
"parentPublication": {
"id": "proceedings/icds/2009/3526/0",
"title": "International Conference on the Digital Society",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/2017/02/07395312",
"title": "Cross-Dataset and Cross-Cultural Music Mood Prediction: A Case on Western and Chinese Pop Songs",
"doi": null,
"abstractUrl": "/journal/ta/2017/02/07395312/13rRUxASua0",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/transai/2020/8699/0/869900a009",
"title": "Play it again IMuCo! Music Composition to Match your Mood",
"doi": null,
"abstractUrl": "/proceedings-article/transai/2020/869900a009/1oJ0ts7x4jK",
"parentPublication": {
"id": "proceedings/transai/2020/8699/0",
"title": "2020 Second International Conference on Transdisciplinary AI (TransAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyNQSGU",
"title": "2014 IEEE International Conference on Granular Computing (GrC)",
"acronym": "grc",
"groupId": "1001626",
"volume": "0",
"displayVolume": "0",
"year": "2014",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNBrDqEL",
"doi": "10.1109/GRC.2014.6982846",
"title": "Semantic content-based music retrieval using audio and fuzzy-music-sense features",
"normalizedTitle": "Semantic content-based music retrieval using audio and fuzzy-music-sense features",
"abstract": "Recently, advanced multimedia technologies enable a rapid growth of music data. It is accordingly a challenging issue to effectively retrieve the desired music pieces from a music collection. Traditional solutions for music retrieval can be divided into two types, namely text-based music retrieval and content-based music retrieval. However, it is difficult to satisfy both textual-percept and audio-content requirements from users. To tackle such problems, in this paper, we propose a new approach that retrieves music using fuzzy music-sense features and audio features. On one hand, the fuzzy music-sense features are adopted as auxiliary ones to increase the precision of content based music retrieval. On the other hand, the fuzzy music-sense features can also provide users with semantic music retrieval without precise query definitions. The experimental results reveal that, our proposed method can catch the relevant music accurately and semantically through effectively bridging music content to music sense.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Recently, advanced multimedia technologies enable a rapid growth of music data. It is accordingly a challenging issue to effectively retrieve the desired music pieces from a music collection. Traditional solutions for music retrieval can be divided into two types, namely text-based music retrieval and content-based music retrieval. However, it is difficult to satisfy both textual-percept and audio-content requirements from users. To tackle such problems, in this paper, we propose a new approach that retrieves music using fuzzy music-sense features and audio features. On one hand, the fuzzy music-sense features are adopted as auxiliary ones to increase the precision of content based music retrieval. On the other hand, the fuzzy music-sense features can also provide users with semantic music retrieval without precise query definitions. The experimental results reveal that, our proposed method can catch the relevant music accurately and semantically through effectively bridging music content to music sense.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Recently, advanced multimedia technologies enable a rapid growth of music data. It is accordingly a challenging issue to effectively retrieve the desired music pieces from a music collection. Traditional solutions for music retrieval can be divided into two types, namely text-based music retrieval and content-based music retrieval. However, it is difficult to satisfy both textual-percept and audio-content requirements from users. To tackle such problems, in this paper, we propose a new approach that retrieves music using fuzzy music-sense features and audio features. On one hand, the fuzzy music-sense features are adopted as auxiliary ones to increase the precision of content based music retrieval. On the other hand, the fuzzy music-sense features can also provide users with semantic music retrieval without precise query definitions. The experimental results reveal that, our proposed method can catch the relevant music accurately and semantically through effectively bridging music content to music sense.",
"fno": "06982846",
"keywords": [
"Music",
"Feature Extraction",
"Instruments",
"Semantics",
"Vectors",
"Content Based Retrieval",
"Databases",
"Content Based",
"Music Retrieval",
"Music Sense",
"Fuzzy",
"Text Based"
],
"authors": [
{
"affiliation": "Department of Information Management, Kainan University, Taoyuan, Taiwan",
"fullName": "Ja-Hwung Su",
"givenName": "Ja-Hwung",
"surname": "Su",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Information Management, Kainan University, Taoyuan, Taiwan",
"fullName": "Chun-Yen Wang",
"givenName": "Chun-Yen",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Information Management, Kainan University, Taoyuan, Taiwan",
"fullName": "Ting-Wei Chiu",
"givenName": "Ting-Wei",
"surname": "Chiu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan",
"fullName": "Josh Jia-Ching Ying",
"givenName": "Josh Jia-Ching",
"surname": "Ying",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan",
"fullName": "Vincent S. Tseng",
"givenName": "Vincent S.",
"surname": "Tseng",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "grc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2014-10-01T00:00:00",
"pubType": "proceedings",
"pages": "259-264",
"year": "2014",
"issn": null,
"isbn": "978-1-4799-5464-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06982845",
"articleId": "12OmNrkjVcP",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06982847",
"articleId": "12OmNz6iOL7",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/mmm/2005/2164/0/21640030",
"title": "Music Key Detection for Musical Audio",
"doi": null,
"abstractUrl": "/proceedings-article/mmm/2005/21640030/12OmNAoUTrj",
"parentPublication": {
"id": "proceedings/mmm/2005/2164/0",
"title": "Multi-Media Modeling Conference, International",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2004/8603/3/01394566",
"title": "Music segmentation by rhythmic features and melodic shapes",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2004/01394566/12OmNqBbHTk",
"parentPublication": {
"id": "proceedings/icme/2004/8603/3",
"title": "2004 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmcs/1999/0253/1/02539457",
"title": "A Combinatorial Approach to Content-Based Music Selection",
"doi": null,
"abstractUrl": "/proceedings-article/icmcs/1999/02539457/12OmNs0TKMQ",
"parentPublication": {
"id": "proceedings/icmcs/1999/0253/1",
"title": "Multimedia Computing and Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icebe/2017/1412/0/1412a275",
"title": "A Survey of Audio MIR Systems, Symbolic MIR Systems and a Music Definition Language Demo-System",
"doi": null,
"abstractUrl": "/proceedings-article/icebe/2017/1412a275/12OmNvjyxKR",
"parentPublication": {
"id": "proceedings/icebe/2017/1412/0",
"title": "2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2004/8603/2/01394310",
"title": "Multimodal music retrieval for large databases",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2004/01394310/12OmNwoPtkB",
"parentPublication": {
"id": "proceedings/icme/2004/8603/2",
"title": "2004 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2008/3454/0/3454a613",
"title": "A Music Retrieval Method Based on Distribution of Feature Segments",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2008/3454a613/12OmNxWcHda",
"parentPublication": {
"id": "proceedings/ism/2008/3454/0",
"title": "2008 Tenth IEEE International Symposium on Multimedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2016/2722/0/07590352",
"title": "Immersive Orchestras: Audio Processing for Orchestral Music VR Content",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2016/07590352/12OmNxYtu8a",
"parentPublication": {
"id": "proceedings/vs-games/2016/2722/0",
"title": "2016 8th International Conference on Games and Virtual Worlds for Serious Applications (VS-Games)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ism/2008/3454/0/3454a574",
"title": "Music Genre Classification and Similarity Calculation Using Bass-Line Features",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2008/3454a574/12OmNyLiuGi",
"parentPublication": {
"id": "proceedings/ism/2008/3454/0",
"title": "2008 Tenth IEEE International Symposium on Multimedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2004/832/0/01336130",
"title": "Looking for new, not known music only: music retrieval by melody style",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2004/01336130/12OmNyLiurp",
"parentPublication": {
"id": "proceedings/jcdl/2004/832/0",
"title": "Proceedings of the Fourth ACM/IEEE Joint Conference on Digital Libraries",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/act/2009/3915/0/05376715",
"title": "Evaluation of Audio Based Searching for Indian Traditional Music",
"doi": null,
"abstractUrl": "/proceedings-article/act/2009/05376715/13bd1fph1xI",
"parentPublication": {
"id": "proceedings/act/2009/3915/0",
"title": "Advances in Computing, Control, and Telecommunication Technologies, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyr8Ytt",
"title": "2015 19th International Conference on Information Visualisation (iV)",
"acronym": "iv",
"groupId": "1000370",
"volume": "0",
"displayVolume": "0",
"year": "2015",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNvjyxYk",
"doi": "10.1109/iV.2015.21",
"title": "A Color-Based Visualization Approach to Understand Harmonic Structures of Musical Compositions",
"normalizedTitle": "A Color-Based Visualization Approach to Understand Harmonic Structures of Musical Compositions",
"abstract": "Music expertise is the ability to understand the structural elements of music compositions by reading musical scores or even by simply listening to music performance. Although the most common way to learn music is through the study of musical scores, this approach is demanding in terms of learning ability, given the required implicit knowledge of music theoretical notations and concepts. In this work we define a two-level color-based approach, that exploits graphical visualization techniques to represent data structures of classical music, and to perform harmonic analysis of musical compositions. Our main goal is to make easier and very quick the study of classical notations (recognized as a tedious and difficult task in the field), by providing individuals with a mechanism that clarifies complex relationships in music using visual clues. We performed a preliminary study to evaluate the effectiveness of our approach as well as participants' perceptions about its usefulness and pleasantness. The results of the study provided us with overall positive feedback about the effectiveness of our approach as well as further directions to explore.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Music expertise is the ability to understand the structural elements of music compositions by reading musical scores or even by simply listening to music performance. Although the most common way to learn music is through the study of musical scores, this approach is demanding in terms of learning ability, given the required implicit knowledge of music theoretical notations and concepts. In this work we define a two-level color-based approach, that exploits graphical visualization techniques to represent data structures of classical music, and to perform harmonic analysis of musical compositions. Our main goal is to make easier and very quick the study of classical notations (recognized as a tedious and difficult task in the field), by providing individuals with a mechanism that clarifies complex relationships in music using visual clues. We performed a preliminary study to evaluate the effectiveness of our approach as well as participants' perceptions about its usefulness and pleasantness. The results of the study provided us with overall positive feedback about the effectiveness of our approach as well as further directions to explore.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Music expertise is the ability to understand the structural elements of music compositions by reading musical scores or even by simply listening to music performance. Although the most common way to learn music is through the study of musical scores, this approach is demanding in terms of learning ability, given the required implicit knowledge of music theoretical notations and concepts. In this work we define a two-level color-based approach, that exploits graphical visualization techniques to represent data structures of classical music, and to perform harmonic analysis of musical compositions. Our main goal is to make easier and very quick the study of classical notations (recognized as a tedious and difficult task in the field), by providing individuals with a mechanism that clarifies complex relationships in music using visual clues. We performed a preliminary study to evaluate the effectiveness of our approach as well as participants' perceptions about its usefulness and pleasantness. The results of the study provided us with overall positive feedback about the effectiveness of our approach as well as further directions to explore.",
"fno": "7568a056",
"keywords": [
"Harmonic Analysis",
"Color",
"Music",
"Visualization",
"Image Color Analysis",
"Testing",
"Data Visualization",
"Evaluation",
"Visualization",
"Harmonic Music Composition"
],
"authors": [
{
"affiliation": null,
"fullName": "Delfina Malandrino",
"givenName": "Delfina",
"surname": "Malandrino",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Donato Pirozzi",
"givenName": "Donato",
"surname": "Pirozzi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Gianluca Zaccagnino",
"givenName": "Gianluca",
"surname": "Zaccagnino",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Rocco Zaccagnino",
"givenName": "Rocco",
"surname": "Zaccagnino",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2015-07-01T00:00:00",
"pubType": "proceedings",
"pages": "56-61",
"year": "2015",
"issn": "1550-6037",
"isbn": "978-1-4673-7568-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "7568a050",
"articleId": "12OmNqI04Kf",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "7568a062",
"articleId": "12OmNwIpNpt",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdar/1993/4960/0/00395590",
"title": "Musical score recognition: A hierarchical and recursive approach",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/1993/00395590/12OmNBTJIEK",
"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": "proceedings/icdar/2007/2822/2/04377027",
"title": "Guido: A Musical Score Recognition System",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2007/04377027/12OmNy49sPl",
"parentPublication": {
"id": "proceedings/icdar/2007/2822/2",
"title": "Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csa/2008/3428/0/3428a269",
"title": "Multitimbral Musical Instrument Classification",
"doi": null,
"abstractUrl": "/proceedings-article/csa/2008/3428a269/12OmNyFU6ZE",
"parentPublication": {
"id": "proceedings/csa/2008/3428/0",
"title": "2008 International Symposium on Computer Science and its Applications (CSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icassp/2002/7402/2/05744965",
"title": "Bayesian harmonic models for musical pitch estimation and analysis",
"doi": null,
"abstractUrl": "/proceedings-article/icassp/2002/05744965/12OmNzwZ6uR",
"parentPublication": {
"id": "proceedings/icassp/2002/7402/2",
"title": "Proceedings of International Conference on Acoustics, Speech and Signal Processing (CASSP'02)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2013/04/mmu2013040076",
"title": "New Musical Instrument Design Considerations",
"doi": null,
"abstractUrl": "/magazine/mu/2013/04/mmu2013040076/13rRUEgs2IN",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a484",
"title": "Evaluation Study of Visualisations for Harmonic Analysis of 4-Part Music",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a484/17D45WB0qdU",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a471",
"title": "MixMash: A Visualisation System for Musical Mashup Creation",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a471/17D45XvMcd9",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2018/7202/0/720200a498",
"title": "Visualization and Music Harmony: Design, Implementation, and Evaluation",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2018/720200a498/17D45XwUALT",
"parentPublication": {
"id": "proceedings/iv/2018/7202/0",
"title": "2018 22nd International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iv/2020/9134/0/913400a537",
"title": "SymPlot: A Web-Tool to Visualise Symbolic Musical Data",
"doi": null,
"abstractUrl": "/proceedings-article/iv/2020/913400a537/1rSR87UUpy0",
"parentPublication": {
"id": "proceedings/iv/2020/9134/0",
"title": "2020 24th International Conference Information Visualisation (IV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mipr/2021/1865/0/186500a372",
"title": "Smart Portable Musical Simulation System Based on Unified Temperament",
"doi": null,
"abstractUrl": "/proceedings-article/mipr/2021/186500a372/1xPspwqBDUs",
"parentPublication": {
"id": "proceedings/mipr/2021/1865/0",
"title": "2021 IEEE 4th International Conference on Multimedia Information Processing and Retrieval (MIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNy5hRd3",
"title": "Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on",
"acronym": "wi-iat",
"groupId": "1001411",
"volume": "1",
"displayVolume": "0",
"year": "2010",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNvo67An",
"doi": "10.1109/WI-IAT.2010.162",
"title": "Muzk Mesh: Interlinking Semantic Music Data",
"normalizedTitle": "Muzk Mesh: Interlinking Semantic Music Data",
"abstract": "The vision of the Semantic Web is to lift current Web into semantic repositories where heterogeneous data can be queried and different services can be mashed up. The Web becomes a platform for integrating data and services. The paper discusses the MuzkMesh music portal which mashups existing semantic music data from the Linked Open Data (LOD) bubbles and other common APIs. It aims to demo the power of semantic integration and useful use scenarios on music retrieval and entertainment.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The vision of the Semantic Web is to lift current Web into semantic repositories where heterogeneous data can be queried and different services can be mashed up. The Web becomes a platform for integrating data and services. The paper discusses the MuzkMesh music portal which mashups existing semantic music data from the Linked Open Data (LOD) bubbles and other common APIs. It aims to demo the power of semantic integration and useful use scenarios on music retrieval and entertainment.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The vision of the Semantic Web is to lift current Web into semantic repositories where heterogeneous data can be queried and different services can be mashed up. The Web becomes a platform for integrating data and services. The paper discusses the MuzkMesh music portal which mashups existing semantic music data from the Linked Open Data (LOD) bubbles and other common APIs. It aims to demo the power of semantic integration and useful use scenarios on music retrieval and entertainment.",
"fno": "4191a699",
"keywords": [
"Semantic Mashup",
"Music Data",
"Data Integration",
"Linked Open Data"
],
"authors": [
{
"affiliation": null,
"fullName": "Mayank Singhi",
"givenName": "Mayank",
"surname": "Singhi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Ying Ding",
"givenName": "Ying",
"surname": "Ding",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Yuyin Sun",
"givenName": "Yuyin",
"surname": "Sun",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wi-iat",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2010-08-01T00:00:00",
"pubType": "proceedings",
"pages": "699-702",
"year": "2010",
"issn": null,
"isbn": "978-0-7695-4191-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4191a695",
"articleId": "12OmNCeaPY5",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4191a703",
"articleId": "12OmNwkzuo8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ispdc/2011/4540/0/4540a247",
"title": "SIGMA - SemantIc Government Mash-Up Application: Using Semantic Web Technologies to Provide Access to Governmental Data",
"doi": null,
"abstractUrl": "/proceedings-article/ispdc/2011/4540a247/12OmNAHEpAX",
"parentPublication": {
"id": "proceedings/ispdc/2011/4540/0",
"title": "Parallel and Distributed Computing, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pci/2009/3788/0/3788a043",
"title": "Semantic Web Multimedia Metadata Retrieval: A Music Approach",
"doi": null,
"abstractUrl": "/proceedings-article/pci/2009/3788a043/12OmNAYoKi5",
"parentPublication": {
"id": "proceedings/pci/2009/3788/0",
"title": "2009 13th Panhellenic Conference on Informatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/greencom-cpscom/2010/4331/0/4331a653",
"title": "Towards Our Real Life- SMMS: Semantic-Based Mobile Mashup System",
"doi": null,
"abstractUrl": "/proceedings-article/greencom-cpscom/2010/4331a653/12OmNAndigp",
"parentPublication": {
"id": "proceedings/greencom-cpscom/2010/4331/0",
"title": "IEEE-ACM International Conference on Green Computing and Communications and International Conference on Cyber, Physical and Social Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/skg/2012/4794/0/4794a265",
"title": "Integrating Financial Data Using Semantic Web for Improved Visibility",
"doi": null,
"abstractUrl": "/proceedings-article/skg/2012/4794a265/12OmNwpGgPT",
"parentPublication": {
"id": "proceedings/skg/2012/4794/0",
"title": "Semantics, Knowledge and Grid, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsc/2011/4492/0/4492a344",
"title": "A Multidimensional Semantic Space for Data Model Independent Queries over RDF Data",
"doi": null,
"abstractUrl": "/proceedings-article/icsc/2011/4492a344/12OmNyKa6eF",
"parentPublication": {
"id": "proceedings/icsc/2011/4492/0",
"title": "2011 IEEE Fifth International Conference on Semantic Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ncm/2009/3769/0/3769a338",
"title": "Semantic Text Mining with Linked Data",
"doi": null,
"abstractUrl": "/proceedings-article/ncm/2009/3769a338/12OmNz2C1tr",
"parentPublication": {
"id": "proceedings/ncm/2009/3769/0",
"title": "Networked Computing and Advanced Information Management, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmla/2011/4607/2/4607b112",
"title": "Looking Beyond Genres: Identifying Meaningful Semantic Layers from Tags in Online Music Collections",
"doi": null,
"abstractUrl": "/proceedings-article/icmla/2011/4607b112/12OmNzG4gsD",
"parentPublication": {
"id": "proceedings/icmla/2011/4607/2",
"title": "Machine Learning and Applications, Fourth International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsac/2011/4439/0/4439a245",
"title": "Managing Web Content Using Linked Data Principles - Combining Semantic Structure with Dynamic Content Syndication",
"doi": null,
"abstractUrl": "/proceedings-article/compsac/2011/4439a245/12OmNzcxZop",
"parentPublication": {
"id": "proceedings/compsac/2011/4439/0",
"title": "2011 IEEE 35th Annual Computer Software and Applications Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2009/02/mmu2009020052",
"title": "Interlinking Music-Related Data on the Web",
"doi": null,
"abstractUrl": "/magazine/mu/2009/02/mmu2009020052/13rRUxC0SJ4",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/jcdl/2019/1547/0/154700a434",
"title": "MELD: A Linked Data Framework for Multimedia Access to Music Digital Libraries",
"doi": null,
"abstractUrl": "/proceedings-article/jcdl/2019/154700a434/1ckrE95M72U",
"parentPublication": {
"id": "proceedings/jcdl/2019/1547/0",
"title": "2019 ACM/IEEE Joint Conference on Digital Libraries (JCDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "13xI8A66zF8",
"title": "2018 IEEE International Conference on Cognitive Computing (ICCC)",
"acronym": "iccc",
"groupId": "1821784",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "13xI8A0ZNjm",
"doi": "10.1109/ICCC.2018.00023",
"title": "MUSE Prototype for Music Sentiment Expression",
"normalizedTitle": "MUSE Prototype for Music Sentiment Expression",
"abstract": "This paper briefly describes and evaluates MUSE, a MUsical Sentiment Expression prototype system, taking as input a MIDI music file and producing as output a sentiment vector describing the 6 primary emotions (i.e., anger, fear, joy, love, sadness, and surprise) expressed by the music file.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This paper briefly describes and evaluates MUSE, a MUsical Sentiment Expression prototype system, taking as input a MIDI music file and producing as output a sentiment vector describing the 6 primary emotions (i.e., anger, fear, joy, love, sadness, and surprise) expressed by the music file.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This paper briefly describes and evaluates MUSE, a MUsical Sentiment Expression prototype system, taking as input a MIDI music file and producing as output a sentiment vector describing the 6 primary emotions (i.e., anger, fear, joy, love, sadness, and surprise) expressed by the music file.",
"fno": "724101a106",
"keywords": [
"Emotion Recognition",
"Learning Artificial Intelligence",
"Music",
"Sentiment Analysis",
"MUSE Prototype",
"MIDI Music File",
"Sentiment Vector",
"Emotions",
"Musical Sentiment Expression Prototype System",
"Music",
"Training",
"Feature Extraction",
"Sentiment Analysis",
"Frequency Domain Analysis",
"Correlation",
"Prototypes",
"Music Analysis MIDI Sentiment Analysis Supervised Learning Fuzzy K Nearest Neighbors"
],
"authors": [
{
"affiliation": null,
"fullName": "Ralph Abboud",
"givenName": "Ralph",
"surname": "Abboud",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Joe Tekli",
"givenName": "Joe",
"surname": "Tekli",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iccc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-07-01T00:00:00",
"pubType": "proceedings",
"pages": "106-109",
"year": "2018",
"issn": null,
"isbn": "978-1-5386-7241-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "724101a099",
"articleId": "13xI8B3IkXZ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "724101a110",
"articleId": "13xI8B8fV38",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ism/2005/2489/0/24890414",
"title": "Melody Extraction on MIDI Music Files",
"doi": null,
"abstractUrl": "/proceedings-article/ism/2005/24890414/12OmNBW0vBS",
"parentPublication": {
"id": "proceedings/ism/2005/2489/0",
"title": "Seventh IEEE International Symposium on Multimedia (ISM'05)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/1988/0878/0/00028447",
"title": "Sentiment extraction in music",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/1988/00028447/12OmNvqW6VV",
"parentPublication": {
"id": "proceedings/icpr/1988/0878/0",
"title": "9th International Conference on Pattern Recognition",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wedelmusic/2001/1284/0/12840043",
"title": "Content Protection and Usage Control for Digital Music",
"doi": null,
"abstractUrl": "/proceedings-article/wedelmusic/2001/12840043/12OmNxVV5S6",
"parentPublication": {
"id": "proceedings/wedelmusic/2001/1284/0",
"title": "Web Delivering of Music, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2015/9926/0/07364034",
"title": "Sentiment expression via emoticons on social media",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2015/07364034/12OmNxxvAHJ",
"parentPublication": {
"id": "proceedings/big-data/2015/9926/0",
"title": "2015 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icebe/2017/1412/0/1412a232",
"title": "Music Definition Language & Music Manipulation Language: A Coding Scheme for Music Representation and Storage",
"doi": null,
"abstractUrl": "/proceedings-article/icebe/2017/1412a232/12OmNzZ5omO",
"parentPublication": {
"id": "proceedings/icebe/2017/1412/0",
"title": "2017 IEEE 14th International Conference on e-Business Engineering (ICEBE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/snpd/2018/5889/0/08441085",
"title": "An Analysis of Music Lyrics by Measuring the Distance of Emotion and Sentiment",
"doi": null,
"abstractUrl": "/proceedings-article/snpd/2018/08441085/13bd1gQYgDL",
"parentPublication": {
"id": "proceedings/snpd/2018/5889/0",
"title": "2018 19th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2009/04/mmu2009040062",
"title": "A Web-Based Music Lecture Database Framework",
"doi": null,
"abstractUrl": "/magazine/mu/2009/04/mmu2009040062/13rRUIIVlhs",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09781257",
"title": "MUSE: Visual Analysis of Musical Semantic Sequence",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09781257/1DDydDu6nPW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cost/2022/6248/0/624800a049",
"title": "Real-time Human-Music Emotional Interaction Based on Multimodal Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/cost/2022/624800a049/1H2ps4vFCw0",
"parentPublication": {
"id": "proceedings/cost/2022/6248/0",
"title": "2022 International Conference on Culture-Oriented Science and Technology (CoST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/ta/5555/01/09484711",
"title": "The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements",
"doi": null,
"abstractUrl": "/journal/ta/5555/01/09484711/1veoi3EX1tK",
"parentPublication": {
"id": "trans/ta",
"title": "IEEE Transactions on Affective Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "18qc9v4jDKU",
"title": "2019 International Workshop on Multilayer Music Representation and Processing (MMRP)",
"acronym": "mmrp",
"groupId": "1830884",
"volume": "0",
"displayVolume": "0",
"year": "2019",
"__typename": "ProceedingType"
},
"article": {
"id": "18qc9CbHT1e",
"doi": "10.1109/MMRP.2019.00017",
"title": "Semantic Web Technology for New Experiences Throughout the Music Production-Consumption Chain",
"normalizedTitle": "Semantic Web Technology for New Experiences Throughout the Music Production-Consumption Chain",
"abstract": "The FAST project (Fusing Audio and Semantic Technology for Intelligent Music Production and Consumption) with 5 years of UK funding, has sought to create a new musical ecosystem that empowers all manner of people, from professional performers to casual listeners, to engage in new, more creative, immersive and dynamic musical experiences. Realising this requires a step-change in digital music technologies. Going beyond today's digital sound files, future experiences will demand far richer musical information, whereby music content will be packaged in a flexible, structured way that combines audio recordings with rich, layered metadata to support interactive and adaptive musical experiences. This defines the overall ambition of FAST-to lay the foundations for a new generation of ‘semantic audio’ technologies that underpin diverse future music experiences. This paper therefore aims to describe the overall vision of the project, set out the broad landscape in which it is working, highlight some key results and show how they bring out a central notion of FAST, that of Digital Music Objects, which are flexible constructs consisting of recorded music essence coupled with rich, semantic, linked metadata.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The FAST project (Fusing Audio and Semantic Technology for Intelligent Music Production and Consumption) with 5 years of UK funding, has sought to create a new musical ecosystem that empowers all manner of people, from professional performers to casual listeners, to engage in new, more creative, immersive and dynamic musical experiences. Realising this requires a step-change in digital music technologies. Going beyond today's digital sound files, future experiences will demand far richer musical information, whereby music content will be packaged in a flexible, structured way that combines audio recordings with rich, layered metadata to support interactive and adaptive musical experiences. This defines the overall ambition of FAST-to lay the foundations for a new generation of ‘semantic audio’ technologies that underpin diverse future music experiences. This paper therefore aims to describe the overall vision of the project, set out the broad landscape in which it is working, highlight some key results and show how they bring out a central notion of FAST, that of Digital Music Objects, which are flexible constructs consisting of recorded music essence coupled with rich, semantic, linked metadata.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The FAST project (Fusing Audio and Semantic Technology for Intelligent Music Production and Consumption) with 5 years of UK funding, has sought to create a new musical ecosystem that empowers all manner of people, from professional performers to casual listeners, to engage in new, more creative, immersive and dynamic musical experiences. Realising this requires a step-change in digital music technologies. Going beyond today's digital sound files, future experiences will demand far richer musical information, whereby music content will be packaged in a flexible, structured way that combines audio recordings with rich, layered metadata to support interactive and adaptive musical experiences. This defines the overall ambition of FAST-to lay the foundations for a new generation of ‘semantic audio’ technologies that underpin diverse future music experiences. This paper therefore aims to describe the overall vision of the project, set out the broad landscape in which it is working, highlight some key results and show how they bring out a central notion of FAST, that of Digital Music Objects, which are flexible constructs consisting of recorded music essence coupled with rich, semantic, linked metadata.",
"fno": "08665378",
"keywords": [
"Information Resources",
"Meta Data",
"Music",
"Semantic Web",
"FAST Project",
"Musical Ecosystem",
"Digital Music Technologies",
"Digital Sound Files",
"Music Content",
"Audio Recordings",
"Interactive Experiences",
"Semantic Audio Technologies",
"Information Source",
"Linked Metadata",
"Intelligent Music Production And Consumption",
"Fusing Audio And Semantic Technology",
"Music Production Consumption Chain",
"Semantic Web Technology",
"Music",
"Feature Extraction",
"Instruments",
"Semantics",
"Metadata",
"Production",
"Media"
],
"authors": [
{
"affiliation": "Queen Mary University of London, Centre for Digital Music, London, UK",
"fullName": "Mark Sandler",
"givenName": "Mark",
"surname": "Sandler",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Oxford, E-Research Centre, Oxford, UK",
"fullName": "David De Roure",
"givenName": "David",
"surname": "De Roure",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Nottingham, Mixed Reality Lab, Nottingham, UK",
"fullName": "Steven Benford",
"givenName": "Steven",
"surname": "Benford",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Oxford, E-Research Centre, Oxford, UK",
"fullName": "Kevin Page",
"givenName": "Kevin",
"surname": "Page",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "mmrp",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2019-01-01T00:00:00",
"pubType": "proceedings",
"pages": "49-55",
"year": "2019",
"issn": null,
"isbn": "978-1-7281-1649-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08665367",
"articleId": "18qc9HTXhlK",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08665374",
"articleId": "18qc9PHDKZG",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icsc/2016/0662/0/0662a047",
"title": "The Mobile Audio Ontology: Experiencing Dynamic Music Objects on Mobile Devices",
"doi": null,
"abstractUrl": "/proceedings-article/icsc/2016/0662a047/12OmNCcbE0n",
"parentPublication": {
"id": "proceedings/icsc/2016/0662/0",
"title": "2016 IEEE Tenth International Conference on Semantic Computing (ICSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icci-cc/2012/2795/0/06311153",
"title": "The expansion of paths in the mutual transformation mechanism of music and narrative",
"doi": null,
"abstractUrl": "/proceedings-article/icci-cc/2012/06311153/12OmNvC0sVl",
"parentPublication": {
"id": "proceedings/icci-cc/2012/2795/0",
"title": "2012 11th IEEE International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isspit/2008/3554/0/04775722",
"title": "A Genetic Algorithm Approach with Harmonic Structure Evolution for Polyphonic Music Transcription",
"doi": null,
"abstractUrl": "/proceedings-article/isspit/2008/04775722/12OmNwDAC6g",
"parentPublication": {
"id": "proceedings/isspit/2008/3554/0",
"title": "2008 8th IEEE International Symposium on Signal Processing and Information Technology. ISSPIT 2008",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmew/2015/7079/0/07169826",
"title": "Giantsteps - progress towards developing intelligent and collaborative interfaces for music production and performance",
"doi": null,
"abstractUrl": "/proceedings-article/icmew/2015/07169826/12OmNx3Zjfh",
"parentPublication": {
"id": "proceedings/icmew/2015/7079/0",
"title": "2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icetet/2008/3267/0/3267a508",
"title": "Exploring Data Analysis in Music Using Tool Praat",
"doi": null,
"abstractUrl": "/proceedings-article/icetet/2008/3267a508/12OmNxGALfS",
"parentPublication": {
"id": "proceedings/icetet/2008/3267/0",
"title": "Emerging Trends in Engineering & Technology, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vs-games/2016/2722/0/07590352",
"title": "Immersive Orchestras: Audio Processing for Orchestral Music VR Content",
"doi": null,
"abstractUrl": "/proceedings-article/vs-games/2016/07590352/12OmNxYtu8a",
"parentPublication": {
"id": "proceedings/vs-games/2016/2722/0",
"title": "2016 8th International Conference on Games and Virtual Worlds for Serious Applications (VS-Games)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2018/1737/0/08486474",
"title": "Simultaneous Realization of Multiple Music Video Applications Based on Heterogeneous Network Analysis Via Latent Link Estimation",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2018/08486474/14jQfQoIeuG",
"parentPublication": {
"id": "proceedings/icme/2018/1737/0",
"title": "2018 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mmrp/2019/1649/0/08665363",
"title": "Heretic: Modeling Anthony Braxton's Language Music",
"doi": null,
"abstractUrl": "/proceedings-article/mmrp/2019/08665363/18qcaB7dG1O",
"parentPublication": {
"id": "proceedings/mmrp/2019/1649/0",
"title": "2019 International Workshop on Multilayer Music Representation and Processing (MMRP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bracis/2019/4253/0/425300a854",
"title": "Audio Plugin Recommendation Systems for Music Production",
"doi": null,
"abstractUrl": "/proceedings-article/bracis/2019/425300a854/1fHkIS6UmME",
"parentPublication": {
"id": "proceedings/bracis/2019/4253/0",
"title": "2019 8th Brazilian Conference on Intelligent Systems (BRACIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ai4i/2019/4087/0/408700a050",
"title": "Towards Leveraging the Music Industry with Hyperknowledge",
"doi": null,
"abstractUrl": "/proceedings-article/ai4i/2019/408700a050/1i2oi1jyktG",
"parentPublication": {
"id": "proceedings/ai4i/2019/4087/0",
"title": "2019 Second International Conference on Artificial Intelligence for Industries (AI4I)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1xPsim7PuRq",
"title": "2021 IEEE 4th International Conference on Multimedia Information Processing and Retrieval (MIPR)",
"acronym": "mipr",
"groupId": "1825825",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1xPspwqBDUs",
"doi": "10.1109/MIPR51284.2021.00069",
"title": "Smart Portable Musical Simulation System Based on Unified Temperament",
"normalizedTitle": "Smart Portable Musical Simulation System Based on Unified Temperament",
"abstract": "This study builds a digital system of a portable musical instrument based on Unified Temperament. The system utilizes Equal-temperament, which integrates different modes of playing on the Musical Pad. By using the visualized and digitalized system, people without musical training will be able to give a musical performance. The Musical Pad simulates different musical instruments, including keyboard, woodwind, string, and other orchestral instruments. Therefore, music lovers can cooperate to play a variety of parts in polyphonic music. The system is suitable for general music education for non-artistic students in primary and middle schools. In the new form for music teaching and appreciation, students can participate more actively.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This study builds a digital system of a portable musical instrument based on Unified Temperament. The system utilizes Equal-temperament, which integrates different modes of playing on the Musical Pad. By using the visualized and digitalized system, people without musical training will be able to give a musical performance. The Musical Pad simulates different musical instruments, including keyboard, woodwind, string, and other orchestral instruments. Therefore, music lovers can cooperate to play a variety of parts in polyphonic music. The system is suitable for general music education for non-artistic students in primary and middle schools. In the new form for music teaching and appreciation, students can participate more actively.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This study builds a digital system of a portable musical instrument based on Unified Temperament. The system utilizes Equal-temperament, which integrates different modes of playing on the Musical Pad. By using the visualized and digitalized system, people without musical training will be able to give a musical performance. The Musical Pad simulates different musical instruments, including keyboard, woodwind, string, and other orchestral instruments. Therefore, music lovers can cooperate to play a variety of parts in polyphonic music. The system is suitable for general music education for non-artistic students in primary and middle schools. In the new form for music teaching and appreciation, students can participate more actively.",
"fno": "186500a372",
"keywords": [
"Data Visualisation",
"Music",
"Musical Acoustics",
"Musical Instruments",
"Portable Musical Instrument",
"Equal Temperament",
"Visualized System",
"Digitalized System",
"Musical Training",
"Musical Performance",
"Orchestral Instruments",
"Music Lovers",
"Polyphonic Music",
"General Music Education",
"Music Teaching",
"Digital System",
"Musical Pad",
"Smart Portable Musical Simulation System",
"Unified Temperament",
"Training",
"Visualization",
"Digital Systems",
"Instruments",
"Multimedia Systems",
"Conferences",
"Music",
"Temperament",
"Music Education",
"Instruments",
"Orchestra"
],
"authors": [
{
"affiliation": "Tianjin University,School of Precision Instrument and Opto-Electronics Engineering,Tianjin,China,300072",
"fullName": "Lin Gan",
"givenName": "Lin",
"surname": "Gan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tianjin University,School of Foreign Languages and Literature,Tianjin,China,300072",
"fullName": "Li Lv",
"givenName": "Li",
"surname": "Lv",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Beijing Normal University,State Key Laboratory of Cognitive Neuroscience and Learning,Beijing,China,100875",
"fullName": "Cuicui Wang",
"givenName": "Cuicui",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Tianjin University,College of Intelligence and Computing,Tianjin,China,300072",
"fullName": "Mu Zhang",
"givenName": "Mu",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "mipr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-09-01T00:00:00",
"pubType": "proceedings",
"pages": "372-376",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-1865-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "186500a366",
"articleId": "1xPsnttW7fy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "186500a377",
"articleId": "1xPsokwn38Y",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icalt/2009/3711/0/3711a083",
"title": "A Study of Computer-Assisted Instruction on Music Appreciation: An Example of Chinese Musical Instruments",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2009/3711a083/12OmNAPjA7O",
"parentPublication": {
"id": "proceedings/icalt/2009/3711/0",
"title": "Advanced Learning Technologies, IEEE International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2009/3959/0/3959a228",
"title": "Taxonomy of Musical Genres",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2009/3959a228/12OmNy6Zs3s",
"parentPublication": {
"id": "proceedings/sitis/2009/3959/0",
"title": "2009 Fifth International Conference on Signal Image Technology and Internet Based Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csa/2008/3428/0/3428a269",
"title": "Multitimbral Musical Instrument Classification",
"doi": null,
"abstractUrl": "/proceedings-article/csa/2008/3428a269/12OmNyFU6ZE",
"parentPublication": {
"id": "proceedings/csa/2008/3428/0",
"title": "2008 International Symposium on Computer Science and its Applications (CSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mmcs/1997/7819/0/00609561",
"title": "MusiKalscope: a graphical musical instrument",
"doi": null,
"abstractUrl": "/proceedings-article/mmcs/1997/00609561/12OmNzb7Zp3",
"parentPublication": {
"id": "proceedings/mmcs/1997/7819/0",
"title": "Proceedings of IEEE International Conference on Multimedia Computing and Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2013/04/mmu2013040076",
"title": "New Musical Instrument Design Considerations",
"doi": null,
"abstractUrl": "/magazine/mu/2013/04/mmu2013040076/13rRUEgs2IN",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mu/2017/01/mmu2017010063",
"title": "A Method and Toolkit for Digital Musical Instruments: Generating Ideas and Prototypes",
"doi": null,
"abstractUrl": "/magazine/mu/2017/01/mmu2017010063/13rRUwjGoIi",
"parentPublication": {
"id": "mags/mu",
"title": "IEEE MultiMedia",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2007/04/mcg2007040014",
"title": "An Immersive Musical Instrument Prototype",
"doi": null,
"abstractUrl": "/magazine/cg/2007/04/mcg2007040014/13rRUyfKIKx",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mmrp/2019/1649/0/08665380",
"title": "Requirements for a File Format for Smart Musical Instruments",
"doi": null,
"abstractUrl": "/proceedings-article/mmrp/2019/08665380/18qcaXJs6Aw",
"parentPublication": {
"id": "proceedings/mmrp/2019/1649/0",
"title": "2019 International Workshop on Multilayer Music Representation and Processing (MMRP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09781257",
"title": "MUSE: Visual Analysis of Musical Semantic Sequence",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09781257/1DDydDu6nPW",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmct/2022/7362/0/736200a010",
"title": "A Virtual Ethnic Musical Instrument Platform Based on Web App",
"doi": null,
"abstractUrl": "/proceedings-article/icmct/2022/736200a010/1Ml2hqurrva",
"parentPublication": {
"id": "proceedings/icmct/2022/7362/0",
"title": "2022 7th International Conference on Multimedia Communication Technologies (ICMCT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1jPbbHBGDHq",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"acronym": "wacv",
"groupId": "1000040",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1jPbrcnBX8s",
"doi": "10.1109/WACV45572.2020.9093582",
"title": "360 Panorama Synthesis from a Sparse Set of Images with Unknown Field of View",
"normalizedTitle": "360 Panorama Synthesis from a Sparse Set of Images with Unknown Field of View",
"abstract": "360° images represent scenes captured in all possible viewing directions and enable viewers to navigate freely around the scene thereby providing an immersive experience. Conversely, conventional images represent scenes in a single viewing direction with a small or limited field of view (FOV). As a result, only certain parts of the scenes are observed, and valuable information about the surroundings is lost. In this paper, a learning-based approach that reconstructs the scene in 360° × 180°from a sparse set of conventional images (typically 4 images) is proposed. The proposed approach first estimates the FOV of input images relative to the panorama. The estimated FOV is then used as the prior for synthesizing a high-resolution 360°panoramic output. The proposed method overcomes the difficulty of learning-based approach in synthesizing high resolution images (up to 512×1024). Experimental results demonstrate that the proposed method produces 360° panorama with reasonable quality. Results also show that the proposed method outperforms the alternative method and can be generalized for non-panoramic scenes and images captured by a smartphone camera.",
"abstracts": [
{
"abstractType": "Regular",
"content": "360° images represent scenes captured in all possible viewing directions and enable viewers to navigate freely around the scene thereby providing an immersive experience. Conversely, conventional images represent scenes in a single viewing direction with a small or limited field of view (FOV). As a result, only certain parts of the scenes are observed, and valuable information about the surroundings is lost. In this paper, a learning-based approach that reconstructs the scene in 360° × 180°from a sparse set of conventional images (typically 4 images) is proposed. The proposed approach first estimates the FOV of input images relative to the panorama. The estimated FOV is then used as the prior for synthesizing a high-resolution 360°panoramic output. The proposed method overcomes the difficulty of learning-based approach in synthesizing high resolution images (up to 512×1024). Experimental results demonstrate that the proposed method produces 360° panorama with reasonable quality. Results also show that the proposed method outperforms the alternative method and can be generalized for non-panoramic scenes and images captured by a smartphone camera.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "360° images represent scenes captured in all possible viewing directions and enable viewers to navigate freely around the scene thereby providing an immersive experience. Conversely, conventional images represent scenes in a single viewing direction with a small or limited field of view (FOV). As a result, only certain parts of the scenes are observed, and valuable information about the surroundings is lost. In this paper, a learning-based approach that reconstructs the scene in 360° × 180°from a sparse set of conventional images (typically 4 images) is proposed. The proposed approach first estimates the FOV of input images relative to the panorama. The estimated FOV is then used as the prior for synthesizing a high-resolution 360°panoramic output. The proposed method overcomes the difficulty of learning-based approach in synthesizing high resolution images (up to 512×1024). Experimental results demonstrate that the proposed method produces 360° panorama with reasonable quality. Results also show that the proposed method outperforms the alternative method and can be generalized for non-panoramic scenes and images captured by a smartphone camera.",
"fno": "09093582",
"keywords": [
"Image Reconstruction",
"Image Resolution",
"Learning Artificial Intelligence",
"360 Panorama Synthesis",
"Sparse Set",
"Single Viewing Direction",
"Learning Based Approach",
"Estimated FOV",
"High Resolution Images",
"Nonpanoramic Scenes",
"360 X 00 B 0 Images",
"Field Of View",
"Immersive Experience",
"Scene Reconstruction",
"High Resolution 360 X 00 B 0 Panoramic Output",
"Task Analysis",
"Estimation",
"Generators",
"Image Resolution",
"Training",
"Cameras",
"Bridges"
],
"authors": [
{
"affiliation": "Inha University,Dept. of Information and Communication Engineering,Incheon,Korea,22212",
"fullName": "Julius Surya Sumantri",
"givenName": "Julius Surya",
"surname": "Sumantri",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Inha University,Dept. of Information and Communication Engineering,Incheon,Korea,22212",
"fullName": "In Kyu Park",
"givenName": "In",
"surname": "Kyu Park",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wacv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-03-01T00:00:00",
"pubType": "proceedings",
"pages": "2375-2384",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-6553-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09093529",
"articleId": "1jPbgvLBbH2",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09093473",
"articleId": "1jPbyKqJrS8",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "trans/tg/2018/04/08260946",
"title": "The Effect of Transition Type in Multi-View 360° Media",
"doi": null,
"abstractUrl": "/journal/tg/2018/04/08260946/13rRUxly8T4",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mipr/2019/1198/0/119800a015",
"title": "FDDB-360: Face Detection in 360-Degree Fisheye Images",
"doi": null,
"abstractUrl": "/proceedings-article/mipr/2019/119800a015/19wB4BA5bEI",
"parentPublication": {
"id": "proceedings/mipr/2019/1198/0",
"title": "2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09779957",
"title": "Casual 6-DoF: free-viewpoint panorama using a handheld 360° camera",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09779957/1DBTD2uB4di",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2022/8563/0/09859817",
"title": "Omni-NeRF: Neural Radiance Field from 360° Image Captures",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2022/09859817/1G9DIJAkSzK",
"parentPublication": {
"id": "proceedings/icme/2022/8563/0",
"title": "2022 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2022/6946/0/694600d752",
"title": "360MonoDepth: High-Resolution 360° Monocular Depth Estimation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600d752/1H1mgCrsMtG",
"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/2023/9346/0/934600d056",
"title": "360MVSNet: Deep Multi-view Stereo Network with 360° Images for Indoor Scene Reconstruction",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2023/934600d056/1L8qkd9hTbi",
"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/wacv/2020/6553/0/09093262",
"title": "360-Indoor: Towards Learning Real-World Objects in 360° Indoor Equirectangular Images",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093262/1jPbAWPyE8g",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093452",
"title": "Visual Question Answering on 360° Images",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093452/1jPbCyCHgkw",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/msn/2020/9916/0/991600a291",
"title": "MEC-Assisted FoV-Aware and QoE-Driven Adaptive 360° Video Streaming for Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/msn/2020/991600a291/1sBO3kw7jnq",
"parentPublication": {
"id": "proceedings/msn/2020/9916/0",
"title": "2020 16th International Conference on Mobility, Sensing and Networking (MSN)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2021/0477/0/047700a081",
"title": "Temporally Consistent 3D Human Pose Estimation Using Dual 360° Cameras",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2021/047700a081/1uqGhVR6c2k",
"parentPublication": {
"id": "proceedings/wacv/2021/0477/0",
"title": "2021 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNyaXPPU",
"title": "2015 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)",
"acronym": "icmew",
"groupId": "1801805",
"volume": "0",
"displayVolume": "0",
"year": "2015",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwxlrdP",
"doi": "10.1109/ICMEW.2015.7169765",
"title": "What are the salient keyframes in short casual videos? an extensive user study using a new video dataset",
"normalizedTitle": "What are the salient keyframes in short casual videos? an extensive user study using a new video dataset",
"abstract": "Understanding the saliency of keyframes in short casual/home-made videos containing redundant information is an important step towards the design of successful keyframe selection and summarization techniques for such videos. Therefore, we present an extensive user study focusing on saliency of keyframes in such short redundant videos. In our study, more than 200 users annotated 32 videos, altogether selecting more than 20.000 keyframes. We present the description of the user study, the utilized annotation tool and we discuss the results. We provide also a preliminary comparison of several popular keyframe selection techniques using the ground truth derived from the annotations.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Understanding the saliency of keyframes in short casual/home-made videos containing redundant information is an important step towards the design of successful keyframe selection and summarization techniques for such videos. Therefore, we present an extensive user study focusing on saliency of keyframes in such short redundant videos. In our study, more than 200 users annotated 32 videos, altogether selecting more than 20.000 keyframes. We present the description of the user study, the utilized annotation tool and we discuss the results. We provide also a preliminary comparison of several popular keyframe selection techniques using the ground truth derived from the annotations.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Understanding the saliency of keyframes in short casual/home-made videos containing redundant information is an important step towards the design of successful keyframe selection and summarization techniques for such videos. Therefore, we present an extensive user study focusing on saliency of keyframes in such short redundant videos. In our study, more than 200 users annotated 32 videos, altogether selecting more than 20.000 keyframes. We present the description of the user study, the utilized annotation tool and we discuss the results. We provide also a preliminary comparison of several popular keyframe selection techniques using the ground truth derived from the annotations.",
"fno": "07169765",
"keywords": [
"Videos",
"Histograms",
"Motion Segmentation",
"Image Color Analysis",
"Tracking",
"Multimedia Communication",
"Streaming Media",
"Annotated Video Dataset",
"Casual Home Made Videos",
"Low Quality Videos",
"Keyframe Selection"
],
"authors": [
{
"affiliation": "Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic",
"fullName": "J. Lokoc",
"givenName": "J.",
"surname": "Lokoc",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Klagenfurt University, Institute of Information Technology, Austria",
"fullName": "B. Munzer",
"givenName": "B.",
"surname": "Munzer",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Klagenfurt University, Institute of Information Technology, Austria",
"fullName": "K. Schoeffmann",
"givenName": "K.",
"surname": "Schoeffmann",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Klagenfurt University, Institute of Information Technology, Austria",
"fullName": "M. Del Fabro",
"givenName": "M.",
"surname": "Del Fabro",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Klagenfurt University, Institute of Information Technology, Austria",
"fullName": "M. J. Primus",
"givenName": "M. J.",
"surname": "Primus",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Charles University, Faculty of Mathematics and Physics, Prague, Czech Republic",
"fullName": "T. Skopal",
"givenName": "T.",
"surname": "Skopal",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Finance and Administration, Prague, Czech Republic",
"fullName": "J. Lansky",
"givenName": "J.",
"surname": "Lansky",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icmew",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2015-06-01T00:00:00",
"pubType": "proceedings",
"pages": "1-6",
"year": "2015",
"issn": null,
"isbn": "978-1-4799-7079-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "07169764",
"articleId": "12OmNzZ5o9v",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07169766",
"articleId": "12OmNAtaS1w",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icme/2007/1016/0/04284646",
"title": "A Computational Model of Saliency Depletion/Recovery Phenomena for the Salient Region Extraction of Videos",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2007/04284646/12OmNAYGlBH",
"parentPublication": {
"id": "proceedings/icme/2007/1016/0",
"title": "2007 International Conference on Multimedia & Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209c371",
"title": "Graph Construction for Salient Object Detection in Videos",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209c371/12OmNwK7oal",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cis/2016/4840/0/4840a218",
"title": "Salient Object Detection via Video Spatio-Temporal Difference and Coherence",
"doi": null,
"abstractUrl": "/proceedings-article/cis/2016/4840a218/12OmNx76TPr",
"parentPublication": {
"id": "proceedings/cis/2016/4840/0",
"title": "2016 12th International Conference on Computational Intelligence and Security (CIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mipr/2018/1857/0/185701a418",
"title": "Comprehensive Dataset of Broadcast Soccer Videos",
"doi": null,
"abstractUrl": "/proceedings-article/mipr/2018/185701a418/12OmNxFsmFH",
"parentPublication": {
"id": "proceedings/mipr/2018/1857/0",
"title": "2018 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2017/0457/0/0457d224",
"title": "Predicting Salient Face in Multiple-Face Videos",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2017/0457d224/12OmNyQYtmx",
"parentPublication": {
"id": "proceedings/cvpr/2017/0457/0",
"title": "2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2017/6067/0/08019389",
"title": "Video salient object detection via cross-frame cellular automata",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2017/08019389/12OmNykTNmp",
"parentPublication": {
"id": "proceedings/icme/2017/6067/0",
"title": "2017 IEEE International Conference on Multimedia and Expo (ICME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgiv/2016/0811/0/0811a312",
"title": "Efficient Video Summarization Based on Motion SIFT-Distribution Histogram",
"doi": null,
"abstractUrl": "/proceedings-article/cgiv/2016/0811a312/12OmNzlUKP9",
"parentPublication": {
"id": "proceedings/cgiv/2016/0811/0",
"title": "2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2017/11/07779036",
"title": "Summarizing Unconstrained Videos Using Salient Montages",
"doi": null,
"abstractUrl": "/journal/tp/2017/11/07779036/13rRUNvgzba",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000f333",
"title": "Gaze Prediction in Dynamic 360° Immersive Videos",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000f333/17D45VW8brT",
"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/icfhr/2018/5875/0/587500a050",
"title": "Visual Search Engine for Handwritten and Typeset Math in Lecture Videos and LATEX Notes",
"doi": null,
"abstractUrl": "/proceedings-article/icfhr/2018/587500a050/17D45WXIkCx",
"parentPublication": {
"id": "proceedings/icfhr/2018/5875/0",
"title": "2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNylsZKr",
"title": "Proceedings 2nd Annual IEEE International Symposium on Bioinformatics and Bioengineering (BIBE 2001)",
"acronym": "bibe",
"groupId": "1000075",
"volume": "0",
"displayVolume": "0",
"year": "2001",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNqGRGdS",
"doi": "10.1109/BIBE.2001.974425",
"title": "Medical decision-making and collaborative reasoning",
"normalizedTitle": "Medical decision-making and collaborative reasoning",
"abstract": "An overview is presented of different constraints in conventional medical decision-making for improving collaborative reasoning. When designing and implementing an effective assisted diagnoses system it is imperative to make a complete study of reasoning processes used by physicians every day. We are particularly interested in studying the process of conventional decision-making when, at the first stage, a physician faces a diagnosis decision and, later, when this decision is made by several physicians, that is, when collaborative medical reasoning is involved. The design of an architecture that supports the requirements of medical practices in this framework is presented.",
"abstracts": [
{
"abstractType": "Regular",
"content": "An overview is presented of different constraints in conventional medical decision-making for improving collaborative reasoning. When designing and implementing an effective assisted diagnoses system it is imperative to make a complete study of reasoning processes used by physicians every day. We are particularly interested in studying the process of conventional decision-making when, at the first stage, a physician faces a diagnosis decision and, later, when this decision is made by several physicians, that is, when collaborative medical reasoning is involved. The design of an architecture that supports the requirements of medical practices in this framework is presented.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "An overview is presented of different constraints in conventional medical decision-making for improving collaborative reasoning. When designing and implementing an effective assisted diagnoses system it is imperative to make a complete study of reasoning processes used by physicians every day. We are particularly interested in studying the process of conventional decision-making when, at the first stage, a physician faces a diagnosis decision and, later, when this decision is made by several physicians, that is, when collaborative medical reasoning is involved. The design of an architecture that supports the requirements of medical practices in this framework is presented.",
"fno": "00974425",
"keywords": [
"Decision Making",
"Collaboration",
"Medical Diagnostic Imaging",
"Diseases",
"Testing",
"Uncertainty",
"Humans",
"History",
"Decision Support Systems",
"Inference Mechanisms"
],
"authors": [
{
"affiliation": "Ecole Nat. Superieure des Telecommun. de Bretagne, Brest, France",
"fullName": "J.M. Quintero",
"givenName": "J.M.",
"surname": "Quintero",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "A. Aguilera",
"givenName": "A.",
"surname": "Aguilera",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "M. Abraham",
"givenName": "M.",
"surname": "Abraham",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "H. Villegas",
"givenName": "H.",
"surname": "Villegas",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "G. Montilla",
"givenName": "G.",
"surname": "Montilla",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "B. Solaiman",
"givenName": "B.",
"surname": "Solaiman",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "bibe",
"isOpenAccess": false,
"showRecommendedArticles": false,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2001-01-01T00:00:00",
"pubType": "proceedings",
"pages": "161-165",
"year": "2001",
"issn": null,
"isbn": "0-7695-1423-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "00974424",
"articleId": "12OmNy49sSM",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "00974426",
"articleId": "12OmNwDSdbY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxV4ity",
"title": "2016 IEEE Tenth International Conference on Semantic Computing (ICSC)",
"acronym": "icsc",
"groupId": "1001356",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwB2dUS",
"doi": "10.1109/ICSC.2016.53",
"title": "Visualization of Pain Severity Events in Clinical Records Using Semantic Structures",
"normalizedTitle": "Visualization of Pain Severity Events in Clinical Records Using Semantic Structures",
"abstract": "Physicians are often required to make critical medical decisions that may be based on previous events in the patient's health history. However, these events may be very difficult to locate in the patient record due to the large volume of unstructured textual data in the patient's chart. Even when the chart is housed in an electronic health record (EHR) system, keyword search within the chart may produce many results that are not relevant or that may overlook related expressions and concepts entirely. In addition, some medical events, such as the occurrence of symptoms, are associated with important attributes such as location or severity, and require other elements such as the type of clinical note and its date and time in order to provide the proper context of the event. This paper describes a prototype system that performs ontology-based semantic search through clinical text to extract pain severity events, and then presents them in a visualization to monitor the progression of pain over time.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Physicians are often required to make critical medical decisions that may be based on previous events in the patient's health history. However, these events may be very difficult to locate in the patient record due to the large volume of unstructured textual data in the patient's chart. Even when the chart is housed in an electronic health record (EHR) system, keyword search within the chart may produce many results that are not relevant or that may overlook related expressions and concepts entirely. In addition, some medical events, such as the occurrence of symptoms, are associated with important attributes such as location or severity, and require other elements such as the type of clinical note and its date and time in order to provide the proper context of the event. This paper describes a prototype system that performs ontology-based semantic search through clinical text to extract pain severity events, and then presents them in a visualization to monitor the progression of pain over time.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Physicians are often required to make critical medical decisions that may be based on previous events in the patient's health history. However, these events may be very difficult to locate in the patient record due to the large volume of unstructured textual data in the patient's chart. Even when the chart is housed in an electronic health record (EHR) system, keyword search within the chart may produce many results that are not relevant or that may overlook related expressions and concepts entirely. In addition, some medical events, such as the occurrence of symptoms, are associated with important attributes such as location or severity, and require other elements such as the type of clinical note and its date and time in order to provide the proper context of the event. This paper describes a prototype system that performs ontology-based semantic search through clinical text to extract pain severity events, and then presents them in a visualization to monitor the progression of pain over time.",
"fno": "0662a321",
"keywords": [
"Pain",
"Semantics",
"Ontologies",
"Knowledge Based Systems",
"Engines",
"Visualization",
"Context",
"Clinical Decision Support",
"Visualization",
"Information Extraction",
"Clinical Text",
"Semantic Structure"
],
"authors": [
{
"affiliation": null,
"fullName": "Clare T. Grasso",
"givenName": "Clare T.",
"surname": "Grasso",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Anupam Joshi",
"givenName": "Anupam",
"surname": "Joshi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Eliot Siegel",
"givenName": "Eliot",
"surname": "Siegel",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icsc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-02-01T00:00:00",
"pubType": "proceedings",
"pages": "321-324",
"year": "2016",
"issn": null,
"isbn": "978-1-5090-0662-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "0662a314",
"articleId": "12OmNzcxZfH",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "0662a325",
"articleId": "12OmNCga1N7",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/fg/2011/9140/0/05771462",
"title": "Painful data: The UNBC-McMaster shoulder pain expression archive database",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2011/05771462/12OmNrMZpIu",
"parentPublication": {
"id": "proceedings/fg/2011/9140/0",
"title": "Face and Gesture 2011",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/incos/2010/4278/0/4278a259",
"title": "Epione: An Innovative Pain Management System Using Facial Expression Analysis, Biofeedback and Augmented Reality-Based Distraction",
"doi": null,
"abstractUrl": "/proceedings-article/incos/2010/4278a259/12OmNvnfkag",
"parentPublication": {
"id": "proceedings/incos/2010/4278/0",
"title": "Intelligent Networking and Collaborative Systems, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acii/2017/0563/0/08273618",
"title": "Embedding stacked bottleneck vocal features in a LSTM architecture for automatic pain level classification during emergency triage",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2017/08273618/12OmNx4Q6CF",
"parentPublication": {
"id": "proceedings/acii/2017/0563/0",
"title": "2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icmtma/2013/4932/0/4932a368",
"title": "Clinical and Biomechanical Analyses of Whiplash Injuries",
"doi": null,
"abstractUrl": "/proceedings-article/icmtma/2013/4932a368/12OmNzGlRDC",
"parentPublication": {
"id": "proceedings/icmtma/2013/4932/0",
"title": "2013 Fifth International Conference on Measuring Technology and Mechatronics Automation",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/fg/2018/2335/0/233501a525",
"title": "Clinical Valid Pain Database with Biomarker and Visual Information for Pain Level Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/fg/2018/233501a525/12OmNzTppB1",
"parentPublication": {
"id": "proceedings/fg/2018/2335/0",
"title": "2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2013/5089/0/5089a483",
"title": "Using Social Network Analysis to Identify Key Players within Clinical Teams for Improving Pain Management",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2013/5089a483/12OmNzkuKJG",
"parentPublication": {
"id": "proceedings/ichi/2013/5089/0",
"title": "2013 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdh/2022/8149/0/814900a047",
"title": "Definition and clinical validation of Pain Patient States from high-dimensional mobile data: application to a chronic pain cohort",
"doi": null,
"abstractUrl": "/proceedings-article/icdh/2022/814900a047/1G6jNqFbKiQ",
"parentPublication": {
"id": "proceedings/icdh/2022/8149/0",
"title": "2022 IEEE International Conference on Digital Health (ICDH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2019/1377/0/08797681",
"title": "VR and Volitional Pain: Testing Immersive Interventions During a Tattoo",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08797681/1cJ1hLgyRKU",
"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/acii/2019/3888/0/08925480",
"title": "Automatic Neonatal Pain Estimation: An Acute Pain in Neonates Database",
"doi": null,
"abstractUrl": "/proceedings-article/acii/2019/08925480/1fHGIlcWkXm",
"parentPublication": {
"id": "proceedings/acii/2019/3888/0",
"title": "2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iisa/2020/2346/0/09284379",
"title": "Prediction of pain in knee osteoarthritis patients using machine learning: Data from Osteoarthritis Initiative",
"doi": null,
"abstractUrl": "/proceedings-article/iisa/2020/09284379/1pttMDALIEU",
"parentPublication": {
"id": "proceedings/iisa/2020/2346/0",
"title": "2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNAS9zxg",
"title": "2014 IEEE 27th International Symposium on Computer-Based Medical Systems (CBMS)",
"acronym": "cbms",
"groupId": "1000153",
"volume": "0",
"displayVolume": "0",
"year": "2014",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwEJ13T",
"doi": "10.1109/CBMS.2014.108",
"title": "Need and Requirements Elicitation for Electronic Access to Patient's Medication History in the Emergency Department",
"normalizedTitle": "Need and Requirements Elicitation for Electronic Access to Patient's Medication History in the Emergency Department",
"abstract": "Electronic access to patient's medication history (PMH) in the emergency department (ED) in Portugal is not widely granted, nor has the importance of such access been clearly assessed. Given the known association between poor PMH and medication errors, the goal of this study was to gather requirements for such a system, assessing physicians' opinions regarding the importance of having access to PMH in the ED. A questionnaire was sent to all Portuguese public hospitals which approved the study, and forwarded by email by the internal services of each hospital to ED physicians. Fourteen hospitals authorized the study, from which 83 ED physicians answered the questionnaire. PMH-related information considered most important focused on medication name and posology (>90%) and date and dose of prescription (>80%), but also date of dispensing of medications (>40%). Other information such as allergies (99%) and adverse reactions (96%) were similarly considered important, and physicians agree with the inclusion of non-prescription medications (85%) as well as homeopathic medicines (64%). Overall, access to PMH in the ED appears to be important and present benefits to patients' care. Given this, electronic access to PHM should be settled in Portuguese ED.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Electronic access to patient's medication history (PMH) in the emergency department (ED) in Portugal is not widely granted, nor has the importance of such access been clearly assessed. Given the known association between poor PMH and medication errors, the goal of this study was to gather requirements for such a system, assessing physicians' opinions regarding the importance of having access to PMH in the ED. A questionnaire was sent to all Portuguese public hospitals which approved the study, and forwarded by email by the internal services of each hospital to ED physicians. Fourteen hospitals authorized the study, from which 83 ED physicians answered the questionnaire. PMH-related information considered most important focused on medication name and posology (>90%) and date and dose of prescription (>80%), but also date of dispensing of medications (>40%). Other information such as allergies (99%) and adverse reactions (96%) were similarly considered important, and physicians agree with the inclusion of non-prescription medications (85%) as well as homeopathic medicines (64%). Overall, access to PMH in the ED appears to be important and present benefits to patients' care. Given this, electronic access to PHM should be settled in Portuguese ED.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Electronic access to patient's medication history (PMH) in the emergency department (ED) in Portugal is not widely granted, nor has the importance of such access been clearly assessed. Given the known association between poor PMH and medication errors, the goal of this study was to gather requirements for such a system, assessing physicians' opinions regarding the importance of having access to PMH in the ED. A questionnaire was sent to all Portuguese public hospitals which approved the study, and forwarded by email by the internal services of each hospital to ED physicians. Fourteen hospitals authorized the study, from which 83 ED physicians answered the questionnaire. PMH-related information considered most important focused on medication name and posology (>90%) and date and dose of prescription (>80%), but also date of dispensing of medications (>40%). Other information such as allergies (99%) and adverse reactions (96%) were similarly considered important, and physicians agree with the inclusion of non-prescription medications (85%) as well as homeopathic medicines (64%). Overall, access to PMH in the ED appears to be important and present benefits to patients' care. Given this, electronic access to PHM should be settled in Portuguese ED.",
"fno": "4435a497",
"keywords": [
"Medical Diagnostic Imaging",
"Hospitals",
"History",
"Educational Institutions",
"Safety",
"Electronic Mail",
"Computer Communication Networks",
"Medication Errors",
"Medical History Taking",
"Community Pharmacy Services"
],
"authors": [
{
"affiliation": null,
"fullName": "Margarida David",
"givenName": "Margarida",
"surname": "David",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Fernando Rosa",
"givenName": "Fernando",
"surname": "Rosa",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Pedro Pereira Rodrigues",
"givenName": "Pedro Pereira",
"surname": "Rodrigues",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "cbms",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2014-05-01T00:00:00",
"pubType": "proceedings",
"pages": "497-498",
"year": "2014",
"issn": "2372-9198",
"isbn": "978-1-4799-4435-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4435a495",
"articleId": "12OmNqNXErE",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4435a499",
"articleId": "12OmNzBwGno",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/bibm/2017/3050/0/08217776",
"title": "Medi-Deep: Deep control in a medication usage",
"doi": null,
"abstractUrl": "/proceedings-article/bibm/2017/08217776/12OmNCdk2TY",
"parentPublication": {
"id": "proceedings/bibm/2017/3050/0",
"title": "2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/scamc/1983/0503/0/00764588",
"title": "Physician acceptance of a computerized outpatient medication system in a teaching hospital group practice",
"doi": null,
"abstractUrl": "/proceedings-article/scamc/1983/00764588/12OmNrAdsuL",
"parentPublication": {
"id": "proceedings/scamc/1983/0503/0",
"title": "1983 The Seventh Annual Symposium on Computer Applications in Medical Care",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2016/6117/0/6117a102",
"title": "Linking Patient Alone Time and Provider Time to Staffing Levels and LOS at the Emergency Department: A RFID Based Study",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2016/6117a102/12OmNrK9q1q",
"parentPublication": {
"id": "proceedings/ichi/2016/6117/0",
"title": "2016 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2016/5670/0/5670d189",
"title": "Internet Usage, Physician Performances and Patient's Trust in Physician During Diagnoses: Investigating Both Pre-Use and Not-Use Internet Groups",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2016/5670d189/12OmNs5rkMT",
"parentPublication": {
"id": "proceedings/hicss/2016/5670/0",
"title": "2016 49th Hawaii International Conference on System Sciences (HICSS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icisa/2010/5942/0/05480410",
"title": "A Hybrid Method to Predict Angina Pectoris through Mining Emergency Data",
"doi": null,
"abstractUrl": "/proceedings-article/icisa/2010/05480410/12OmNwpXRWA",
"parentPublication": {
"id": "proceedings/icisa/2010/5942/0",
"title": "2010 International Conference on Information Science and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/dsaa/2016/5206/0/07796958",
"title": "MedCare: Leveraging Medication Similarity for Disease Prediction",
"doi": null,
"abstractUrl": "/proceedings-article/dsaa/2016/07796958/12OmNx3Zje1",
"parentPublication": {
"id": "proceedings/dsaa/2016/5206/0",
"title": "2016 IEEE 3rd International Conference on Data Science and Advanced Analytics (DSAA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/2003/8131/2/01261655",
"title": "Simulating six sigma improvement ideas for a hospital emergency department",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/2003/01261655/12OmNyeWdJI",
"parentPublication": {
"id": "proceedings/wsc/2003/8131/2",
"title": "Proceedings of the 2003 Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/etelemed/2009/3532/0/3532a001",
"title": "Using Timeline Displays to Improve Medication Reconciliation",
"doi": null,
"abstractUrl": "/proceedings-article/etelemed/2009/3532a001/12OmNzYeB4I",
"parentPublication": {
"id": "proceedings/etelemed/2009/3532/0",
"title": "eHealth, Telemedicine, and Social Medicine, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/taai/2018/1229/0/122900a001",
"title": "Using Machine Learning Algorithms in Medication for Cardiac Arrest Early Warning System Construction and Forecasting",
"doi": null,
"abstractUrl": "/proceedings-article/taai/2018/122900a001/17D45X2fUEO",
"parentPublication": {
"id": "proceedings/taai/2018/1229/0",
"title": "2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2022/1008/0/10017700",
"title": "Towards a novel spontaneous medication error reporting tool for enhancing patient safety",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2022/10017700/1KJxscjDRSw",
"parentPublication": {
"id": "proceedings/aiccsa/2022/1008/0",
"title": "2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNAle6y4",
"title": "2017 IEEE Workshop on Visual Analytics in Healthcare (VAHC)",
"acronym": "vahc",
"groupId": "1826204",
"volume": "0",
"displayVolume": "0",
"year": "2017",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyYDDIU",
"doi": "10.1109/VAHC.2017.8387501",
"title": "A timeline-based framework for aggregating and summarizing electronic health records",
"normalizedTitle": "A timeline-based framework for aggregating and summarizing electronic health records",
"abstract": "Electronic Health Records (EHRs) contain a significant amount of longitudinal information about a patient including pre-existing conditions, earlier diagnosis, previous treatments, active medications, base-line measurements for different clinical results, and much more. Unfortunately, data integration within an EHR and across different EHRs continue to be a limiting factor that threatens patient safety and the efficiency of healthcare providers. The disparate nature of the clinical data even within a single EHR often results in clinicians having to access and review a number of reports, modules, and tabs to access different data elements and clinical results. Due to the fragmented nature of EHR interfaces and the number of interactions that are needed to access clinical data, clinicians often spend a considerable part of their time going through the EHR of a patient in order to get a comprehensive overview and to be able to provide quality care. Data visualization and the integration of analytic models within graphical interfaces present a unique opportunity to effectively combine multiple clinical data sources and reduce the cognitive burden that disparate reports often have for end-users. With the ability of visualization techniques to summarize different data elements, we present a timeline-based framework to effectively aggregate and summarize the disparate clinical data of a patient enclosed within an EHR. The interface combines a set of visualization techniques with machine learning summarization approaches to optimize the process of understanding a patient's history through views that allow for easily skimming and jumping through time, filters for limiting the amount of information shown, and a hierarchy of summaries that provide an interface to view and compare different time frames.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Electronic Health Records (EHRs) contain a significant amount of longitudinal information about a patient including pre-existing conditions, earlier diagnosis, previous treatments, active medications, base-line measurements for different clinical results, and much more. Unfortunately, data integration within an EHR and across different EHRs continue to be a limiting factor that threatens patient safety and the efficiency of healthcare providers. The disparate nature of the clinical data even within a single EHR often results in clinicians having to access and review a number of reports, modules, and tabs to access different data elements and clinical results. Due to the fragmented nature of EHR interfaces and the number of interactions that are needed to access clinical data, clinicians often spend a considerable part of their time going through the EHR of a patient in order to get a comprehensive overview and to be able to provide quality care. Data visualization and the integration of analytic models within graphical interfaces present a unique opportunity to effectively combine multiple clinical data sources and reduce the cognitive burden that disparate reports often have for end-users. With the ability of visualization techniques to summarize different data elements, we present a timeline-based framework to effectively aggregate and summarize the disparate clinical data of a patient enclosed within an EHR. The interface combines a set of visualization techniques with machine learning summarization approaches to optimize the process of understanding a patient's history through views that allow for easily skimming and jumping through time, filters for limiting the amount of information shown, and a hierarchy of summaries that provide an interface to view and compare different time frames.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Electronic Health Records (EHRs) contain a significant amount of longitudinal information about a patient including pre-existing conditions, earlier diagnosis, previous treatments, active medications, base-line measurements for different clinical results, and much more. Unfortunately, data integration within an EHR and across different EHRs continue to be a limiting factor that threatens patient safety and the efficiency of healthcare providers. The disparate nature of the clinical data even within a single EHR often results in clinicians having to access and review a number of reports, modules, and tabs to access different data elements and clinical results. Due to the fragmented nature of EHR interfaces and the number of interactions that are needed to access clinical data, clinicians often spend a considerable part of their time going through the EHR of a patient in order to get a comprehensive overview and to be able to provide quality care. Data visualization and the integration of analytic models within graphical interfaces present a unique opportunity to effectively combine multiple clinical data sources and reduce the cognitive burden that disparate reports often have for end-users. With the ability of visualization techniques to summarize different data elements, we present a timeline-based framework to effectively aggregate and summarize the disparate clinical data of a patient enclosed within an EHR. The interface combines a set of visualization techniques with machine learning summarization approaches to optimize the process of understanding a patient's history through views that allow for easily skimming and jumping through time, filters for limiting the amount of information shown, and a hierarchy of summaries that provide an interface to view and compare different time frames.",
"fno": "08387501",
"keywords": [
"Data Visualization",
"History",
"Medical Diagnostic Imaging",
"Navigation",
"Aggregates",
"Electronic Medical Records",
"Limiting"
],
"authors": [
{
"affiliation": null,
"fullName": "Filip Dabek",
"givenName": "Filip",
"surname": "Dabek",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Elizabeth Jimenez",
"givenName": "Elizabeth",
"surname": "Jimenez",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Jesus J. Caban",
"givenName": "Jesus J.",
"surname": "Caban",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vahc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2017-10-01T00:00:00",
"pubType": "proceedings",
"pages": "55-61",
"year": "2017",
"issn": null,
"isbn": "978-1-5386-3187-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08387500",
"articleId": "12OmNzZmZsv",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08387502",
"articleId": "12OmNvkGW8Q",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cbms/2014/4435/0/4435a267",
"title": "Electronic Health Records: A Survey of the Experiences and Expectations of Irish Dermatologists",
"doi": null,
"abstractUrl": "/proceedings-article/cbms/2014/4435a267/12OmNBhpRZ0",
"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/trustcom-bigdatase-i-spa/2016/3205/0/07847074",
"title": "MTPGraph: A Data-Driven Approach to Predict Medical Risk Based on Temporal Profile Graph",
"doi": null,
"abstractUrl": "/proceedings-article/trustcom-bigdatase-i-spa/2016/07847074/12OmNxw5Bcv",
"parentPublication": {
"id": "proceedings/trustcom-bigdatase-i-spa/2016/3205/0",
"title": "2016 IEEE Trustcom/BigDataSE/ISPA",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2014/5209/0/5209c763",
"title": "DensityTransfer: A Data Driven Approach for Imputing Electronic Health Records",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209c763/12OmNyL0Tw5",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibmw/2011/1612/0/06112447",
"title": "Using a feedback system to enhance chart note quality in Electronic Health Records",
"doi": null,
"abstractUrl": "/proceedings-article/bibmw/2011/06112447/12OmNzTYBSF",
"parentPublication": {
"id": "proceedings/bibmw/2011/1612/0",
"title": "2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)",
"__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": "proceedings/ichi/2016/6117/0/6117a302",
"title": "LabLinker: Finding Links of Laboratory Test Results between Structured Records and Clinical Notes",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2016/6117a302/12OmNzcPAEL",
"parentPublication": {
"id": "proceedings/ichi/2016/6117/0",
"title": "2016 IEEE International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tb/2017/03/07513372",
"title": "Modeling Healthcare Quality via Compact Representations of Electronic Health Records",
"doi": null,
"abstractUrl": "/journal/tb/2017/03/07513372/13rRUwbs2f4",
"parentPublication": {
"id": "trans/tb",
"title": "IEEE/ACM Transactions on Computational Biology and Bioinformatics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsa-c/2020/7415/0/09095666",
"title": "Defining Security Metrics To Evaluate Electronic Health Records Systems: A Case Study in Chile",
"doi": null,
"abstractUrl": "/proceedings-article/icsa-c/2020/09095666/1jXvqC6ouaY",
"parentPublication": {
"id": "proceedings/icsa-c/2020/7415/0",
"title": "2020 IEEE International Conference on Software Architecture Companion (ICSA-C)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/blockchain/2020/0495/0/049500a456",
"title": "Secured Inter-Healthcare Patient Health Records Exchange Architecture",
"doi": null,
"abstractUrl": "/proceedings-article/blockchain/2020/049500a456/1pttSXtqMne",
"parentPublication": {
"id": "proceedings/blockchain/2020/0495/0",
"title": "2020 IEEE International Conference on Blockchain (Blockchain)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2020/6251/0/09377795",
"title": "Heterogeneous Similarity Graph Neural Network on Electronic Health Records",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2020/09377795/1s64EJgr0qI",
"parentPublication": {
"id": "proceedings/big-data/2020/6251/0",
"title": "2020 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxzMnU0",
"title": "2011 15th International Conference on Information Visualisation",
"acronym": "iv",
"groupId": "1000370",
"volume": "0",
"displayVolume": "0",
"year": "2011",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzVGcC4",
"doi": "10.1109/IV.2011.87",
"title": "Adaptive Visual Symbols for Personal Health Records",
"normalizedTitle": "Adaptive Visual Symbols for Personal Health Records",
"abstract": "As a hub of information controlled by the patient, personal health records (PHR) collect information from the patient medical history including a wide variety of data sources as patient's observations, lab results, clinical findings and in the future maybe even personal genetic data and automatic recordings from monitoring devices. This development will on the one hand make health care more personalized and user controlled but on the other hand also overloads consumers with a huge amount of data. To address this issue we developed a framework for adaptive visual symbols (AVS). An AVS can adapt its appearance and level of detail during the communication process. Finally we demonstrate the AVS principle for the visualization of personal health records.",
"abstracts": [
{
"abstractType": "Regular",
"content": "As a hub of information controlled by the patient, personal health records (PHR) collect information from the patient medical history including a wide variety of data sources as patient's observations, lab results, clinical findings and in the future maybe even personal genetic data and automatic recordings from monitoring devices. This development will on the one hand make health care more personalized and user controlled but on the other hand also overloads consumers with a huge amount of data. To address this issue we developed a framework for adaptive visual symbols (AVS). An AVS can adapt its appearance and level of detail during the communication process. Finally we demonstrate the AVS principle for the visualization of personal health records.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "As a hub of information controlled by the patient, personal health records (PHR) collect information from the patient medical history including a wide variety of data sources as patient's observations, lab results, clinical findings and in the future maybe even personal genetic data and automatic recordings from monitoring devices. This development will on the one hand make health care more personalized and user controlled but on the other hand also overloads consumers with a huge amount of data. To address this issue we developed a framework for adaptive visual symbols (AVS). An AVS can adapt its appearance and level of detail during the communication process. Finally we demonstrate the AVS principle for the visualization of personal health records.",
"fno": "06004004",
"keywords": [
"Health Care",
"Medical Information Systems",
"Adaptive Visual Symbol",
"Personal Health Record",
"Personal Genetic Data",
"Health Care",
"Communication Process",
"Visualization",
"Medical Services",
"Adaptation Models",
"Semantics",
"Medical Diagnostic Imaging",
"User Interfaces",
"Object Oriented Modeling",
"Electronic Health Records",
"Information Visualisation"
],
"authors": [
{
"affiliation": null,
"fullName": "Heimo Muller",
"givenName": "Heimo",
"surname": "Muller",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Herman Maurer",
"givenName": "Herman",
"surname": "Maurer",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Robert Reihs",
"givenName": "Robert",
"surname": "Reihs",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Stefan Sauer",
"givenName": "Stefan",
"surname": "Sauer",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Kurt Zatloukal",
"givenName": "Kurt",
"surname": "Zatloukal",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "iv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2011-07-01T00:00:00",
"pubType": "proceedings",
"pages": "220-225",
"year": "2011",
"issn": "1550-6037",
"isbn": "978-1-4577-0868-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06004003",
"articleId": "12OmNBRsVAJ",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06004005",
"articleId": "12OmNz61cYQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icis/2017/5507/0/07960004",
"title": "Managing personal health records using meta-data and cloud storage",
"doi": null,
"abstractUrl": "/proceedings-article/icis/2017/07960004/12OmNARAngK",
"parentPublication": {
"id": "proceedings/icis/2017/5507/0",
"title": "2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/etelemed/2010/3950/0/3950a100",
"title": "Exploiting Personal Health Records in Automating Information Therapy",
"doi": null,
"abstractUrl": "/proceedings-article/etelemed/2010/3950a100/12OmNBNM8Ya",
"parentPublication": {
"id": "proceedings/etelemed/2010/3950/0",
"title": "eHealth, Telemedicine, and Social Medicine, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asonam/2016/2846/0/07752367",
"title": "A Personal Health Recommender System incorporating personal health records, modular ontologies, and crowd-sourced data",
"doi": null,
"abstractUrl": "/proceedings-article/asonam/2016/07752367/12OmNCfSqNB",
"parentPublication": {
"id": "proceedings/asonam/2016/2846/0",
"title": "2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aina/2010/4018/0/4018b012",
"title": "HealthPass: Fine-Grained Access Control to Portable Personal Health Records",
"doi": null,
"abstractUrl": "/proceedings-article/aina/2010/4018b012/12OmNvnOwwa",
"parentPublication": {
"id": "proceedings/aina/2010/4018/0",
"title": "2010 24th IEEE International Conference on Advanced Information Networking and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itme/2015/8302/0/8302a678",
"title": "The Problems of Information Security of Electronic Personal Health Data",
"doi": null,
"abstractUrl": "/proceedings-article/itme/2015/8302a678/12OmNx9nGLU",
"parentPublication": {
"id": "proceedings/itme/2015/8302/0",
"title": "2015 7th International Conference on Information Technology in Medicine and Education (ITME)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icedeg/2015/8910/0/07114460",
"title": "Security and privacy legislation guidelines for developing personal health records",
"doi": null,
"abstractUrl": "/proceedings-article/icedeg/2015/07114460/12OmNzayNFO",
"parentPublication": {
"id": "proceedings/icedeg/2015/8910/0",
"title": "2015 Second International Conference on eDemocracy & eGovernment (ICEDEG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/asonam/2012/4799/0/4799a815",
"title": "Security Standards for Electronic Health Records",
"doi": null,
"abstractUrl": "/proceedings-article/asonam/2012/4799a815/12OmNzzxuuf",
"parentPublication": {
"id": "proceedings/asonam/2012/4799/0",
"title": "2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/co/2015/02/mco2015020024",
"title": "Ensuring Privacy in a Personal Health Record System",
"doi": null,
"abstractUrl": "/magazine/co/2015/02/mco2015020024/13rRUxBrGba",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/co/2012/11/mco2012110027",
"title": "Personal Health Records: New Means to Safely Handle Health Data?",
"doi": null,
"abstractUrl": "/magazine/co/2012/11/mco2012110027/13rRUyoPSSx",
"parentPublication": {
"id": "mags/co",
"title": "Computer",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/snpd/2019/1651/0/08935646",
"title": "Connecting Personal Health Records Together with EHR Using Tangle",
"doi": null,
"abstractUrl": "/proceedings-article/snpd/2019/08935646/1fTheTBuO2Y",
"parentPublication": {
"id": "proceedings/snpd/2019/1651/0",
"title": "2019 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzBOibV",
"title": "1983 The Seventh Annual Symposium on Computer Applications in Medical Care",
"acronym": "scamc",
"groupId": "1000122",
"volume": "0",
"displayVolume": "0",
"year": "1983",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNzX6cgy",
"doi": "10.1109/SCAMC.1983.764817",
"title": "Using experience to improve clinical decision making",
"normalizedTitle": "Using experience to improve clinical decision making",
"abstract": "Patients with chronic illnesses, such as coronary artery disease, have long periods of time between their disease onset, intervention, and eventual outcome. The physician's inability to couple long term outcomes to the process of patient care confuses the evaluation of therapeutic options and testing procedures. At the Duke University Medical Center, the computer has been used to capture the experience of patients with coronary artery disease and establish the feedback loop necessary for using experience to improve clinical decision making. Methods currently being used for quantitating the diagnostic and prognostic information added by a noninvasive test for an individual patient suspected of having coronary artery disease are described.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Patients with chronic illnesses, such as coronary artery disease, have long periods of time between their disease onset, intervention, and eventual outcome. The physician's inability to couple long term outcomes to the process of patient care confuses the evaluation of therapeutic options and testing procedures. At the Duke University Medical Center, the computer has been used to capture the experience of patients with coronary artery disease and establish the feedback loop necessary for using experience to improve clinical decision making. Methods currently being used for quantitating the diagnostic and prognostic information added by a noninvasive test for an individual patient suspected of having coronary artery disease are described.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Patients with chronic illnesses, such as coronary artery disease, have long periods of time between their disease onset, intervention, and eventual outcome. The physician's inability to couple long term outcomes to the process of patient care confuses the evaluation of therapeutic options and testing procedures. At the Duke University Medical Center, the computer has been used to capture the experience of patients with coronary artery disease and establish the feedback loop necessary for using experience to improve clinical decision making. Methods currently being used for quantitating the diagnostic and prognostic information added by a noninvasive test for an individual patient suspected of having coronary artery disease are described.",
"fno": "00764817",
"keywords": [
"Decision Making",
"Testing",
"Coronary Arteriosclerosis",
"Medical Diagnostic Imaging",
"Feedback Loop",
"Medical Treatment",
"Cardiology",
"Diseases",
"Management Training",
"Medical Tests"
],
"authors": [
{
"affiliation": "Duke University Medical Center, Durham, North Carolina",
"fullName": "D.B. Pryor",
"givenName": "D.B.",
"surname": "Pryor",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "F.E. Harrell",
"givenName": "F.E.",
"surname": "Harrell",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "K.L. Lee",
"givenName": "K.L.",
"surname": "Lee",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "R.M. Califf",
"givenName": "R.M.",
"surname": "Califf",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "R.A. Rosati",
"givenName": "R.A.",
"surname": "Rosati",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "scamc",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "1983-01-01T00:00:00",
"pubType": "proceedings",
"pages": "936,937,938,939",
"year": "1983",
"issn": null,
"isbn": null,
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "00764816",
"articleId": "12OmNx8OuuD",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "00764818",
"articleId": "12OmNwp74zn",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cic/1989/2114/0/00130592",
"title": "Global and regional ejection fraction changes with CABG evaluated by stress radionuclide angiography",
"doi": null,
"abstractUrl": "/proceedings-article/cic/1989/00130592/12OmNAXPxYO",
"parentPublication": {
"id": "proceedings/cic/1989/2114/0",
"title": "Proceedings Computers in Cardiology",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bibe/2007/1509/0/04375574",
"title": "Calcium De-blooming in Coronary CT Image",
"doi": null,
"abstractUrl": "/proceedings-article/bibe/2007/04375574/12OmNBEGYIh",
"parentPublication": {
"id": "proceedings/bibe/2007/1509/0",
"title": "7th IEEE International Conference on Bioinformatics and Bioengineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/esciencew/2010/4295/0/4295a039",
"title": "Haemodynamic Effect of Coronary Angulations on Subsequent Development of Coronary Artery Disease: A Preliminary Study",
"doi": null,
"abstractUrl": "/proceedings-article/esciencew/2010/4295a039/12OmNCctfdQ",
"parentPublication": {
"id": "proceedings/esciencew/2010/4295/0",
"title": "2010 Sixth IEEE International Conference on e-Science Workshops",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cbmsys/1989/1960/0/00047351",
"title": "Detection of ischemic responses during treadmill exercise by computer-aided impedance cardiography",
"doi": null,
"abstractUrl": "/proceedings-article/cbmsys/1989/00047351/12OmNwErpsS",
"parentPublication": {
"id": "proceedings/cbmsys/1989/1960/0",
"title": "[1989] Proceedings. Second Annual IEEE Symposium on Computer-based Medical Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cic/1989/2114/0/00130473",
"title": "Neural networks in detection of coronary artery disease",
"doi": null,
"abstractUrl": "/proceedings-article/cic/1989/00130473/12OmNyz5JX8",
"parentPublication": {
"id": "proceedings/cic/1989/2114/0",
"title": "Proceedings Computers in Cardiology",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/etd/1995/7085/0/00403483",
"title": "A comparative study of artificial intelligent techniques in the detection of coronary artery disease",
"doi": null,
"abstractUrl": "/proceedings-article/etd/1995/00403483/12OmNzdoMBm",
"parentPublication": {
"id": "proceedings/etd/1995/7085/0",
"title": "Proceedings Electronic Technology Directions to the Year 2000",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/synasc/2008/3523/0/3523a243",
"title": "Automatic Assessment of Cardiac Artery Disease by Using DCAD Module",
"doi": null,
"abstractUrl": "/proceedings-article/synasc/2008/3523a243/12OmNzn38Sl",
"parentPublication": {
"id": "proceedings/synasc/2008/3523/0",
"title": "2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2007/06/v1632",
"title": "CoViCAD: Comprehensive Visualization of Coronary Artery Disease",
"doi": null,
"abstractUrl": "/journal/tg/2007/06/v1632/13rRUxBa5xa",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2008/06/ttg2008061595",
"title": "Visualization of Myocardial Perfusion Derived from Coronary Anatomy",
"doi": null,
"abstractUrl": "/journal/tg/2008/06/ttg2008061595/13rRUxOdD8d",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpr/2021/8808/0/09412674",
"title": "Prediction of Obstructive Coronary Artery Disease from Myocardial Perfusion Scintigraphy using Deep Neural Networks",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2021/09412674/1tmhT7OZSPS",
"parentPublication": {
"id": "proceedings/icpr/2021/8808/0",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNC1oT6m",
"title": "Information Technology: New Generations, Third International Conference on",
"acronym": "itng",
"groupId": "1001685",
"volume": "0",
"displayVolume": "0",
"year": "2012",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNy1SFLB",
"doi": "10.1109/ITNG.2012.69",
"title": "An Exploratory Study of the Users' Behavior on Social Network Sites",
"normalizedTitle": "An Exploratory Study of the Users' Behavior on Social Network Sites",
"abstract": "This study makes use of Google Analytics data from four social network sites under web 2.0 setting to analyze their users' behavior. Several statistical techniques are used to analyze the data based on the measures across the four companies with seven cases. Some interesting findings indicate that certain patterns emerge according to the characteristics of the web services. Managerial implications are discussed along with suggestions for future research.",
"abstracts": [
{
"abstractType": "Regular",
"content": "This study makes use of Google Analytics data from four social network sites under web 2.0 setting to analyze their users' behavior. Several statistical techniques are used to analyze the data based on the measures across the four companies with seven cases. Some interesting findings indicate that certain patterns emerge according to the characteristics of the web services. Managerial implications are discussed along with suggestions for future research.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "This study makes use of Google Analytics data from four social network sites under web 2.0 setting to analyze their users' behavior. Several statistical techniques are used to analyze the data based on the measures across the four companies with seven cases. Some interesting findings indicate that certain patterns emerge according to the characteristics of the web services. Managerial implications are discussed along with suggestions for future research.",
"fno": "4654a848",
"keywords": [
"Social Network Site",
"Google Analytics",
"Statistical Analysis"
],
"authors": [
{
"affiliation": null,
"fullName": "Shwu-Min Horng",
"givenName": "Shwu-Min",
"surname": "Horng",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "itng",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2012-04-01T00:00:00",
"pubType": "proceedings",
"pages": "848-849",
"year": "2012",
"issn": null,
"isbn": "978-0-7695-4654-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "4654a846",
"articleId": "12OmNBOCWaT",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "4654a850",
"articleId": "12OmNCdBDFg",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/dasc/2009/3929/0/3929a648",
"title": "An Analysis of Security in Social Networks",
"doi": null,
"abstractUrl": "/proceedings-article/dasc/2009/3929a648/12OmNAYXWBh",
"parentPublication": {
"id": "proceedings/dasc/2009/3929/0",
"title": "Dependable, Autonomic and Secure Computing, IEEE International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apweb/2010/4012/0/4012a392",
"title": "A Metric for Measuring Members' Contribution to Information Propagation in Social Network Sites",
"doi": null,
"abstractUrl": "/proceedings-article/apweb/2010/4012a392/12OmNAle6JF",
"parentPublication": {
"id": "proceedings/apweb/2010/4012/0",
"title": "Conference, International Asia-Pacific Web",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsea/2009/3777/0/3777a229",
"title": "An Anonymous Social Network Site to Share Pictures",
"doi": null,
"abstractUrl": "/proceedings-article/icsea/2009/3777a229/12OmNAnuTD8",
"parentPublication": {
"id": "proceedings/icsea/2009/3777/0",
"title": "Software Engineering Advances, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itng/2010/3984/0/3984a454",
"title": "Analysis of Users' Behavior on Web 2.0 Social Network Sites: An Empirical Study",
"doi": null,
"abstractUrl": "/proceedings-article/itng/2010/3984a454/12OmNC2xhDa",
"parentPublication": {
"id": "proceedings/itng/2010/3984/0",
"title": "Information Technology: New Generations, Third International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iciw/2009/3613/0/3613a267",
"title": "UPP: User Privacy Policy for Social Networking Sites",
"doi": null,
"abstractUrl": "/proceedings-article/iciw/2009/3613a267/12OmNqJq4rE",
"parentPublication": {
"id": "proceedings/iciw/2009/3613/0",
"title": "Internet and Web Applications and Services, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2014/7978/0/7978a172",
"title": "Conversation Analysis on Social Networking Sites",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2014/7978a172/12OmNvjgWIb",
"parentPublication": {
"id": "proceedings/sitis/2014/7978/0",
"title": "2014 Tenth International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cse/2009/3823/4/3823e985",
"title": "Visible Flows: Contextual Integrity and the Design of Privacy Mechanisms on Social Network Sites",
"doi": null,
"abstractUrl": "/proceedings-article/cse/2009/3823e985/12OmNvpew7H",
"parentPublication": {
"id": "proceedings/cse/2009/3823/2",
"title": "2009 International Conference on Computational Science and Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/smap/2011/4524/0/4524a051",
"title": "Social Networking and On-Line Communities: Classification and Research Trends",
"doi": null,
"abstractUrl": "/proceedings-article/smap/2011/4524a051/12OmNwp74v0",
"parentPublication": {
"id": "proceedings/smap/2011/4524/0",
"title": "Semantic Media Adaptation and Personalization, International Workshop on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itng/2009/3596/0/3596a934",
"title": "The Behavior and Preferences of Users on Web 2.0 Social Network Sites: An Empirical Study",
"doi": null,
"abstractUrl": "/proceedings-article/itng/2009/3596a934/12OmNxuXcwL",
"parentPublication": {
"id": "proceedings/itng/2009/3596/0",
"title": "Information Technology: New Generations, Third International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdmw/2018/9288/0/928800a183",
"title": "Cross-Platform Modeling of Users' Behavior on Social Media",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2018/928800a183/18jXFqVdBEk",
"parentPublication": {
"id": "proceedings/icdmw/2018/9288/0",
"title": "2018 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "17D45VtKirC",
"title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"acronym": "vast",
"groupId": "1001630",
"volume": "0",
"displayVolume": "0",
"year": "2017",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45WIXbRE",
"doi": "10.1109/VAST.2017.8585620",
"title": "ClockPetals: Interactive Sequential Analysis of Traffic Patterns VAST Challenge MC1 Award: Multi-Challenge Award for Aesthetic Design",
"normalizedTitle": "ClockPetals: Interactive Sequential Analysis of Traffic Patterns VAST Challenge MC1 Award: Multi-Challenge Award for Aesthetic Design",
"abstract": "The visual analytics system ClockPetals aims to reveal the spatio-temporal and sequential patterns of a large traffic record dataset. The system features appealing interactive web graphics that fast illustrate traffic patterns and allow users to locate unusual, anomalous traffic events from multiple demographical and temporal dimensions. ClockPetals also provides the interactive exploration of different vehicle batches via common sequential characteristic clustering. This paper presents the system's architecture and the benefits of its adoption.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The visual analytics system ClockPetals aims to reveal the spatio-temporal and sequential patterns of a large traffic record dataset. The system features appealing interactive web graphics that fast illustrate traffic patterns and allow users to locate unusual, anomalous traffic events from multiple demographical and temporal dimensions. ClockPetals also provides the interactive exploration of different vehicle batches via common sequential characteristic clustering. This paper presents the system's architecture and the benefits of its adoption.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The visual analytics system ClockPetals aims to reveal the spatio-temporal and sequential patterns of a large traffic record dataset. The system features appealing interactive web graphics that fast illustrate traffic patterns and allow users to locate unusual, anomalous traffic events from multiple demographical and temporal dimensions. ClockPetals also provides the interactive exploration of different vehicle batches via common sequential characteristic clustering. This paper presents the system's architecture and the benefits of its adoption.",
"fno": "08585620",
"keywords": [
"Data Analysis",
"Data Visualisation",
"Interactive Systems",
"Internet",
"Pattern Clustering",
"Road Traffic",
"Spatio Temporal",
"Sequential Patterns",
"Traffic Record Dataset",
"Interactive Web Graphics",
"Traffic Patterns",
"Anomalous Traffic Events",
"Multiple Demographical Dimensions",
"Temporal Dimensions",
"Interactive Exploration",
"Common Sequential Characteristic Clustering",
"Interactive Sequential Analysis",
"VAST Challenge MC 1 Award",
"Aesthetic Design",
"Visual Analytics System",
"Clock Petals",
"Pins",
"Image Color Analysis",
"Visual Analytics",
"Roads",
"Computer Architecture",
"Clocks",
"Human Centered Computing X 2014 Visual Analytics Information Visualization User Interface Design",
"Information Systems X 2014 Spatial Temporal Systems"
],
"authors": [
{
"affiliation": "Department of Computer Graphics Technology, Purdue University, West Lafayette, IN",
"fullName": "Zheng Zhou",
"givenName": "Zheng",
"surname": "Zhou",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Graphics Technology, Purdue University, West Lafayette, IN",
"fullName": "Sijin Wang",
"givenName": "Sijin",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Graphics Technology, Purdue University, West Lafayette, IN",
"fullName": "Wenjie Wu",
"givenName": "Wenjie",
"surname": "Wu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Industrial and Interaction Design, Purdue University, West Lafayette, IN, USA",
"fullName": "Aijun Huang",
"givenName": "Aijun",
"surname": "Huang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Schoool of Mechanical Engineering, Southeast University, China",
"fullName": "Yafeng Niu",
"givenName": "Yafeng",
"surname": "Niu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Graphics Technology, Purdue University, West Lafayette, IN",
"fullName": "Hui Tang",
"givenName": "Hui",
"surname": "Tang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Graphics Technology, Purdue University, West Lafayette, IN",
"fullName": "Yingjie Victor Chen",
"givenName": "Yingjie Victor",
"surname": "Chen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Industrial and Interaction Design, Purdue University, West Lafayette, IN, USA",
"fullName": "Zhenyu Cheryl Qian",
"givenName": "Zhenyu Cheryl",
"surname": "Qian",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vast",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2017-10-01T00:00:00",
"pubType": "proceedings",
"pages": "179-180",
"year": "2017",
"issn": null,
"isbn": "978-1-5386-3163-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08585503",
"articleId": "17D45WHONqn",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08585631",
"articleId": "17D45WYQJ6K",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/pacificvis/2011/935/0/05742386",
"title": "TripVista: Triple Perspective Visual Trajectory Analytics and its application on microscopic traffic data at a road intersection",
"doi": null,
"abstractUrl": "/proceedings-article/pacificvis/2011/05742386/12OmNrHB1QE",
"parentPublication": {
"id": "proceedings/pacificvis/2011/935/0",
"title": "2011 IEEE Pacific Visualization Symposium (PacificVis)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2012/4752/0/06400524",
"title": "M-Sieve: A visualisation tool for supporting network security analysts: VAST 2012 Mini Challenge 1 award: “Subject matter expert's award”",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2012/06400524/12OmNzE54Hu",
"parentPublication": {
"id": "proceedings/vast/2012/4752/0",
"title": "2012 IEEE Conference on Visual Analytics Science and Technology (VAST 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2017/3163/0/08585564",
"title": "Interactive Visual Analytics Application for Spatiotemporal Movement Data VAST Challenge 2017 Mini-Challenge 1: Award for Actionable and Detailed Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2017/08585564/17D45VsBU7R",
"parentPublication": {
"id": "proceedings/vast/2017/3163/0",
"title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2017/3163/0/08585677",
"title": "VAST Mini-Challenge 1",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2017/08585677/17D45WK5Aox",
"parentPublication": {
"id": "proceedings/vast/2017/3163/0",
"title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2017/3163/0/08585631",
"title": "WindNebula: Vectorial-Temporal Analysis for Environmental Assessment : VAST Challenge MC2 Award: Multi-challenge Award for Aesthetic Design",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2017/08585631/17D45WYQJ6K",
"parentPublication": {
"id": "proceedings/vast/2017/3163/0",
"title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2017/3163/0/08585729",
"title": "Interactive Visual Analysis of Traffic Patterns: Ecological Impact within a Nature Preserve (VAST Challenge 2017)",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2017/08585729/17D45WYQJa8",
"parentPublication": {
"id": "proceedings/vast/2017/3163/0",
"title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2017/3163/0/08585588",
"title": "Visual Analytic Design for Detecting Airborne Pollution Sources VAST Challenge 2017 Award: Comprehensive Mini-Challenge 2 Answer",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2017/08585588/17D45WaTkjp",
"parentPublication": {
"id": "proceedings/vast/2017/3163/0",
"title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2017/3163/0/08585461",
"title": "VAST Challenge 2017: Mini-challenge 1",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2017/08585461/17D45XfSET1",
"parentPublication": {
"id": "proceedings/vast/2017/3163/0",
"title": "2017 IEEE Conference on Visual Analytics Science and Technology (VAST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2010/9488/0/05652661",
"title": "VACCINATED — Visual analytics for characterizing a pandemic spread VAST 2010 Mini Challenge 2 award: Support for future detection",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2010/05652661/1iCAmf3w4BG",
"parentPublication": {
"id": "proceedings/vast/2010/9488/0",
"title": "2010 IEEE Symposium on Visual Analytics Science and Technology",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vast/2010/9488/0/05649054",
"title": "VAST 2010 Challenge: Arms dealings and pandemics",
"doi": null,
"abstractUrl": "/proceedings-article/vast/2010/05649054/1iCAmnTV5Uk",
"parentPublication": {
"id": "proceedings/vast/2010/9488/0",
"title": "2010 IEEE Symposium on Visual Analytics Science and Technology",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNwMXnv0",
"title": "2014 IEEE Virtual Reality (VR)",
"acronym": "vr",
"groupId": "1000791",
"volume": "0",
"displayVolume": "0",
"year": "2014",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwGZNNk",
"doi": "10.1109/VR.2014.6802108",
"title": "A demonstration of tablet-based interaction panels for immersive environments",
"normalizedTitle": "A demonstration of tablet-based interaction panels for immersive environments",
"abstract": "Our demo deals with the need in immersive virtual reality for devices that support expressive and adaptive interaction in a low-cost, eyes-free manner. Leveraging rapid prototyping techniques for fabrication, we have developed a variety of panels that can be overlaid on multi-touch tablets and smartphones. The panels are coupled with an app running on the multi-touch device that exchanges commands and state information over a wireless network with the virtual reality application. Sculpted features of the panels provide tactile disambiguation of control widgets and an onscreen heads-up display provides interaction state information. A variety of interaction mappings can be provided through software to support several classes of interaction techniques in virtual environments. We foresee additional uses for applications where eyes-free use and adaptable interaction interfaces can be beneficial.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Our demo deals with the need in immersive virtual reality for devices that support expressive and adaptive interaction in a low-cost, eyes-free manner. Leveraging rapid prototyping techniques for fabrication, we have developed a variety of panels that can be overlaid on multi-touch tablets and smartphones. The panels are coupled with an app running on the multi-touch device that exchanges commands and state information over a wireless network with the virtual reality application. Sculpted features of the panels provide tactile disambiguation of control widgets and an onscreen heads-up display provides interaction state information. A variety of interaction mappings can be provided through software to support several classes of interaction techniques in virtual environments. We foresee additional uses for applications where eyes-free use and adaptable interaction interfaces can be beneficial.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Our demo deals with the need in immersive virtual reality for devices that support expressive and adaptive interaction in a low-cost, eyes-free manner. Leveraging rapid prototyping techniques for fabrication, we have developed a variety of panels that can be overlaid on multi-touch tablets and smartphones. The panels are coupled with an app running on the multi-touch device that exchanges commands and state information over a wireless network with the virtual reality application. Sculpted features of the panels provide tactile disambiguation of control widgets and an onscreen heads-up display provides interaction state information. A variety of interaction mappings can be provided through software to support several classes of interaction techniques in virtual environments. We foresee additional uses for applications where eyes-free use and adaptable interaction interfaces can be beneficial.",
"fno": "06802108",
"keywords": [
"Virtual Reality",
"Three Dimensional Displays",
"Software",
"Educational Institutions",
"Electronic Mail",
"Legged Locomotion",
"Games",
"H 5 2 Information Interfaces And Presentation User Interfaces Input Devices And Strategies",
"H 5 1 Information Interfaces And Presentation Multimedia Information Systems Artificial Augmented And Virtual Realities"
],
"authors": [
{
"affiliation": "USC Institute for Creative Technologies",
"fullName": "David M. Krum",
"givenName": "David M.",
"surname": "Krum",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "USC Institute for Creative Technologies",
"fullName": "Thai Phan",
"givenName": "Thai",
"surname": "Phan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Clemson University",
"fullName": "Lauren Cairco Dukes",
"givenName": "Lauren Cairco",
"surname": "Dukes",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Continuum, Analytics",
"fullName": "Peter Wang",
"givenName": "Peter",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "USC Institute for Creative Technologies",
"fullName": "Mark Bolas",
"givenName": "Mark",
"surname": "Bolas",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2014-03-01T00:00:00",
"pubType": "proceedings",
"pages": "175-176",
"year": "2014",
"issn": null,
"isbn": "978-1-4799-2871-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06802107",
"articleId": "12OmNz6iO9f",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06802109",
"articleId": "12OmNxWcHhQ",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/vr/2009/3943/0/04811045",
"title": "iPhone/iPod Touch as Input Devices for Navigation in Immersive Virtual Environments",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2009/04811045/12OmNqGitWe",
"parentPublication": {
"id": "proceedings/vr/2009/3943/0",
"title": "2009 IEEE Virtual Reality Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2014/2871/0/06802066",
"title": "Tablet-based interaction panels for immersive environments",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2014/06802066/12OmNqN6R3O",
"parentPublication": {
"id": "proceedings/vr/2014/2871/0",
"title": "2014 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wevr/2017/3881/0/07957708",
"title": "Utilizing immersive virtual reality in everydaywork",
"doi": null,
"abstractUrl": "/proceedings-article/wevr/2017/07957708/12OmNyQ7FH1",
"parentPublication": {
"id": "proceedings/wevr/2017/3881/0",
"title": "2017 IEEE 3rd Workshop on Everyday Virtual Reality (WEVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/grc/2011/0372/0/06122623",
"title": "VISIE: A spatially immersive interaction environment using real-time human measurement",
"doi": null,
"abstractUrl": "/proceedings-article/grc/2011/06122623/12OmNyen1sx",
"parentPublication": {
"id": "proceedings/grc/2011/0372/0",
"title": "2011 IEEE International Conference on Granular Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2018/3365/0/08446319",
"title": "A Demonstration of FaceDisplay: Asymetric Multi-User Interaction for Mobile VR",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2018/08446319/13bd1AITn9X",
"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/2019/1377/0/08798255",
"title": "HapticSphere: Physical Support To Enable Precision Touch Interaction in Mobile Mixed-Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798255/1cJ0Uje3t8Q",
"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/2019/1377/0/08798129",
"title": "VRLearner: A Virtual Reality Based Assessment Tool in Higher Education",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2019/08798129/1cJ1bHDzNNC",
"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/dsc/2019/4528/0/09069366",
"title": "Grey Island: Immersive tangible interaction through augmented reality",
"doi": null,
"abstractUrl": "/proceedings-article/dsc/2019/09069366/1jdCYiSUwBG",
"parentPublication": {
"id": "proceedings/dsc/2019/4528/0",
"title": "2019 IEEE Fourth International Conference on Data Science in Cyberspace (DSC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aivr/2020/7463/0/746300a209",
"title": "A Virtual Reality Framework for Human-Virtual Crowd Interaction Studies",
"doi": null,
"abstractUrl": "/proceedings-article/aivr/2020/746300a209/1qpzBFKHFpC",
"parentPublication": {
"id": "proceedings/aivr/2020/7463/0",
"title": "2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2021/4057/0/405700a395",
"title": "Is Walking Necessary for Effective Locomotion and Interaction in VR?",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2021/405700a395/1tnXRY815xS",
"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"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "17D45VtKisi",
"title": "2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)",
"acronym": "ucc-companion",
"groupId": "1829804",
"volume": "0",
"displayVolume": "0",
"year": "2018",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45WB0qbv",
"doi": "10.1109/UCC-Companion.2018.00080",
"title": "A Review of Applications of Extended Reality in the Construction Domain",
"normalizedTitle": "A Review of Applications of Extended Reality in the Construction Domain",
"abstract": "this paper uses Extended Reality (XR) as an umbrella to encapsulate Virtual Reality, Augmented Reality, and everything between real and virtual environment. XR has attracted a wide range of audience from different disciplines in recent years. The advancement of XR is commonly led by technology developers such as computer science and computer engineering. However, studies of the XR applications are increasing dramatically in many fields. This research investigated the latest XR applications in the construction domain. Major research topics have been identified and future development of the applications are suggested. The outcome of this research could assist researchers and practitioners to identify the frontier of latest XR technologies and research direction.",
"abstracts": [
{
"abstractType": "Regular",
"content": "this paper uses Extended Reality (XR) as an umbrella to encapsulate Virtual Reality, Augmented Reality, and everything between real and virtual environment. XR has attracted a wide range of audience from different disciplines in recent years. The advancement of XR is commonly led by technology developers such as computer science and computer engineering. However, studies of the XR applications are increasing dramatically in many fields. This research investigated the latest XR applications in the construction domain. Major research topics have been identified and future development of the applications are suggested. The outcome of this research could assist researchers and practitioners to identify the frontier of latest XR technologies and research direction.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "this paper uses Extended Reality (XR) as an umbrella to encapsulate Virtual Reality, Augmented Reality, and everything between real and virtual environment. XR has attracted a wide range of audience from different disciplines in recent years. The advancement of XR is commonly led by technology developers such as computer science and computer engineering. However, studies of the XR applications are increasing dramatically in many fields. This research investigated the latest XR applications in the construction domain. Major research topics have been identified and future development of the applications are suggested. The outcome of this research could assist researchers and practitioners to identify the frontier of latest XR technologies and research direction.",
"fno": "035900a353",
"keywords": [
"X Reality",
"Extended Reality",
"Two Dimensional Displays",
"Solid Modeling",
"Extended Reality",
"Built Environment",
"Virtual Reality",
"Augmented Reality",
"Construction"
],
"authors": [
{
"affiliation": null,
"fullName": "Mustafa Al-Adhami",
"givenName": "Mustafa",
"surname": "Al-Adhami",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Ling Ma",
"givenName": "Ling",
"surname": "Ma",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Song Wu",
"givenName": "Song",
"surname": "Wu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ucc-companion",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2018-12-01T00:00:00",
"pubType": "proceedings",
"pages": "353-358",
"year": "2018",
"issn": null,
"isbn": "978-1-7281-0359-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08605803",
"articleId": "17D45WB0qcf",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "035900a359",
"articleId": "17QjJchx62B",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/iiswc/2021/4173/0/417300a024",
"title": "ILLIXR: Enabling End-to-End Extended Reality Research",
"doi": null,
"abstractUrl": "/proceedings-article/iiswc/2021/417300a024/1A8gldXRikU",
"parentPublication": {
"id": "proceedings/iiswc/2021/4173/0",
"title": "2021 IEEE International Symposium on Workload Characterization (IISWC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apsec/2021/3784/0/378400a572",
"title": "Topic Trends in Issue Tracking System of Extended Reality Frameworks",
"doi": null,
"abstractUrl": "/proceedings-article/apsec/2021/378400a572/1B4m7XRlTcQ",
"parentPublication": {
"id": "proceedings/apsec/2021/3784/0",
"title": "2021 28th Asia-Pacific Software Engineering Conference (APSEC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mi/2022/04/09741292",
"title": "ILLIXR: An Open Testbed to Enable Extended Reality Systems Research",
"doi": null,
"abstractUrl": "/magazine/mi/2022/04/09741292/1C0jifhs3DO",
"parentPublication": {
"id": "mags/mi",
"title": "IEEE Micro",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a652",
"title": "Role of Dynamic Affordance and Cognitive Load in the Design of Extended Reality based Simulation Environments for Surgical Contexts",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a652/1CJdQCrNADm",
"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/5555/01/09772329",
"title": "Using Extended Reality in Flight Simulators: A Literature Review",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09772329/1DgjDn5nymI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2022/6814/0/681400a195",
"title": "Using Extended Reality to Teach Protection of Civilians in Higher Military Education",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2022/681400a195/1I6RMFjiO0U",
"parentPublication": {
"id": "proceedings/cw/2022/6814/0",
"title": "2022 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a322",
"title": "Extended Reality Training for Business and Education: The New Generation of Learning Experiences",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a322/1J7W77jxOlq",
"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/2022/5365/0/536500a254",
"title": "Generative Research in the Context of Academic Extended Reality Research",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a254/1J7WcCweXhC",
"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/2021/1298/0/129800a476",
"title": "Designing Virtual Pedagogical Agents and Mentors for Extended Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a476/1yeQC8OgSoU",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a018",
"title": "Accessible Tangible User Interfaces in eXtended Reality Experiences for Cultural Heritage",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a018/1yeQGLRgXHW",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1jIxhEnA8IE",
"title": "2020 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)",
"acronym": "vrw",
"groupId": "1836626",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1jIxj9oCqpq",
"doi": "10.1109/VRW50115.2020.00292",
"title": "NIDIT: Workshop on Novel Input Devices and Interaction Techniques",
"normalizedTitle": "NIDIT: Workshop on Novel Input Devices and Interaction Techniques",
"abstract": "Virtual reality has finally become a mainstream technology. Recent advances in commercial VR hardware have led to high-resolution, ergonomic, — and critically — low cost head-mounted displays. Advances in commercial input devices and interaction techniques have arguably not kept pace with advances in displays. For instance, most HMDs include a tracked input device: “wands” that are not dissimilar to the earliest examples of 3D controllers used in the VR systems of the 1980s. Interaction in commercial VR systems has similarly lagged; despite many advances in 3D interaction in the past three decades of VR research, interaction in commercial systems largely relies on classical techniques like the virtual hand, or raycasting. This full-day workshop will bring together researchers and industry practitioners to discuss and experience the future of input devices for VR, AR, and 3D User Interfaces, and help chart a course for the future of 3D interaction techniques. In addition to a presentation at the workshop, authors of all accepted submissions will be strongly encouraged to demonstrate their novel input device and interaction techniques in an interactive demo format following presentations.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Virtual reality has finally become a mainstream technology. Recent advances in commercial VR hardware have led to high-resolution, ergonomic, — and critically — low cost head-mounted displays. Advances in commercial input devices and interaction techniques have arguably not kept pace with advances in displays. For instance, most HMDs include a tracked input device: “wands” that are not dissimilar to the earliest examples of 3D controllers used in the VR systems of the 1980s. Interaction in commercial VR systems has similarly lagged; despite many advances in 3D interaction in the past three decades of VR research, interaction in commercial systems largely relies on classical techniques like the virtual hand, or raycasting. This full-day workshop will bring together researchers and industry practitioners to discuss and experience the future of input devices for VR, AR, and 3D User Interfaces, and help chart a course for the future of 3D interaction techniques. In addition to a presentation at the workshop, authors of all accepted submissions will be strongly encouraged to demonstrate their novel input device and interaction techniques in an interactive demo format following presentations.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Virtual reality has finally become a mainstream technology. Recent advances in commercial VR hardware have led to high-resolution, ergonomic, — and critically — low cost head-mounted displays. Advances in commercial input devices and interaction techniques have arguably not kept pace with advances in displays. For instance, most HMDs include a tracked input device: “wands” that are not dissimilar to the earliest examples of 3D controllers used in the VR systems of the 1980s. Interaction in commercial VR systems has similarly lagged; despite many advances in 3D interaction in the past three decades of VR research, interaction in commercial systems largely relies on classical techniques like the virtual hand, or raycasting. This full-day workshop will bring together researchers and industry practitioners to discuss and experience the future of input devices for VR, AR, and 3D User Interfaces, and help chart a course for the future of 3D interaction techniques. In addition to a presentation at the workshop, authors of all accepted submissions will be strongly encouraged to demonstrate their novel input device and interaction techniques in an interactive demo format following presentations.",
"fno": "09090436",
"keywords": [
"Conferences",
"X Reality",
"Virtual Reality",
"Three Dimensional Displays",
"Training",
"Industries",
"Animation"
],
"authors": [
{
"affiliation": "Carleton University,Canada",
"fullName": "Robert J. Teather",
"givenName": "Robert J.",
"surname": "Teather",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Colorado State University,USA",
"fullName": "Francisco R. Ortega",
"givenName": "Francisco R.",
"surname": "Ortega",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "KU Leuven,Belgium",
"fullName": "Adalberto L. Simeone",
"givenName": "Adalberto L.",
"surname": "Simeone",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "vrw",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-03-01T00:00:00",
"pubType": "proceedings",
"pages": "1-4",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-6532-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09090659",
"articleId": "1jIxA7uQ2xq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09090675",
"articleId": "1jIxqoL3kbK",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/isuvr/2017/3091/0/3091a020",
"title": "Visual Representation of Gesture Interaction Feedback in Virtual Reality Games",
"doi": null,
"abstractUrl": "/proceedings-article/isuvr/2017/3091a020/12OmNx5Yviz",
"parentPublication": {
"id": "proceedings/isuvr/2017/3091/0",
"title": "2017 International Symposium on Ubiquitous Virtual Reality (ISUVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/3dui/2006/0225/0/02250111",
"title": "Interaction Techniques for Exploring Historic Sites through Situated Media",
"doi": null,
"abstractUrl": "/proceedings-article/3dui/2006/02250111/12OmNx6g6dA",
"parentPublication": {
"id": "proceedings/3dui/2006/0225/0",
"title": "3D User Interfaces (3DUI'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2022/9617/0/961700a812",
"title": "Tangiball: Foot-Enabled Embodied Tangible Interaction with a Ball in Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2022/961700a812/1CJczvrAl0Y",
"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/vrw/2022/8402/0/840200a674",
"title": "A Comparison of Input Devices for Precise Interaction Tasks in VR-based Surgical Planning and Training",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a674/1CJdE39vY9G",
"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/5555/01/09773967",
"title": "A Review of Interaction Techniques for Immersive Environments",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09773967/1DjDoKqOJz2",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iciscet/2022/6044/0/604400a248",
"title": "Research on the production and application of virtual reality technology based on immersion and interaction in 3D animation scene",
"doi": null,
"abstractUrl": "/proceedings-article/iciscet/2022/604400a248/1HbbRgeLkze",
"parentPublication": {
"id": "proceedings/iciscet/2022/6044/0",
"title": "2022 International Conference on Information System, Computing and Educational Technology (ICISCET)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a085",
"title": "MEinVR: Multimodal Interaction Paradigms in Immersive Exploration",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a085/1J7W98ABKwM",
"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/aivr/2022/5725/0/572500a140",
"title": "Direct Interaction Word-Gesture Text Input in Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/aivr/2022/572500a140/1KmF8k8WXi8",
"parentPublication": {
"id": "proceedings/aivr/2022/5725/0",
"title": "2022 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2023/05/10058530",
"title": "A Lack of Restraint: Comparing Virtual Reality Interaction Techniques for Constrained Transport Seating",
"doi": null,
"abstractUrl": "/journal/tg/2023/05/10058530/1LdkjHapKW4",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvidl/2020/9481/0/948100a592",
"title": "Research on roaming and interaction in VR game based on Unity 3D",
"doi": null,
"abstractUrl": "/proceedings-article/cvidl/2020/948100a592/1pbe56ulRmw",
"parentPublication": {
"id": "proceedings/cvidl/2020/9481/0",
"title": "2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNAWH9tG",
"title": "5th ACIS International Conference on Software Engineering Research, Management & Applications (SERA 2007)",
"acronym": "sera",
"groupId": "1001129",
"volume": "0",
"displayVolume": "0",
"year": "2007",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNqBKTX2",
"doi": "10.1109/SERA.2007.43",
"title": "An Efficient Expression on Cartoon Rendering Scheme in Game Characters",
"normalizedTitle": "An Efficient Expression on Cartoon Rendering Scheme in Game Characters",
"abstract": "The traditional cell-animations are expressed mostly by silhouette edges and inner shadings. Expressing cell-animations by digital techniques is cartoon rendering. Rendering techniques are divided into photorealistic rendering technique and non-photorealistic rendering technique. Cartoon rendering is non-photorealistic rendering technique and used in movies, advertisements and games etc. This paper examines game characters among contents using cartoon renderings. And this paper investigates features and effects of cartoon rendering techniques used in each game. Based on those considerations, this paper proposes new cartoon rendering technique.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The traditional cell-animations are expressed mostly by silhouette edges and inner shadings. Expressing cell-animations by digital techniques is cartoon rendering. Rendering techniques are divided into photorealistic rendering technique and non-photorealistic rendering technique. Cartoon rendering is non-photorealistic rendering technique and used in movies, advertisements and games etc. This paper examines game characters among contents using cartoon renderings. And this paper investigates features and effects of cartoon rendering techniques used in each game. Based on those considerations, this paper proposes new cartoon rendering technique.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The traditional cell-animations are expressed mostly by silhouette edges and inner shadings. Expressing cell-animations by digital techniques is cartoon rendering. Rendering techniques are divided into photorealistic rendering technique and non-photorealistic rendering technique. Cartoon rendering is non-photorealistic rendering technique and used in movies, advertisements and games etc. This paper examines game characters among contents using cartoon renderings. And this paper investigates features and effects of cartoon rendering techniques used in each game. Based on those considerations, this paper proposes new cartoon rendering technique.",
"fno": "28670924",
"keywords": [],
"authors": [
{
"affiliation": "Chonbuk National University, South Korea",
"fullName": "Jong Seo Kim",
"givenName": "Jong Seo",
"surname": "Kim",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Jeonju University, South Korea",
"fullName": "Kang Soo You",
"givenName": "Kang Soo",
"surname": "You",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Chonbuk National University, South Korea",
"fullName": "Hoon Sung Kwak",
"givenName": "Hoon Sung",
"surname": "Kwak",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "sera",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2007-08-01T00:00:00",
"pubType": "proceedings",
"pages": "924-928",
"year": "2007",
"issn": null,
"isbn": "0-7695-2867-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "28670917",
"articleId": "12OmNB7LvCi",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "28670929",
"articleId": "12OmNywfKJd",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/segah/2013/6165/0/06665314",
"title": "Palco: A multisensor realtime 3D cartoon production system",
"doi": null,
"abstractUrl": "/proceedings-article/segah/2013/06665314/12OmNALCNrO",
"parentPublication": {
"id": "proceedings/segah/2013/6165/0",
"title": "2013 IEEE 2nd International Conference on Serious Games and Applications for Health (SeGAH)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pg/2002/1784/0/17840454",
"title": "Cartoon Motion Capture by Shape Matching",
"doi": null,
"abstractUrl": "/proceedings-article/pg/2002/17840454/12OmNC8dgo7",
"parentPublication": {
"id": "proceedings/pg/2002/1784/0",
"title": "Computer Graphics and Applications, Pacific Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isuc/2008/3433/0/3433a199",
"title": "An Extended Non-Photorealistic Rendering Technique for Depicting Motions of Multiple 3D Objects",
"doi": null,
"abstractUrl": "/proceedings-article/isuc/2008/3433a199/12OmNwLOYV3",
"parentPublication": {
"id": "proceedings/isuc/2008/3433/0",
"title": "2008 Second International Symposium on Universal Communication",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icig/2013/5050/0/5050a913",
"title": "Cartoon Rendering Illumination Model Based on Phong",
"doi": null,
"abstractUrl": "/proceedings-article/icig/2013/5050a913/12OmNwoPtun",
"parentPublication": {
"id": "proceedings/icig/2013/5050/0",
"title": "2013 Seventh International Conference on Image and Graphics (ICIG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/haptics/2010/6821/0/05444656",
"title": "Expressive haptic rendering with cartoon-inspired effects",
"doi": null,
"abstractUrl": "/proceedings-article/haptics/2010/05444656/12OmNyNQSNU",
"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/cgi/2003/1946/0/19460276",
"title": "Cartoon Blur: Non-Photorealistic Motion Blur",
"doi": null,
"abstractUrl": "/proceedings-article/cgi/2003/19460276/12OmNzC5SOT",
"parentPublication": {
"id": "proceedings/cgi/2003/1946/0",
"title": "Computer Graphics International Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cgiv/2004/2178/0/21780215",
"title": "Non-Photorealistic Outdoor Scene Rendering: Techniques and Application",
"doi": null,
"abstractUrl": "/proceedings-article/cgiv/2004/21780215/12OmNzZmZtZ",
"parentPublication": {
"id": "proceedings/cgiv/2004/2178/0",
"title": "Proceedings. International Conference on Computer Graphics, Imaging and Visualization, 2004. CGIV 2004.",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09774005",
"title": "Multi-scale Flow-based Occluding Effect and Content Separation for Cartoon Animations",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09774005/1DjDpHtWZfa",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/aiccsa/2022/1008/0/10017484",
"title": "Shapes2Toon: Generating Cartoon Characters from Simple Geometric Shapes",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2022/10017484/1KJxupzPEAM",
"parentPublication": {
"id": "proceedings/aiccsa/2022/1008/0",
"title": "2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wacv/2020/6553/0/09093346",
"title": "Neural Puppet: Generative Layered Cartoon Characters",
"doi": null,
"abstractUrl": "/proceedings-article/wacv/2020/09093346/1jPbkInDnXy",
"parentPublication": {
"id": "proceedings/wacv/2020/6553/0",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNx8Ounz",
"title": "2010 IEEE Haptics Symposium (Formerly known as Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems)",
"acronym": "haptics",
"groupId": "1000312",
"volume": "0",
"displayVolume": "0",
"year": "2010",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNyNQSNU",
"doi": "10.1109/HAPTIC.2010.5444656",
"title": "Expressive haptic rendering with cartoon-inspired effects",
"normalizedTitle": "Expressive haptic rendering with cartoon-inspired effects",
"abstract": "Non-photorealistic rendering (NPR) rejects a rigid adherence to physically accurate creation of visual imagery in favor of expressive styles that can enhance information transfer or create an artistic feeling. This paper considers those goals in the context of haptic rendering. Expressive haptic rendering techniques are developed for cartoon-inspired haptic rendering effects and demonstrated in three classic cartoon scenarios: super-slippery surfaces, exaggerated recoil and vibration upon hitting an object, and falling from a height based on a character's awareness of danger. Subjectively, these effects create increased interest in a scene and can facilitate transfer of artistic goals to a user. The value of expressive haptic rendering derives from this enhanced interaction experience.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Non-photorealistic rendering (NPR) rejects a rigid adherence to physically accurate creation of visual imagery in favor of expressive styles that can enhance information transfer or create an artistic feeling. This paper considers those goals in the context of haptic rendering. Expressive haptic rendering techniques are developed for cartoon-inspired haptic rendering effects and demonstrated in three classic cartoon scenarios: super-slippery surfaces, exaggerated recoil and vibration upon hitting an object, and falling from a height based on a character's awareness of danger. Subjectively, these effects create increased interest in a scene and can facilitate transfer of artistic goals to a user. The value of expressive haptic rendering derives from this enhanced interaction experience.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Non-photorealistic rendering (NPR) rejects a rigid adherence to physically accurate creation of visual imagery in favor of expressive styles that can enhance information transfer or create an artistic feeling. This paper considers those goals in the context of haptic rendering. Expressive haptic rendering techniques are developed for cartoon-inspired haptic rendering effects and demonstrated in three classic cartoon scenarios: super-slippery surfaces, exaggerated recoil and vibration upon hitting an object, and falling from a height based on a character's awareness of danger. Subjectively, these effects create increased interest in a scene and can facilitate transfer of artistic goals to a user. The value of expressive haptic rendering derives from this enhanced interaction experience.",
"fno": "05444656",
"keywords": [
"Electronic Data Interchange",
"Haptic Interfaces",
"Rendering Computer Graphics",
"Cartoon Inspired Effect",
"Visual Imagery",
"Information Transfer",
"Haptic Rendering Techniques",
"Nonphotorealistic Rendering",
"Haptic Interfaces",
"Rendering Computer Graphics",
"Animation",
"Computer Graphics",
"Visual Communication",
"Electronic Mail",
"Filters",
"Mechanical Engineering",
"Physics Computing",
"Vibrations"
],
"authors": [
{
"affiliation": "Department of Mechanical Engineering, University of Utah, USA",
"fullName": "Brian Gleeson",
"givenName": "Brian",
"surname": "Gleeson",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "School of Computing, University of Utah, USA",
"fullName": "David E. Johnson",
"givenName": "David E.",
"surname": "Johnson",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "haptics",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2010-03-01T00:00:00",
"pubType": "proceedings",
"pages": "",
"year": "2010",
"issn": "2324-7347",
"isbn": "978-1-4244-6821-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "05444659",
"articleId": "12OmNAoDhQy",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "05444657",
"articleId": "12OmNBtCCyX",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/cw/2010/4215/0/4215a038",
"title": "Haptic Rendering of Mixed Haptic Effects",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2010/4215a038/12OmNCdk2IT",
"parentPublication": {
"id": "proceedings/cw/2010/4215/0",
"title": "2010 International Conference on Cyberworlds",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"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/icig/2013/5050/0/5050a913",
"title": "Cartoon Rendering Illumination Model Based on Phong",
"doi": null,
"abstractUrl": "/proceedings-article/icig/2013/5050a913/12OmNwoPtun",
"parentPublication": {
"id": "proceedings/icig/2013/5050/0",
"title": "2013 Seventh International Conference on Image and Graphics (ICIG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2009/3943/0/04810990",
"title": "Spatialized Haptic Rendering: Providing Impact Position Information in 6DOF Haptic Simulations Using Vibrations",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2009/04810990/12OmNxw5BnV",
"parentPublication": {
"id": "proceedings/vr/2009/3943/0",
"title": "2009 IEEE Virtual Reality Conference",
"__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/haptic/2006/0226/0/01627081",
"title": "Standardized Evaluation of Haptic Rendering Systems",
"doi": null,
"abstractUrl": "/proceedings-article/haptic/2006/01627081/12OmNzR8Czk",
"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/2015/04/07124506",
"title": "Direct Visuo-Haptic 4D Volume Rendering Using Respiratory Motion Models",
"doi": null,
"abstractUrl": "/journal/th/2015/04/07124506/13rRUwInvfi",
"parentPublication": {
"id": "trans/th",
"title": "IEEE Transactions on Haptics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/2022/07/09273221",
"title": "Crowd Navigation in VR: Exploring Haptic Rendering of Collisions",
"doi": null,
"abstractUrl": "/journal/tg/2022/07/09273221/1pb9BhAe16o",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1jPbbHBGDHq",
"title": "2020 IEEE Winter Conference on Applications of Computer Vision (WACV)",
"acronym": "wacv",
"groupId": "1000040",
"volume": "0",
"displayVolume": "0",
"year": "2020",
"__typename": "ProceedingType"
},
"article": {
"id": "1jPbkInDnXy",
"doi": "10.1109/WACV45572.2020.9093346",
"title": "Neural Puppet: Generative Layered Cartoon Characters",
"normalizedTitle": "Neural Puppet: Generative Layered Cartoon Characters",
"abstract": "We propose a learning based method for generating new animations of a cartoon character given a few example images. Our method is designed to learn from a traditionally animated sequence, where each frame is drawn by an artist, and thus the input images lack any common structure, correspondences, or labels. We express pose changes as a deformation of a layered 2.5D template mesh, and devise a novel architecture that learns to predict mesh deformations matching the template to a target image. This enables us to extract a common low-dimensional structure from a diverse set of character poses. We combine recent advances in differentiable rendering as well as mesh-aware models to successfully align common template even if only a few character images are available during training. In addition to coarse poses, character appearance also varies due to shading, out-of-plane motions, and artistic effects. We capture these subtle changes by applying an image translation network to refine the mesh rendering, providing an end-to-end model to generate new animations of a character with high visual quality. We demonstrate that our generative model can be used to synthesize in-between frames and to create data-driven deformation. Our template fitting procedure outperforms state-of-the-art generic techniques for detecting image correspondences.",
"abstracts": [
{
"abstractType": "Regular",
"content": "We propose a learning based method for generating new animations of a cartoon character given a few example images. Our method is designed to learn from a traditionally animated sequence, where each frame is drawn by an artist, and thus the input images lack any common structure, correspondences, or labels. We express pose changes as a deformation of a layered 2.5D template mesh, and devise a novel architecture that learns to predict mesh deformations matching the template to a target image. This enables us to extract a common low-dimensional structure from a diverse set of character poses. We combine recent advances in differentiable rendering as well as mesh-aware models to successfully align common template even if only a few character images are available during training. In addition to coarse poses, character appearance also varies due to shading, out-of-plane motions, and artistic effects. We capture these subtle changes by applying an image translation network to refine the mesh rendering, providing an end-to-end model to generate new animations of a character with high visual quality. We demonstrate that our generative model can be used to synthesize in-between frames and to create data-driven deformation. Our template fitting procedure outperforms state-of-the-art generic techniques for detecting image correspondences.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "We propose a learning based method for generating new animations of a cartoon character given a few example images. Our method is designed to learn from a traditionally animated sequence, where each frame is drawn by an artist, and thus the input images lack any common structure, correspondences, or labels. We express pose changes as a deformation of a layered 2.5D template mesh, and devise a novel architecture that learns to predict mesh deformations matching the template to a target image. This enables us to extract a common low-dimensional structure from a diverse set of character poses. We combine recent advances in differentiable rendering as well as mesh-aware models to successfully align common template even if only a few character images are available during training. In addition to coarse poses, character appearance also varies due to shading, out-of-plane motions, and artistic effects. We capture these subtle changes by applying an image translation network to refine the mesh rendering, providing an end-to-end model to generate new animations of a character with high visual quality. We demonstrate that our generative model can be used to synthesize in-between frames and to create data-driven deformation. Our template fitting procedure outperforms state-of-the-art generic techniques for detecting image correspondences.",
"fno": "09093346",
"keywords": [
"Computer Animation",
"Feature Extraction",
"Image Matching",
"Image Sequences",
"Learning Artificial Intelligence",
"Neural Nets",
"Pose Estimation",
"Rendering Computer Graphics",
"Neural Puppet",
"Generative Layered Cartoon Characters",
"Learning Based Method",
"Animations",
"Cartoon Character",
"Input Images",
"Common Structure",
"2 5 D Template Mesh",
"Mesh Deformations",
"Target Image",
"Low Dimensional Structure",
"Character Poses",
"Differentiable Rendering",
"Mesh Aware Models",
"Character Images",
"Coarse Poses",
"Character Appearance",
"Artistic Effects",
"Image Translation Network",
"Mesh Rendering",
"End To End Model",
"Generative Model",
"Data Driven Deformation",
"Template Fitting Procedure",
"Image Correspondences",
"Strain",
"Animation",
"Training",
"Deformable Models",
"Rendering Computer Graphics",
"Computational Modeling",
"Three Dimensional Displays"
],
"authors": [
{
"affiliation": "Cornell University",
"fullName": "Omid Poursaeed",
"givenName": "Omid",
"surname": "Poursaeed",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Adobe Research",
"fullName": "Vladimir G. Kim",
"givenName": "Vladimir G.",
"surname": "Kim",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Adobe Research",
"fullName": "Eli Shechtman",
"givenName": "Eli",
"surname": "Shechtman",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Adobe Research",
"fullName": "Jun Saito",
"givenName": "Jun",
"surname": "Saito",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Cornell University",
"fullName": "Serge Belongie",
"givenName": "Serge",
"surname": "Belongie",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "wacv",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2020-03-01T00:00:00",
"pubType": "proceedings",
"pages": "3335-3345",
"year": "2020",
"issn": null,
"isbn": "978-1-7281-6553-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09093513",
"articleId": "1jPbhl2sXny",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09093320",
"articleId": "1jPbsFLjroc",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ca/1994/6240/0/00323996",
"title": "Modelling and interpolating cartoon characters",
"doi": null,
"abstractUrl": "/proceedings-article/ca/1994/00323996/12OmNCwCLm2",
"parentPublication": {
"id": "proceedings/ca/1994/6240/0",
"title": "Proceedings of Computer Animation '94",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icvrv/2014/6854/0/6854a058",
"title": "Animation of Refitted 3D Garment Models for Reshaped Bodies",
"doi": null,
"abstractUrl": "/proceedings-article/icvrv/2014/6854a058/12OmNvAiSyg",
"parentPublication": {
"id": "proceedings/icvrv/2014/6854/0",
"title": "2014 International Conference on Virtual Reality and Visualization (ICVRV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icig/2004/2244/0/01410478",
"title": "Impostor-based animation of deformable virtual characters with dynamic shadow",
"doi": null,
"abstractUrl": "/proceedings-article/icig/2004/01410478/12OmNwJgAFK",
"parentPublication": {
"id": "proceedings/icig/2004/2244/0",
"title": "Proceedings. Third International Conference on Image and Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2008/1971/0/04480788",
"title": "Piavca: A Framework for Heterogeneous Interactions with Virtual Characters",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2008/04480788/12OmNx3Zjlw",
"parentPublication": {
"id": "proceedings/vr/2008/1971/0",
"title": "IEEE Virtual Reality 2008",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cad-graphics/2015/8020/0/07450426",
"title": "Automatic Human Animation for Non-Humanoid 3D Characters",
"doi": null,
"abstractUrl": "/proceedings-article/cad-graphics/2015/07450426/12OmNyQYtow",
"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/iccit/2009/3896/0/3896a393",
"title": "A Rapid Mesh Fusion Method to Create 3D Virtual Characters in Games",
"doi": null,
"abstractUrl": "/proceedings-article/iccit/2009/3896a393/12OmNyQYtwe",
"parentPublication": {
"id": "proceedings/iccit/2009/3896/0",
"title": "Convergence Information Technology, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2007/2996/0/29960003",
"title": "A Simple Framework for Natural Animation of Digitized Models",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2007/29960003/12OmNzIUfYb",
"parentPublication": {
"id": "proceedings/sibgrapi/2007/2996/0",
"title": "XX Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2007)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sibgrapi/2012/4829/0/4829a198",
"title": "Representing and Manipulating Mesh-Based Character Animations",
"doi": null,
"abstractUrl": "/proceedings-article/sibgrapi/2012/4829a198/12OmNznkKdG",
"parentPublication": {
"id": "proceedings/sibgrapi/2012/4829/0",
"title": "2012 25th SIBGRAPI Conference on Graphics, Patterns and Images",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2011/04/mcg2011040056",
"title": "Direct Control of Simulated Nonhuman Characters",
"doi": null,
"abstractUrl": "/magazine/cg/2011/04/mcg2011040056/13rRUwInv93",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2021/2812/0/281200k0734",
"title": "Dynamic Surface Function Networks for Clothed Human Bodies",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2021/281200k0734/1BmFU8kwG2s",
"parentPublication": {
"id": "proceedings/iccv/2021/2812/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzlUKD1",
"title": "2012 IEEE International Conference on Automation Science and Engineering (CASE 2012)",
"acronym": "case",
"groupId": "1001095",
"volume": "0",
"displayVolume": "0",
"year": "2012",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNwD1pWU",
"doi": "10.1109/CoASE.2012.6386365",
"title": "Uncertainty management in remanufacturing: A review",
"normalizedTitle": "Uncertainty management in remanufacturing: A review",
"abstract": "Remanufacturing is practice of importance due to the increasing environmental and economic pressure. The process exhibits high levels of uncertainty, making its planning and control more complex than in traditional manufacturing. This paper reviews recent methods for modeling, analyzing and managing such uncertainty in remanufacturing. The purpose is to survey state-of-the-art of this emerging area to supply important insights for future study.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Remanufacturing is practice of importance due to the increasing environmental and economic pressure. The process exhibits high levels of uncertainty, making its planning and control more complex than in traditional manufacturing. This paper reviews recent methods for modeling, analyzing and managing such uncertainty in remanufacturing. The purpose is to survey state-of-the-art of this emerging area to supply important insights for future study.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Remanufacturing is practice of importance due to the increasing environmental and economic pressure. The process exhibits high levels of uncertainty, making its planning and control more complex than in traditional manufacturing. This paper reviews recent methods for modeling, analyzing and managing such uncertainty in remanufacturing. The purpose is to survey state-of-the-art of this emerging area to supply important insights for future study.",
"fno": "06386365",
"keywords": [
"Process Control",
"Process Planning",
"Recycling",
"Uncertainty Management",
"Remanufacturing",
"Environmental Pressure",
"Economic Pressure",
"Industrial Process",
"Process Planning",
"Process Control",
"Uncertainty",
"Manufacturing",
"Stochastic Processes",
"Production Planning",
"Planning",
"Inspection"
],
"authors": [
{
"affiliation": "Department of Electrical and Computer Engineering, Glassboro, NJ 08028, USA",
"fullName": "Ying Tang",
"givenName": "Ying",
"surname": "Tang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "State Key Lab of Mechanical Transmission, Chonqing University, China",
"fullName": "Congbo Li",
"givenName": "Congbo",
"surname": "Li",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "case",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2012-08-01T00:00:00",
"pubType": "proceedings",
"pages": "52-57",
"year": "2012",
"issn": "2161-8070",
"isbn": "978-1-4673-0430-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "06386364",
"articleId": "12OmNxbEtLs",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "06386366",
"articleId": "12OmNzt0Iz0",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/date/2008/3/0/04484690",
"title": "Resilient Dynamic Power Management under Uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/date/2008/04484690/12OmNASraPI",
"parentPublication": {
"id": "proceedings/date/2008/3/0",
"title": "Design, Automation & Test in Europe. DATE'08",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/isee/2007/0861/0/04222886",
"title": "Lean Production Principles in Remanufacturing A Case Study at a Toner Cartridge Remanufacturer",
"doi": null,
"abstractUrl": "/proceedings-article/isee/2007/04222886/12OmNBuL1gb",
"parentPublication": {
"id": "proceedings/isee/2007/0861/0",
"title": "2007 IEEE International Symposium on Electronics and the Environment",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecodesign/2001/1266/0/00992454",
"title": "Production planning in remanufacturing/manufacturing production system",
"doi": null,
"abstractUrl": "/proceedings-article/ecodesign/2001/00992454/12OmNC8dgcG",
"parentPublication": {
"id": "proceedings/ecodesign/2001/1266/0",
"title": "Environmentally Conscious Design and Inverse Manufacturing, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/case/2011/1732/0/06042398",
"title": "A GERT-based analytical method for remanufacturing process routing",
"doi": null,
"abstractUrl": "/proceedings-article/case/2011/06042398/12OmNvkplaU",
"parentPublication": {
"id": "proceedings/case/2011/1732/0",
"title": "2011 IEEE International Conference on Automation Science and Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecodim/2001/1266/0/00992311",
"title": "Planning for product take-back and component life under uncertainty in technological evolution",
"doi": null,
"abstractUrl": "/proceedings-article/ecodim/2001/00992311/12OmNwErpRT",
"parentPublication": {
"id": "proceedings/ecodim/2001/1266/0",
"title": "Proceedings Second International Symposium on Environmentally Conscious Design and Inverse Manufacturing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cmcsn/2012/4738/0/4738a289",
"title": "The Uncertainty Analysis and Verification of the PG7607 Gas Piston Pressure Gauge",
"doi": null,
"abstractUrl": "/proceedings-article/cmcsn/2012/4738a289/12OmNyGbIbb",
"parentPublication": {
"id": "proceedings/cmcsn/2012/4738/0",
"title": "Computing, Measurement, Control and Sensor Network, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecodesign/2001/1266/0/00992311",
"title": "Planning for product take-back and component life under uncertainty in technological evolution",
"doi": null,
"abstractUrl": "/proceedings-article/ecodesign/2001/00992311/12OmNywxlQt",
"parentPublication": {
"id": "proceedings/ecodesign/2001/1266/0",
"title": "Environmentally Conscious Design and Inverse Manufacturing, International Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2011/9618/0/05718966",
"title": "An Investigation on Capacity Planning and Lead Times for Remanufacturing Systems Using System Dynamics",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2011/05718966/12OmNzBwGz3",
"parentPublication": {
"id": "proceedings/hicss/2011/9618/0",
"title": "2011 44th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iiai-aai/2017/0621/0/0621a927",
"title": "Impact of Environmental Uncertainty and Organizational Mechanism on Manufacturing Flexibility through Absorptive Capacity",
"doi": null,
"abstractUrl": "/proceedings-article/iiai-aai/2017/0621a927/12OmNzl3WTA",
"parentPublication": {
"id": "proceedings/iiai-aai/2017/0621/0",
"title": "2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ecodim/2001/1266/0/00992454",
"title": "Production planning in remanufacturing/manufacturing production system",
"doi": null,
"abstractUrl": "/proceedings-article/ecodim/2001/00992454/12OmNzt0Iyc",
"parentPublication": {
"id": "proceedings/ecodim/2001/1266/0",
"title": "Proceedings Second International Symposium on Environmentally Conscious Design and Inverse Manufacturing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNBfZSjh",
"title": "2015 IEEE/ACM 7th International Workshop on Modeling in Software Engineering (MiSE)",
"acronym": "mise",
"groupId": "1001864",
"volume": "0",
"displayVolume": "0",
"year": "2015",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNxG1yWW",
"doi": "10.1109/MiSE.2015.9",
"title": "Modularity for Uncertainty",
"normalizedTitle": "Modularity for Uncertainty",
"abstract": "Uncertainty can appear in all aspects of software development: uncertainty in requirements analysis, design decisions, implementation, and testing. As the research on uncertainty is so young, there are many issues to be tackled. Modularity for Uncertainty is one of them. If uncertainty can be dealt with modularly, we can add or delete uncertain concerns to/from models, code, and tests whenever these concerns arise or are fixed to certain concerns. To deal with this challenging issue, we propose a modularization mechanism for uncertainty. Agile methods embrace change to accept changeable user requirements. On the other hand, our approach embraces uncertainty to support exploratory development. This paper sets out a focused research agenda for uncertainty in terms of the new modularity vision.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Uncertainty can appear in all aspects of software development: uncertainty in requirements analysis, design decisions, implementation, and testing. As the research on uncertainty is so young, there are many issues to be tackled. Modularity for Uncertainty is one of them. If uncertainty can be dealt with modularly, we can add or delete uncertain concerns to/from models, code, and tests whenever these concerns arise or are fixed to certain concerns. To deal with this challenging issue, we propose a modularization mechanism for uncertainty. Agile methods embrace change to accept changeable user requirements. On the other hand, our approach embraces uncertainty to support exploratory development. This paper sets out a focused research agenda for uncertainty in terms of the new modularity vision.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Uncertainty can appear in all aspects of software development: uncertainty in requirements analysis, design decisions, implementation, and testing. As the research on uncertainty is so young, there are many issues to be tackled. Modularity for Uncertainty is one of them. If uncertainty can be dealt with modularly, we can add or delete uncertain concerns to/from models, code, and tests whenever these concerns arise or are fixed to certain concerns. To deal with this challenging issue, we propose a modularization mechanism for uncertainty. Agile methods embrace change to accept changeable user requirements. On the other hand, our approach embraces uncertainty to support exploratory development. This paper sets out a focused research agenda for uncertainty in terms of the new modularity vision.",
"fno": "7055a007",
"keywords": [
"Uncertainty",
"Unified Modeling Language",
"Software",
"Testing",
"Runtime",
"Cognition",
"Connectors",
"Known Unknown",
"Uncertainty",
"Partial Model"
],
"authors": [
{
"affiliation": null,
"fullName": "Takuya Fukamachi",
"givenName": "Takuya",
"surname": "Fukamachi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Naoyasu Ubayashi",
"givenName": "Naoyasu",
"surname": "Ubayashi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Shintaro Hosoai",
"givenName": "Shintaro",
"surname": "Hosoai",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Yasutaka Kamei",
"givenName": "Yasutaka",
"surname": "Kamei",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "mise",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2015-05-01T00:00:00",
"pubType": "proceedings",
"pages": "7-12",
"year": "2015",
"issn": "2156-7891",
"isbn": "978-1-4673-7055-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "7055a001",
"articleId": "12OmNs4S8Cr",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "7055a013",
"articleId": "12OmNx7G61c",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/models/2017/3492/0/3492a093",
"title": "Software Product Lines with Design Choices: Reasoning about Variability and Design Uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/models/2017/3492a093/12OmNAXPy4s",
"parentPublication": {
"id": "proceedings/models/2017/3492/0",
"title": "2017 ACM/IEEE 20th International Conference on Model Driven Engineering Languages and Systems (MODELS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/quatic/2016/3581/0/3581a015",
"title": "Expressing Measurement Uncertainty in Software Models",
"doi": null,
"abstractUrl": "/proceedings-article/quatic/2016/3581a015/12OmNAZOK1b",
"parentPublication": {
"id": "proceedings/quatic/2016/3581/0",
"title": "2016 10th International Conference on the Quality of Information and Communications Technology (QUATIC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icse/2012/1066/0/06227159",
"title": "Partial models: Towards modeling and reasoning with uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/icse/2012/06227159/12OmNBgQFSA",
"parentPublication": {
"id": "proceedings/icse/2012/1066/0",
"title": "2012 34th International Conference on Software Engineering (ICSE 2012)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icis/2017/5507/0/07960091",
"title": "Fuzzy ontology induction in the cognitive model of ontology learning",
"doi": null,
"abstractUrl": "/proceedings-article/icis/2017/07960091/12OmNCeK2f0",
"parentPublication": {
"id": "proceedings/icis/2017/5507/0",
"title": "2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hicss/2011/9618/0/05718862",
"title": "Reducing Uncertainty in Architectural Decisions with AADL",
"doi": null,
"abstractUrl": "/proceedings-article/hicss/2011/05718862/12OmNwErpOy",
"parentPublication": {
"id": "proceedings/hicss/2011/9618/0",
"title": "2011 44th Hawaii International Conference on System Sciences",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sbst/2017/2789/0/07967956",
"title": "An Empirical Evaluation of Mutation and Crossover Operators for Multi-Objective Uncertainty-Wise Test Minimization",
"doi": null,
"abstractUrl": "/proceedings-article/sbst/2017/07967956/12OmNwxlrf2",
"parentPublication": {
"id": "proceedings/sbst/2017/2789/0",
"title": "2017 IEEE/ACM 10th International Workshop on Search-Based Software Testing (SBST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mise/2017/0426/0/07964594",
"title": "iArch-U: Interface-Centric Integrated Uncertainty-Aware Development Environment",
"doi": null,
"abstractUrl": "/proceedings-article/mise/2017/07964594/12OmNxE2mNd",
"parentPublication": {
"id": "proceedings/mise/2017/0426/0",
"title": "2017 IEEE/ACM 9th International Workshop on Modelling in Software Engineering (MiSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/mise/2013/6447/0/06595295",
"title": "Design module: A modularity vision beyond code: Not only program code but also a design model is a module",
"doi": null,
"abstractUrl": "/proceedings-article/mise/2013/06595295/12OmNxdm4xU",
"parentPublication": {
"id": "proceedings/mise/2013/6447/0",
"title": "2013 5th International Workshop on Modeling in Software Engineering (MiSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icis/2012/1536/0/06211148",
"title": "Adding Aspects to Software Architecture",
"doi": null,
"abstractUrl": "/proceedings-article/icis/2012/06211148/12OmNzZWbCc",
"parentPublication": {
"id": "proceedings/icis/2012/1536/0",
"title": "2012 IEEE/ACIS 11th International Conference on Computer and Information Science (ICIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icse-companion/2019/1764/0/176400a095",
"title": "Git-Based Integrated Uncertainty Manager",
"doi": null,
"abstractUrl": "/proceedings-article/icse-companion/2019/176400a095/1cJ7iTrqyLm",
"parentPublication": {
"id": "proceedings/icse-companion/2019/1764/0",
"title": "2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1tmhi3ly74c",
"title": "2020 25th International Conference on Pattern Recognition (ICPR)",
"acronym": "icpr",
"groupId": "1000545",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1tmj0SEORmE",
"doi": "10.1109/ICPR48806.2021.9413010",
"title": "On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration",
"normalizedTitle": "On-manifold Adversarial Data Augmentation Improves Uncertainty Calibration",
"abstract": "Uncertainty estimates help to identify ambiguous, novel, or anomalous inputs, but the reliable quantification of uncertainty has proven to be challenging for modern deep networks. To improve uncertainty estimation, we propose On-Manifold Adversarial Data Augmentation or OMADA, which specifically attempts to generate challenging examples by following an on-manifold adversarial attack path in the latent space of an autoencoder that closely approximates the decision boundaries between classes. On a variety of datasets and for multiple network architectures, OMADA consistently yields more accurate and better calibrated classifiers than baseline models, and outperforms competing approaches such as Mixup, as well as achieving similar performance to (at times better than) postprocessing calibration methods such as temperature scaling. Variants of OMADA can employ different sampling schemes for ambiguous on-manifold examples based on the entropy of their estimated soft labels, which exhibit specific strengths for generalization, calibration of predicted uncertainty, or detection of out-of-distribution inputs.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Uncertainty estimates help to identify ambiguous, novel, or anomalous inputs, but the reliable quantification of uncertainty has proven to be challenging for modern deep networks. To improve uncertainty estimation, we propose On-Manifold Adversarial Data Augmentation or OMADA, which specifically attempts to generate challenging examples by following an on-manifold adversarial attack path in the latent space of an autoencoder that closely approximates the decision boundaries between classes. On a variety of datasets and for multiple network architectures, OMADA consistently yields more accurate and better calibrated classifiers than baseline models, and outperforms competing approaches such as Mixup, as well as achieving similar performance to (at times better than) postprocessing calibration methods such as temperature scaling. Variants of OMADA can employ different sampling schemes for ambiguous on-manifold examples based on the entropy of their estimated soft labels, which exhibit specific strengths for generalization, calibration of predicted uncertainty, or detection of out-of-distribution inputs.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Uncertainty estimates help to identify ambiguous, novel, or anomalous inputs, but the reliable quantification of uncertainty has proven to be challenging for modern deep networks. To improve uncertainty estimation, we propose On-Manifold Adversarial Data Augmentation or OMADA, which specifically attempts to generate challenging examples by following an on-manifold adversarial attack path in the latent space of an autoencoder that closely approximates the decision boundaries between classes. On a variety of datasets and for multiple network architectures, OMADA consistently yields more accurate and better calibrated classifiers than baseline models, and outperforms competing approaches such as Mixup, as well as achieving similar performance to (at times better than) postprocessing calibration methods such as temperature scaling. Variants of OMADA can employ different sampling schemes for ambiguous on-manifold examples based on the entropy of their estimated soft labels, which exhibit specific strengths for generalization, calibration of predicted uncertainty, or detection of out-of-distribution inputs.",
"fno": "09413010",
"keywords": [
"Calibration",
"Generalisation Artificial Intelligence",
"Learning Artificial Intelligence",
"Pattern Classification",
"Uncertainty Calibration",
"Anomalous Inputs",
"Modern Deep Networks",
"Uncertainty Estimation",
"OMADA",
"On Manifold Adversarial Attack Path",
"Multiple Network Architectures",
"Soft Labels",
"Generalization",
"On Manifold Adversarial Data Augmentation",
"Autoencoder",
"Manifolds",
"Training",
"Uncertainty",
"Temperature",
"Estimation",
"Stochastic Processes",
"Network Architecture"
],
"authors": [
{
"affiliation": "Institute of Signal Processing and System Theory, University of Stuttgart,Stuttgart,Germany",
"fullName": "Kanil Patel",
"givenName": "Kanil",
"surname": "Patel",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Bosch Center for Artificial Intelligence,Renningen,Germany",
"fullName": "William Beluch",
"givenName": "William",
"surname": "Beluch",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Bosch Center for Artificial Intelligence,Renningen,Germany",
"fullName": "Dan Zhang",
"givenName": "Dan",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Bosch Center for Artificial Intelligence,Renningen,Germany",
"fullName": "Michael Pfeiffer",
"givenName": "Michael",
"surname": "Pfeiffer",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Institute of Signal Processing and System Theory, University of Stuttgart,Stuttgart,Germany",
"fullName": "Bin Yang",
"givenName": "Bin",
"surname": "Yang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icpr",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-01-01T00:00:00",
"pubType": "proceedings",
"pages": "8029-8036",
"year": "2021",
"issn": "1051-4651",
"isbn": "978-1-7281-8808-9",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "09412322",
"articleId": "1tmjQVF15sY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "09411982",
"articleId": "1tmjMeS6ITe",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/uic-atc-scalcom-cbdcom-iop-smartworld/2016/2771/0/07816829",
"title": "Heterogeneous Data Driven Manifold Regularization Model for Fingerprint Calibration Reduction",
"doi": null,
"abstractUrl": "/proceedings-article/uic-atc-scalcom-cbdcom-iop-smartworld/2016/07816829/12OmNvxbhNU",
"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/iciii/2010/4279/3/4279c332",
"title": "Computer-based System for Calibration of Temperature Transmitter Using RTD",
"doi": null,
"abstractUrl": "/proceedings-article/iciii/2010/4279c332/12OmNz2C1AY",
"parentPublication": {
"id": "proceedings/iciii/2010/4279/3",
"title": "International Conference on Information Management, Innovation Management and Industrial Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2018/6420/0/642000f580",
"title": "Wrapped Gaussian Process Regression on Riemannian Manifolds",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2018/642000f580/17D45Xbl4Pl",
"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/cvpr/2022/6946/0/694600q6113",
"title": "Geometric Anchor Correspondence Mining with Uncertainty Modeling for Universal Domain Adaptation",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2022/694600q6113/1H0OenGZVYY",
"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/icdar/2019/3014/0/301400a799",
"title": "Manifold Mixup Improves Text Recognition with CTC Loss",
"doi": null,
"abstractUrl": "/proceedings-article/icdar/2019/301400a799/1h81xYsQOIM",
"parentPublication": {
"id": "proceedings/icdar/2019/3014/0",
"title": "2019 International Conference on Document Analysis and Recognition (ICDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccv/2019/4803/0/480300b497",
"title": "Calibration Wizard: A Guidance System for Camera Calibration Based on Modelling Geometric and Corner Uncertainty",
"doi": null,
"abstractUrl": "/proceedings-article/iccv/2019/480300b497/1hVlBp1zhpm",
"parentPublication": {
"id": "proceedings/iccv/2019/4803/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision (ICCV)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/09022324",
"title": "Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/09022324/1i5mCk3kctW",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2022/02/09093149",
"title": "Horizontal Flows and Manifold Stochastics in Geometric Deep Learning",
"doi": null,
"abstractUrl": "/journal/tp/2022/02/09093149/1jNtLSScpgY",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2021/0191/0/019100b029",
"title": "MEAL: Manifold Embedding-based Active Learning",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2021/019100b029/1yNhQYsvrZ6",
"parentPublication": {
"id": "proceedings/iccvw/2021/0191/0",
"title": "2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cvpr/2021/4509/0/450900k0119",
"title": "Post-hoc Uncertainty Calibration for Domain Drift Scenarios",
"doi": null,
"abstractUrl": "/proceedings-article/cvpr/2021/450900k0119/1yeJvRAEKvC",
"parentPublication": {
"id": "proceedings/cvpr/2021/4509/0",
"title": "2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNxA3Z4G",
"title": "Proceedings. 38th Annual Simulation Symposium",
"acronym": "anss",
"groupId": "1000676",
"volume": "0",
"displayVolume": "0",
"year": "2005",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNB1wkOQ",
"doi": "10.1109/ANSS.2005.8",
"title": "A Neural Approach for Fast Simulation of Flight Mechanics",
"normalizedTitle": "A Neural Approach for Fast Simulation of Flight Mechanics",
"abstract": "Flight simulators have been part of aviation history since its beginning. With the development of modern aeronautics industry, flight simulators have gained an important place and the industry devoted to their manufacture has become significant. In the case of transportation aircraft, accurate mathematical models based on extensive experimental data have been developed by their manufacturers to optimise their aerodynamic and propulsive characteristics and to design efficient flight control systems. However, in the case of small general aviation aircraft this kind of knowledge is not commonly available and the design of accurate flight simulators can result in a tedious try and modify process until the simulator presents a qualitative behaviour close to the one of the real aircraft. This communication proposes through the use of neural networks a method to perform a direct estimation of the aerodynamic forces acting on aircraft. Artificial Neural networks appear to be an appropriate numerical technique to achieve the mapping of these continuous relationships and detailed aerodynamics and thrust models should become no more mandatory to produce accurate flight simulation software.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Flight simulators have been part of aviation history since its beginning. With the development of modern aeronautics industry, flight simulators have gained an important place and the industry devoted to their manufacture has become significant. In the case of transportation aircraft, accurate mathematical models based on extensive experimental data have been developed by their manufacturers to optimise their aerodynamic and propulsive characteristics and to design efficient flight control systems. However, in the case of small general aviation aircraft this kind of knowledge is not commonly available and the design of accurate flight simulators can result in a tedious try and modify process until the simulator presents a qualitative behaviour close to the one of the real aircraft. This communication proposes through the use of neural networks a method to perform a direct estimation of the aerodynamic forces acting on aircraft. Artificial Neural networks appear to be an appropriate numerical technique to achieve the mapping of these continuous relationships and detailed aerodynamics and thrust models should become no more mandatory to produce accurate flight simulation software.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Flight simulators have been part of aviation history since its beginning. With the development of modern aeronautics industry, flight simulators have gained an important place and the industry devoted to their manufacture has become significant. In the case of transportation aircraft, accurate mathematical models based on extensive experimental data have been developed by their manufacturers to optimise their aerodynamic and propulsive characteristics and to design efficient flight control systems. However, in the case of small general aviation aircraft this kind of knowledge is not commonly available and the design of accurate flight simulators can result in a tedious try and modify process until the simulator presents a qualitative behaviour close to the one of the real aircraft. This communication proposes through the use of neural networks a method to perform a direct estimation of the aerodynamic forces acting on aircraft. Artificial Neural networks appear to be an appropriate numerical technique to achieve the mapping of these continuous relationships and detailed aerodynamics and thrust models should become no more mandatory to produce accurate flight simulation software.",
"fno": "23220168",
"keywords": [],
"authors": [
{
"affiliation": "UNICAMP/FEE",
"fullName": "Gi?rgio Valm?rbida",
"givenName": "Gi?rgio",
"surname": "Valm?rbida",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "LAAS du CNRS and ENAC/DGAC",
"fullName": "Wen-Chi Lu",
"givenName": "Wen-Chi",
"surname": "Lu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "LAAS du CNRS and ENAC/DGAC",
"fullName": "F?lix Mora-Camino",
"givenName": "F?lix",
"surname": "Mora-Camino",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "anss",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2005-04-01T00:00:00",
"pubType": "proceedings",
"pages": "168-172",
"year": "2005",
"issn": "1080-241X",
"isbn": "0-7695-2322-6",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "23220160",
"articleId": "12OmNwpGgQj",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "23220175",
"articleId": "12OmNykkB5L",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/hpcmp-ugc/2006/2797/0/27970052",
"title": "High Resolution Simulation of Full Aircraft Control at Flight Reynolds Numbers",
"doi": null,
"abstractUrl": "/proceedings-article/hpcmp-ugc/2006/27970052/12OmNBhHtfo",
"parentPublication": {
"id": "proceedings/hpcmp-ugc/2006/2797/0",
"title": "HPCMP Users Group Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/1999/5780/2/57801295",
"title": "Using airspace simulation to assess environmental improvements from free flight and CNS/ATM enhancements",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/1999/57801295/12OmNBr4eyu",
"parentPublication": {
"id": "proceedings/wsc/1999/5780/2",
"title": "Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ssst/1995/6985/0/69850487",
"title": "Integrated flight control problem on decentralized sliding modes",
"doi": null,
"abstractUrl": "/proceedings-article/ssst/1995/69850487/12OmNCcbEhr",
"parentPublication": {
"id": "proceedings/ssst/1995/6985/0",
"title": "Southeastern Symposium on System Theory",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/wsc/2002/7614/2/01166382",
"title": "Research flight simulation of future autonomous aircraft operations",
"doi": null,
"abstractUrl": "/proceedings-article/wsc/2002/01166382/12OmNCctfhw",
"parentPublication": {
"id": "proceedings/wsc/2002/7614/2",
"title": "Proceedings of the 2002 Winter Simulation Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/hpcmp-ugc/2007/3088/0/30880041",
"title": "High Resolution Simulation of Full Aircraft Control at Flight Reynolds Numbers",
"doi": null,
"abstractUrl": "/proceedings-article/hpcmp-ugc/2007/30880041/12OmNxFaLcx",
"parentPublication": {
"id": "proceedings/hpcmp-ugc/2007/3088/0",
"title": "HPCMP Users Group Conference",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/itng/2015/8828/0/8828a095",
"title": "IFA2S -- In-flight Awareness Augmentation Systems",
"doi": null,
"abstractUrl": "/proceedings-article/itng/2015/8828a095/12OmNxjjEbO",
"parentPublication": {
"id": "proceedings/itng/2015/8828/0",
"title": "2015 12th International Conference on Information Technology - New Generations (ITNG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2012/4637/0/4637a147",
"title": "Dynamic Modeling and Simulation for a Supermaneuverable Aircraft in Disturbance of Wind Field",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2012/4637a147/12OmNzZEAoW",
"parentPublication": {
"id": "proceedings/icicta/2012/4637/0",
"title": "Intelligent Computation Technology and Automation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09772329",
"title": "Using Extended Reality in Flight Simulators: A Literature Review",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09772329/1DgjDn5nymI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icbaie/2020/6499/0/09196234",
"title": "Research on Air-Ground Joint Debugging System of Flight Inspection",
"doi": null,
"abstractUrl": "/proceedings-article/icbaie/2020/09196234/1n90ZQZRJL2",
"parentPublication": {
"id": "proceedings/icbaie/2020/6499/0",
"title": "2020 International Conference on Big Data, Artificial Intelligence and Internet of Things Engineering (ICBAIE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscsic/2021/1627/0/162700a028",
"title": "Research on Method of Fixed Load Aerodynamic Center in the Flight Test for Civil Aircraft",
"doi": null,
"abstractUrl": "/proceedings-article/iscsic/2021/162700a028/1zzpmqDEAes",
"parentPublication": {
"id": "proceedings/iscsic/2021/1627/0",
"title": "2021 International Symposium on Computer Science and Intelligent Controls (ISCSIC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1B4m5JQTui4",
"title": "2021 28th Asia-Pacific Software Engineering Conference (APSEC)",
"acronym": "apsec",
"groupId": "1000681",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1B4m7XRlTcQ",
"doi": "10.1109/APSEC53868.2021.00073",
"title": "Topic Trends in Issue Tracking System of Extended Reality Frameworks",
"normalizedTitle": "Topic Trends in Issue Tracking System of Extended Reality Frameworks",
"abstract": "Extended Reality (XR) is an emerging technique with a lot of application domains. In this paper, we present an exploration study of two XR frameworks, in particular investigating the trends of topics in their issue tracking systems over time.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Extended Reality (XR) is an emerging technique with a lot of application domains. In this paper, we present an exploration study of two XR frameworks, in particular investigating the trends of topics in their issue tracking systems over time.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Extended Reality (XR) is an emerging technique with a lot of application domains. In this paper, we present an exploration study of two XR frameworks, in particular investigating the trends of topics in their issue tracking systems over time.",
"fno": "378400a572",
"keywords": [
"Software Engineering",
"Topic Trends",
"Issue Tracking System",
"Application Domains",
"XR Frameworks",
"Extended Reality Frameworks",
"Extended Reality",
"Market Research",
"X Reality",
"Software Engineering",
"Issue Tracking Systems",
"Extended Reality",
"Topic Trends"
],
"authors": [
{
"affiliation": "University of Texas at San Antonio,Department of Computer Science",
"fullName": "Irving Rodriguez",
"givenName": "Irving",
"surname": "Rodriguez",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Texas at San Antonio,Department of Computer Science",
"fullName": "Xiaoyin Wang",
"givenName": "Xiaoyin",
"surname": "Wang",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "apsec",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-12-01T00:00:00",
"pubType": "proceedings",
"pages": "572-573",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-3784-4",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "378400a570",
"articleId": "1B4m8V5gTPq",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "378400a574",
"articleId": "1B4mc9yCjss",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ucc-companion/2018/0359/0/035900a353",
"title": "A Review of Applications of Extended Reality in the Construction Domain",
"doi": null,
"abstractUrl": "/proceedings-article/ucc-companion/2018/035900a353/17D45WB0qbv",
"parentPublication": {
"id": "proceedings/ucc-companion/2018/0359/0",
"title": "2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a419",
"title": "Designing Extended Reality Guidance for Physical Caregiving Tasks",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a419/1CJfkFG7dgA",
"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": "proceedings/cw/2022/6814/0/681400a195",
"title": "Using Extended Reality to Teach Protection of Civilians in Higher Military Education",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2022/681400a195/1I6RMFjiO0U",
"parentPublication": {
"id": "proceedings/cw/2022/6814/0",
"title": "2022 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a322",
"title": "Extended Reality Training for Business and Education: The New Generation of Learning Experiences",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a322/1J7W77jxOlq",
"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/2022/5365/0/536500a254",
"title": "Generative Research in the Context of Academic Extended Reality Research",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a254/1J7WcCweXhC",
"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/2022/5365/0/536500a167",
"title": "Flexible XR Prototyping – A Sports Spectating Example",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a167/1J7WuYXm6kg",
"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/mass/2022/7180/0/718000a131",
"title": "Emulating Your eXtended World: An Emulation Environment for XR App Development",
"doi": null,
"abstractUrl": "/proceedings-article/mass/2022/718000a131/1JeEl77BoRy",
"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/issre/2020/9870/0/987000a172",
"title": "An Exploratory Study of Bugs in Extended Reality Applications on the Web",
"doi": null,
"abstractUrl": "/proceedings-article/issre/2020/987000a172/1oFGJBurm48",
"parentPublication": {
"id": "proceedings/issre/2020/9870/0",
"title": "2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a476",
"title": "Designing Virtual Pedagogical Agents and Mentors for Extended Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a476/1yeQC8OgSoU",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a018",
"title": "Accessible Tangible User Interfaces in eXtended Reality Experiences for Cultural Heritage",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a018/1yeQGLRgXHW",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1J7W6LmbCw0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"acronym": "ismar-adjunct",
"groupId": "9973799",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1J7W77jxOlq",
"doi": "10.1109/ISMAR-Adjunct57072.2022.00071",
"title": "Extended Reality Training for Business and Education: The New Generation of Learning Experiences",
"normalizedTitle": "Extended Reality Training for Business and Education: The New Generation of Learning Experiences",
"abstract": "The use of Extended Reality (XR) technology in educational and corporate settings is becoming increasingly important. Although much research has been done on the use of XR for corporate and educational training, little has been published on the integration of XR into real-world applications and scenarios. In this paper, we will discuss the lessons learned from the integration of XR training into a real business environment and educational settings. Furthermore, we will use research that has been further developed into commercial products. The lessons learned are discussed, as well as the real-world challenges and problem solving approaches necessary for success.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The use of Extended Reality (XR) technology in educational and corporate settings is becoming increasingly important. Although much research has been done on the use of XR for corporate and educational training, little has been published on the integration of XR into real-world applications and scenarios. In this paper, we will discuss the lessons learned from the integration of XR training into a real business environment and educational settings. Furthermore, we will use research that has been further developed into commercial products. The lessons learned are discussed, as well as the real-world challenges and problem solving approaches necessary for success.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The use of Extended Reality (XR) technology in educational and corporate settings is becoming increasingly important. Although much research has been done on the use of XR for corporate and educational training, little has been published on the integration of XR into real-world applications and scenarios. In this paper, we will discuss the lessons learned from the integration of XR training into a real business environment and educational settings. Furthermore, we will use research that has been further developed into commercial products. The lessons learned are discussed, as well as the real-world challenges and problem solving approaches necessary for success.",
"fno": "536500a322",
"keywords": [
"Computer Based Training",
"Problem Solving",
"User Experience",
"Virtual Reality",
"Business Environment",
"Corporate Settings",
"Corporate Training",
"Educational Settings",
"Educational Training",
"Extended Reality Technology",
"Extended Reality Training",
"Real World Applications",
"XR",
"Training",
"Extended Reality",
"Problem Solving",
"X Reality",
"Business"
],
"authors": [
{
"affiliation": "University of Applied Management",
"fullName": "Fabrizio Palmas",
"givenName": "Fabrizio",
"surname": "Palmas",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "straightlabs GmbH & Co. KG",
"fullName": "Peter F. J. Niermann",
"givenName": "Peter F. J.",
"surname": "Niermann",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "TU Munich",
"fullName": "David A. Plecher",
"givenName": "David A.",
"surname": "Plecher",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "TU Munich",
"fullName": "Gudrun Klinker",
"givenName": "Gudrun",
"surname": "Klinker",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ismar-adjunct",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "322-326",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-5365-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "536500a315",
"articleId": "1J7Wpsgpk76",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "536500a327",
"articleId": "1J7WbAdfchq",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ucc-companion/2018/0359/0/035900a353",
"title": "A Review of Applications of Extended Reality in the Construction Domain",
"doi": null,
"abstractUrl": "/proceedings-article/ucc-companion/2018/035900a353/17D45WB0qbv",
"parentPublication": {
"id": "proceedings/ucc-companion/2018/0359/0",
"title": "2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apsec/2021/3784/0/378400a572",
"title": "Topic Trends in Issue Tracking System of Extended Reality Frameworks",
"doi": null,
"abstractUrl": "/proceedings-article/apsec/2021/378400a572/1B4m7XRlTcQ",
"parentPublication": {
"id": "proceedings/apsec/2021/3784/0",
"title": "2021 28th Asia-Pacific Software Engineering Conference (APSEC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a419",
"title": "Designing Extended Reality Guidance for Physical Caregiving Tasks",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a419/1CJfkFG7dgA",
"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": "proceedings/cw/2022/6814/0/681400a195",
"title": "Using Extended Reality to Teach Protection of Civilians in Higher Military Education",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2022/681400a195/1I6RMFjiO0U",
"parentPublication": {
"id": "proceedings/cw/2022/6814/0",
"title": "2022 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a254",
"title": "Generative Research in the Context of Academic Extended Reality Research",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a254/1J7WcCweXhC",
"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/mass/2022/7180/0/718000a131",
"title": "Emulating Your eXtended World: An Emulation Environment for XR App Development",
"doi": null,
"abstractUrl": "/proceedings-article/mass/2022/718000a131/1JeEl77BoRy",
"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/icgse/2019/9196/0/919600a080",
"title": "Extended Reality in Global Software Delivery - Towards a Common Fabric of Understanding and Insights",
"doi": null,
"abstractUrl": "/proceedings-article/icgse/2019/919600a080/1cI6t40uIqQ",
"parentPublication": {
"id": "proceedings/icgse/2019/9196/0",
"title": "2019 ACM/IEEE 14th International Conference on Global Software Engineering (ICGSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/issre/2020/9870/0/987000a172",
"title": "An Exploratory Study of Bugs in Extended Reality Applications on the Web",
"doi": null,
"abstractUrl": "/proceedings-article/issre/2020/987000a172/1oFGJBurm48",
"parentPublication": {
"id": "proceedings/issre/2020/9870/0",
"title": "2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a476",
"title": "Designing Virtual Pedagogical Agents and Mentors for Extended Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a476/1yeQC8OgSoU",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a018",
"title": "Accessible Tangible User Interfaces in eXtended Reality Experiences for Cultural Heritage",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a018/1yeQGLRgXHW",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1J7W6LmbCw0",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"acronym": "ismar-adjunct",
"groupId": "9973799",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1J7WcCweXhC",
"doi": "10.1109/ISMAR-Adjunct57072.2022.00056",
"title": "Generative Research in the Context of Academic Extended Reality Research",
"normalizedTitle": "Generative Research in the Context of Academic Extended Reality Research",
"abstract": "As user experience (UX) research has become more formalized in industry research settings, discrepancies in approach and jargon have arisen between industry and academic research, particularly in the field of extended reality (XR). To begin elucidating some of these discrepancies, we conducted a brief investigation into aca-demic XR's acknowledgment of generative research, a type of user research that is exploratory and focuses on understanding users and the problems they face. For our investigation, we searched the digital catalogs of three XR conferences - IEEE ISMAR, IEEE VR, and ACM VRST - with two types of queries: 1) keywords based on generative research and its various names and 2) keywords representing research methods that are often associated with the generative research phase. The results of our searches revealed that the jargon of generative research is rarely explicitly used and that certain generative research methods are under-used by the academic XR community. Based on these results, we recommend that future academic XR researchers explicitly acknowledge the generative research stage. Currently, it is unclear to what degree users of XR are included at various stages of the academic XR user research process. We also recommend that academic XR researchers consider the application of the currently under-utilized research methods. By acknowledging generative research explicitly in the human-centered design process and considering new research methods, we suggest that academic XR researchers may be able to uncover hidden and/or “new” problems related to XR use that may have been otherwise difficult to identify.",
"abstracts": [
{
"abstractType": "Regular",
"content": "As user experience (UX) research has become more formalized in industry research settings, discrepancies in approach and jargon have arisen between industry and academic research, particularly in the field of extended reality (XR). To begin elucidating some of these discrepancies, we conducted a brief investigation into aca-demic XR's acknowledgment of generative research, a type of user research that is exploratory and focuses on understanding users and the problems they face. For our investigation, we searched the digital catalogs of three XR conferences - IEEE ISMAR, IEEE VR, and ACM VRST - with two types of queries: 1) keywords based on generative research and its various names and 2) keywords representing research methods that are often associated with the generative research phase. The results of our searches revealed that the jargon of generative research is rarely explicitly used and that certain generative research methods are under-used by the academic XR community. Based on these results, we recommend that future academic XR researchers explicitly acknowledge the generative research stage. Currently, it is unclear to what degree users of XR are included at various stages of the academic XR user research process. We also recommend that academic XR researchers consider the application of the currently under-utilized research methods. By acknowledging generative research explicitly in the human-centered design process and considering new research methods, we suggest that academic XR researchers may be able to uncover hidden and/or “new” problems related to XR use that may have been otherwise difficult to identify.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "As user experience (UX) research has become more formalized in industry research settings, discrepancies in approach and jargon have arisen between industry and academic research, particularly in the field of extended reality (XR). To begin elucidating some of these discrepancies, we conducted a brief investigation into aca-demic XR's acknowledgment of generative research, a type of user research that is exploratory and focuses on understanding users and the problems they face. For our investigation, we searched the digital catalogs of three XR conferences - IEEE ISMAR, IEEE VR, and ACM VRST - with two types of queries: 1) keywords based on generative research and its various names and 2) keywords representing research methods that are often associated with the generative research phase. The results of our searches revealed that the jargon of generative research is rarely explicitly used and that certain generative research methods are under-used by the academic XR community. Based on these results, we recommend that future academic XR researchers explicitly acknowledge the generative research stage. Currently, it is unclear to what degree users of XR are included at various stages of the academic XR user research process. We also recommend that academic XR researchers consider the application of the currently under-utilized research methods. By acknowledging generative research explicitly in the human-centered design process and considering new research methods, we suggest that academic XR researchers may be able to uncover hidden and/or “new” problems related to XR use that may have been otherwise difficult to identify.",
"fno": "536500a254",
"keywords": [
"Groupware",
"Human Computer Interaction",
"Internet",
"User Centred Design",
"User Experience",
"Virtual Reality",
"Academic Extended Reality Research",
"Academic XR Community",
"Academic XR User Research Process",
"Digital Catalogs",
"Generative Research Phase",
"Human Centered Design Process",
"Industry Research Settings",
"User Experience Research",
"Industries",
"Head Mounted Displays",
"Extended Reality",
"Hardware",
"X Reality",
"Faces",
"H 5 1 Information Interfaces And Presentation",
"Multimedia Information Systems Artificial Augmented And Virtual Realities",
"H 5 2 Information Interfaces And Presentation User Interfaces User Centered Design"
],
"authors": [
{
"affiliation": "University of Central,Florida",
"fullName": "Stephanie Carnell",
"givenName": "Stephanie",
"surname": "Carnell",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Central,Florida",
"fullName": "Dirk Reiners",
"givenName": "Dirk",
"surname": "Reiners",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Central,Florida",
"fullName": "Carolina Cruz-Neira",
"givenName": "Carolina",
"surname": "Cruz-Neira",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ismar-adjunct",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "254-257",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-5365-3",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "536500a249",
"articleId": "1J7WceEw2di",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "536500a258",
"articleId": "1J7WxzHZHry",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ucc-companion/2018/0359/0/035900a353",
"title": "A Review of Applications of Extended Reality in the Construction Domain",
"doi": null,
"abstractUrl": "/proceedings-article/ucc-companion/2018/035900a353/17D45WB0qbv",
"parentPublication": {
"id": "proceedings/ucc-companion/2018/0359/0",
"title": "2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iiswc/2021/4173/0/417300a024",
"title": "ILLIXR: Enabling End-to-End Extended Reality Research",
"doi": null,
"abstractUrl": "/proceedings-article/iiswc/2021/417300a024/1A8gldXRikU",
"parentPublication": {
"id": "proceedings/iiswc/2021/4173/0",
"title": "2021 IEEE International Symposium on Workload Characterization (IISWC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apsec/2021/3784/0/378400a572",
"title": "Topic Trends in Issue Tracking System of Extended Reality Frameworks",
"doi": null,
"abstractUrl": "/proceedings-article/apsec/2021/378400a572/1B4m7XRlTcQ",
"parentPublication": {
"id": "proceedings/apsec/2021/3784/0",
"title": "2021 28th Asia-Pacific Software Engineering Conference (APSEC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/mi/2022/04/09741292",
"title": "ILLIXR: An Open Testbed to Enable Extended Reality Systems Research",
"doi": null,
"abstractUrl": "/magazine/mi/2022/04/09741292/1C0jifhs3DO",
"parentPublication": {
"id": "mags/mi",
"title": "IEEE Micro",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a419",
"title": "Designing Extended Reality Guidance for Physical Caregiving Tasks",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a419/1CJfkFG7dgA",
"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": "proceedings/cw/2022/6814/0/681400a195",
"title": "Using Extended Reality to Teach Protection of Civilians in Higher Military Education",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2022/681400a195/1I6RMFjiO0U",
"parentPublication": {
"id": "proceedings/cw/2022/6814/0",
"title": "2022 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a322",
"title": "Extended Reality Training for Business and Education: The New Generation of Learning Experiences",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a322/1J7W77jxOlq",
"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/issre/2020/9870/0/987000a172",
"title": "An Exploratory Study of Bugs in Extended Reality Applications on the Web",
"doi": null,
"abstractUrl": "/proceedings-article/issre/2020/987000a172/1oFGJBurm48",
"parentPublication": {
"id": "proceedings/issre/2020/9870/0",
"title": "2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a476",
"title": "Designing Virtual Pedagogical Agents and Mentors for Extended Reality",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a476/1yeQC8OgSoU",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a018",
"title": "Accessible Tangible User Interfaces in eXtended Reality Experiences for Cultural Heritage",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a018/1yeQGLRgXHW",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1JjykdQLNW8",
"title": "2022 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)",
"acronym": "chase",
"groupId": "9983536",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1JjyrslgV0c",
"doi": null,
"title": "An Improved Framework to Assess the Evaluation of Extended Reality Healthcare Simulators using Machine Learning",
"normalizedTitle": "An Improved Framework to Assess the Evaluation of Extended Reality Healthcare Simulators using Machine Learning",
"abstract": "In this paper, an improved machine learning framework for the assessment of Extended Reality (XR) based simulators is presented. The simulators in focus are healthcare simulators development for training and education of medical residents and students. Machine learning (ML) has been used by many researchers to assess medical simulators. However, there is a lack of standard when conducting such an assessment. Some researchers have also investigated the standardization of the assessment process using ML, but they are limited to virtual reality. In this paper, the objective is to develop an improved Framework encompassing assessment processes for Virtual, Mixed and Augmented Reality based simulators and various ML models.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In this paper, an improved machine learning framework for the assessment of Extended Reality (XR) based simulators is presented. The simulators in focus are healthcare simulators development for training and education of medical residents and students. Machine learning (ML) has been used by many researchers to assess medical simulators. However, there is a lack of standard when conducting such an assessment. Some researchers have also investigated the standardization of the assessment process using ML, but they are limited to virtual reality. In this paper, the objective is to develop an improved Framework encompassing assessment processes for Virtual, Mixed and Augmented Reality based simulators and various ML models.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In this paper, an improved machine learning framework for the assessment of Extended Reality (XR) based simulators is presented. The simulators in focus are healthcare simulators development for training and education of medical residents and students. Machine learning (ML) has been used by many researchers to assess medical simulators. However, there is a lack of standard when conducting such an assessment. Some researchers have also investigated the standardization of the assessment process using ML, but they are limited to virtual reality. In this paper, the objective is to develop an improved Framework encompassing assessment processes for Virtual, Mixed and Augmented Reality based simulators and various ML models.",
"fno": "947600a188",
"keywords": [
"Augmented Reality",
"Computer Based Training",
"Health Care",
"Learning Artificial Intelligence",
"Medical Computing",
"Virtual Reality",
"Education",
"Extended Reality Based Simulators",
"Extended Reality Healthcare Simulators",
"Healthcare Simulators Development",
"Improved Framework Encompassing Assessment Processes",
"Improved Machine",
"Machine Learning",
"Medical Residents",
"Medical Simulators",
"ML",
"Virtual Reality",
"Training",
"Solid Modeling",
"Extended Reality",
"Medical Simulation",
"Surgery",
"Machine Learning",
"Medical Services",
"Machine Learning",
"Extended Reality",
"Virtual Reality",
"Mixed Reality",
"Augmented Reality",
"Simulator",
"Healthcare",
"Surgery"
],
"authors": [
{
"affiliation": "University of Illinois Urbana-Champaign,Champaign,Illinois,USA",
"fullName": "Avinash Gupta",
"givenName": "Avinash",
"surname": "Gupta",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "University of Illinois Urbana-Champaign,Champaign,Illinois,USA",
"fullName": "Harris Nisar",
"givenName": "Harris",
"surname": "Nisar",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "chase",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-11-01T00:00:00",
"pubType": "proceedings",
"pages": "188-192",
"year": "2022",
"issn": null,
"isbn": "978-1-4503-9476-5",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "947600a186",
"articleId": "1JjytC6Bala",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "947600a193",
"articleId": "1Jjyn7a9emY",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/mvhi/2010/4009/0/4009a377",
"title": "Simulation of Blood Vessels for Surgery Simulators",
"doi": null,
"abstractUrl": "/proceedings-article/mvhi/2010/4009a377/12OmNAXxXf6",
"parentPublication": {
"id": "proceedings/mvhi/2010/4009/0",
"title": "Machine Vision and Human-machine Interface, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/svr/2013/5001/0/06655790",
"title": "Evaluation of Collaborative Activities in Medical Simulators Based on Virtual Reality",
"doi": null,
"abstractUrl": "/proceedings-article/svr/2013/06655790/12OmNAlvI6p",
"parentPublication": {
"id": "proceedings/svr/2013/5001/0",
"title": "2013 XV Symposium on Virtual and Augmented Reality (SVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vr/2017/6647/0/07892354",
"title": "Optical see-through vs. spatial augmented reality simulators for medical applications",
"doi": null,
"abstractUrl": "/proceedings-article/vr/2017/07892354/12OmNB1wkLS",
"parentPublication": {
"id": "proceedings/vr/2017/6647/0",
"title": "2017 IEEE Virtual Reality (VR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/svr/2015/7204/0/7204a092",
"title": "Metrics for User Assessment in Simulators Based on VR",
"doi": null,
"abstractUrl": "/proceedings-article/svr/2015/7204a092/12OmNCykm8v",
"parentPublication": {
"id": "proceedings/svr/2015/7204/0",
"title": "2015 XVII Symposium on Virtual and Augmented Reality (SVR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iciev-iscmht/2017/1023/0/08338542",
"title": "Medical robots and simulators",
"doi": null,
"abstractUrl": "/proceedings-article/iciev-iscmht/2017/08338542/12OmNzxPTPB",
"parentPublication": {
"id": "proceedings/iciev-iscmht/2017/1023/0",
"title": "2017 6th International Conference on Informatics, Electronics and Vision & 2017 7th International Symposium in Computational Medical and Health Technology (ICIEV-ISCMHT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "mags/cg/2006/06/mcg2006060022",
"title": "Guest Editors' Introduction: Simulators and Closed Interaction Loops",
"doi": null,
"abstractUrl": "/magazine/cg/2006/06/mcg2006060022/13rRUxNmPLb",
"parentPublication": {
"id": "mags/cg",
"title": "IEEE Computer Graphics and Applications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ucc-companion/2018/0359/0/035900a353",
"title": "A Review of Applications of Extended Reality in the Construction Domain",
"doi": null,
"abstractUrl": "/proceedings-article/ucc-companion/2018/035900a353/17D45WB0qbv",
"parentPublication": {
"id": "proceedings/ucc-companion/2018/0359/0",
"title": "2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a652",
"title": "Role of Dynamic Affordance and Cognitive Load in the Design of Extended Reality based Simulation Environments for Surgical Contexts",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a652/1CJdQCrNADm",
"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": "proceedings/itei/2021/8050/0/805000a219",
"title": "Application of virtual reality technology in experimental teaching of medical specialty",
"doi": null,
"abstractUrl": "/proceedings-article/itei/2021/805000a219/1CzeGNTNNsI",
"parentPublication": {
"id": "proceedings/itei/2021/8050/0",
"title": "2021 3rd International Conference on Internet Technology and Educational Informization (ITEI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tg/5555/01/09772329",
"title": "Using Extended Reality in Flight Simulators: A Literature Review",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09772329/1DgjDn5nymI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1JrQPhTSspy",
"title": "2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)",
"acronym": "ismar",
"groupId": "1000465",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1JrQS43SrFC",
"doi": "10.1109/ISMAR55827.2022.00023",
"title": "A Literature Review of User Studies in Extended Reality Applications for Archaeology",
"normalizedTitle": "A Literature Review of User Studies in Extended Reality Applications for Archaeology",
"abstract": "In the present study we conducted a systematic review on user studies for Archaeology in eXtended Reality of the last 10 years. After a screening and selection process, 52 articles were selected for an in-depth analysis. Their classification follows different axes: devices, location dependency, type of users, interaction and collaboration. We also organised the existing user studies according to tasks, evaluation measurements, number of participants, and how the study was conducted (pre-test and/or post-test, formative and summative evaluation, quantitative and qualitative data). We found an intertwined relation between Archaeology and Cultural Heritage, which is reflected in the vast presence of applications for museum exhibitions and tours on archaeological sites. Similarities between systems developed for archaeologists and for general public were also investigated. Our purpose was to find a common ground between different user studies that could help designers of the next systems have a base on which they can build their system. We also highlighted which would be the preferred and most suitable evaluation techniques, when they are needed, with the type of users to address. The results show a heterogeneity of measurable variables and possible choices, but some guidelines could be derived.",
"abstracts": [
{
"abstractType": "Regular",
"content": "In the present study we conducted a systematic review on user studies for Archaeology in eXtended Reality of the last 10 years. After a screening and selection process, 52 articles were selected for an in-depth analysis. Their classification follows different axes: devices, location dependency, type of users, interaction and collaboration. We also organised the existing user studies according to tasks, evaluation measurements, number of participants, and how the study was conducted (pre-test and/or post-test, formative and summative evaluation, quantitative and qualitative data). We found an intertwined relation between Archaeology and Cultural Heritage, which is reflected in the vast presence of applications for museum exhibitions and tours on archaeological sites. Similarities between systems developed for archaeologists and for general public were also investigated. Our purpose was to find a common ground between different user studies that could help designers of the next systems have a base on which they can build their system. We also highlighted which would be the preferred and most suitable evaluation techniques, when they are needed, with the type of users to address. The results show a heterogeneity of measurable variables and possible choices, but some guidelines could be derived.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "In the present study we conducted a systematic review on user studies for Archaeology in eXtended Reality of the last 10 years. After a screening and selection process, 52 articles were selected for an in-depth analysis. Their classification follows different axes: devices, location dependency, type of users, interaction and collaboration. We also organised the existing user studies according to tasks, evaluation measurements, number of participants, and how the study was conducted (pre-test and/or post-test, formative and summative evaluation, quantitative and qualitative data). We found an intertwined relation between Archaeology and Cultural Heritage, which is reflected in the vast presence of applications for museum exhibitions and tours on archaeological sites. Similarities between systems developed for archaeologists and for general public were also investigated. Our purpose was to find a common ground between different user studies that could help designers of the next systems have a base on which they can build their system. We also highlighted which would be the preferred and most suitable evaluation techniques, when they are needed, with the type of users to address. The results show a heterogeneity of measurable variables and possible choices, but some guidelines could be derived.",
"fno": "532500a092",
"keywords": [
"Archaeology",
"History",
"Human Computer Interaction",
"Museums",
"User Interfaces",
"Virtual Reality",
"Archaeological Sites",
"Archaeology",
"Different Axes",
"Different User Studies",
"Evaluation Measurements",
"Existing User Studies",
"Extended Reality Applications",
"Literature Review",
"Most Suitable Evaluation Techniques",
"Pre Test",
"Preferred Evaluation Techniques",
"Screening",
"Selection Process",
"Systematic Review",
"Archeology",
"Systematics",
"Extended Reality",
"Bibliographies",
"Collaboration",
"Particle Measurements",
"Museums",
"Human Centered Computing",
"Human Computer Interaction HCI",
"HCI Design And Evaluation Methods",
"User Studies",
"Interaction Paradigms",
"Virtual Reality Mixed Or Augmented Reality",
"Applied Computing",
"Physical Sciences And Engineering",
"Archaeology"
],
"authors": [
{
"affiliation": "Université Paris-Saclay, CNRS, LISN, VENISE team,Orsay,France",
"fullName": "Michele De Bonis",
"givenName": "Michele De",
"surname": "Bonis",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Université Paris-Saclay, CNRS, LISN, VENISE team,Orsay,France",
"fullName": "Huyen Nguyen",
"givenName": "Huyen",
"surname": "Nguyen",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Université Paris-Saclay, CNRS, LISN, VENISE team,Orsay,France",
"fullName": "Patrick Bourdot",
"givenName": "Patrick",
"surname": "Bourdot",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ismar",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-10-01T00:00:00",
"pubType": "proceedings",
"pages": "92-101",
"year": "2022",
"issn": "1554-7868",
"isbn": "978-1-6654-5325-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "532500a082",
"articleId": "1JrQQ8dsLKM",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "532500a102",
"articleId": "1JrRiazvJ1m",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/seaa/2016/2820/0/2820a181",
"title": "Literature Review of Empirical Research Studies within the Domain of Acceptance Testing",
"doi": null,
"abstractUrl": "/proceedings-article/seaa/2016/2820a181/12OmNAu1Fky",
"parentPublication": {
"id": "proceedings/seaa/2016/2820/0",
"title": "2016 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apsec/2017/3681/0/3681a041",
"title": "Text-Mining Techniques and Tools for Systematic Literature Reviews: A Systematic Literature Review",
"doi": null,
"abstractUrl": "/proceedings-article/apsec/2017/3681a041/12OmNBlofPT",
"parentPublication": {
"id": "proceedings/apsec/2017/3681/0",
"title": "2017 24th Asia-Pacific Software Engineering Conference (APSEC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/eecs/2017/2085/0/2085a198",
"title": "Educational Process Mining: A Systematic Literature Review",
"doi": null,
"abstractUrl": "/proceedings-article/eecs/2017/2085a198/12OmNyKrHak",
"parentPublication": {
"id": "proceedings/eecs/2017/2085/0",
"title": "2017 European Conference on Electrical Engineering and Computer Science (EECS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/edocw/2017/1568/0/1568a041",
"title": "Defining Enterprise Architecture: A Systematic Literature Review",
"doi": null,
"abstractUrl": "/proceedings-article/edocw/2017/1568a041/12OmNzxPTMA",
"parentPublication": {
"id": "proceedings/edocw/2017/1568/0",
"title": "2017 IEEE 21st International Enterprise Distributed Object Computing Workshop (EDOCW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icse-companion/2018/5663/0/566301a418",
"title": "Poster: A Systematic Literature Review to Support the Selection of User Acceptance Testing Techniques",
"doi": null,
"abstractUrl": "/proceedings-article/icse-companion/2018/566301a418/13bd1eNNYnx",
"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/ts/2017/09/07779159",
"title": "Reporting Usability Defects: A Systematic Literature Review",
"doi": null,
"abstractUrl": "/journal/ts/2017/09/07779159/13rRUIIVlel",
"parentPublication": {
"id": "trans/ts",
"title": "IEEE Transactions on Software Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/issrew/2021/2603/0/260300a304",
"title": "Online Log Parsing: Preliminary Literature Review",
"doi": null,
"abstractUrl": "/proceedings-article/issrew/2021/260300a304/1AZO8U8bOkU",
"parentPublication": {
"id": "proceedings/issrew/2021/2603/0",
"title": "2021 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/se4rai/2022/9319/0/931900a001",
"title": "Operationalizing Machine Learning Models - A Systematic Literature Review",
"doi": null,
"abstractUrl": "/proceedings-article/se4rai/2022/931900a001/1ED20Ql4AIo",
"parentPublication": {
"id": "proceedings/se4rai/2022/9319/0",
"title": "2022 IEEE/ACM 1st International Workshop on Software Engineering for Responsible Artificial Intelligence (SE4RAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iisa/2022/6390/0/09904356",
"title": "ARCHAEORAMA: Proposing a multimodal application for the documentation of archaeological excavations in situ",
"doi": null,
"abstractUrl": "/proceedings-article/iisa/2022/09904356/1H5KvrXcSD6",
"parentPublication": {
"id": "proceedings/iisa/2022/6390/0",
"title": "2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icalt/2020/6090/0/09156050",
"title": "AI in Cybersecurity Education- A Systematic Literature Review of Studies on Cybersecurity MOOCs",
"doi": null,
"abstractUrl": "/proceedings-article/icalt/2020/09156050/1m1j13h7BKg",
"parentPublication": {
"id": "proceedings/icalt/2020/6090/0",
"title": "2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1yfxDjRGMmc",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"acronym": "ismar-adjunct",
"groupId": "1810084",
"volume": "0",
"displayVolume": "0",
"year": "2021",
"__typename": "ProceedingType"
},
"article": {
"id": "1yeQC8OgSoU",
"doi": "10.1109/ISMAR-Adjunct54149.2021.00112",
"title": "Designing Virtual Pedagogical Agents and Mentors for Extended Reality",
"normalizedTitle": "Designing Virtual Pedagogical Agents and Mentors for Extended Reality",
"abstract": "The use of virtual and augmented reality for educational purposes has seen a rapid increase in interest in recent years. Extended reality offers unique affordances to learners, and can enhance learning. Specifically, we are interested in the use of pedagogical agents in extended reality due to their potential to increase student motivation and learning. However, the design of pedagogical agents in extended reality is still a nascent area of study, which can be important in an immersive environment where social cues can be more salient. Pedagogical agent design aspects such as speech, appearance, and modality can prime social cues and affect learning outcomes and instructor perception. In this paper, we propose a project to investigate auditory and visual social cues of pedagogical agents in XR such as speech, ethnicity, and modality.",
"abstracts": [
{
"abstractType": "Regular",
"content": "The use of virtual and augmented reality for educational purposes has seen a rapid increase in interest in recent years. Extended reality offers unique affordances to learners, and can enhance learning. Specifically, we are interested in the use of pedagogical agents in extended reality due to their potential to increase student motivation and learning. However, the design of pedagogical agents in extended reality is still a nascent area of study, which can be important in an immersive environment where social cues can be more salient. Pedagogical agent design aspects such as speech, appearance, and modality can prime social cues and affect learning outcomes and instructor perception. In this paper, we propose a project to investigate auditory and visual social cues of pedagogical agents in XR such as speech, ethnicity, and modality.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "The use of virtual and augmented reality for educational purposes has seen a rapid increase in interest in recent years. Extended reality offers unique affordances to learners, and can enhance learning. Specifically, we are interested in the use of pedagogical agents in extended reality due to their potential to increase student motivation and learning. However, the design of pedagogical agents in extended reality is still a nascent area of study, which can be important in an immersive environment where social cues can be more salient. Pedagogical agent design aspects such as speech, appearance, and modality can prime social cues and affect learning outcomes and instructor perception. In this paper, we propose a project to investigate auditory and visual social cues of pedagogical agents in XR such as speech, ethnicity, and modality.",
"fno": "129800a476",
"keywords": [
"Augmented Reality",
"Computer Aided Instruction",
"Extended Reality",
"Pedagogical Agent Design Aspects",
"Virtual Pedagogical Agents",
"Virtual Reality",
"Augmented Reality",
"Student Motivation",
"Student Learning",
"Social Cues",
"XR",
"Visualization",
"Extended Reality",
"Affordances",
"X Reality",
"Computing Methodologies",
"Computer Graphics",
"Graphics Systems And Interfaces",
"Mixed Augmented Reality",
"Applied Computing",
"Education",
"Interactive Learning Environments"
],
"authors": [
{
"affiliation": "University of Central Florida",
"fullName": "Tiffany D. Do",
"givenName": "Tiffany D.",
"surname": "Do",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "ismar-adjunct",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2021-10-01T00:00:00",
"pubType": "proceedings",
"pages": "476-479",
"year": "2021",
"issn": null,
"isbn": "978-1-6654-1298-8",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "129800a473",
"articleId": "1yeQCejb7Co",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "129800a480",
"articleId": "1yfxLCQRUBi",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/ucc-companion/2018/0359/0/035900a353",
"title": "A Review of Applications of Extended Reality in the Construction Domain",
"doi": null,
"abstractUrl": "/proceedings-article/ucc-companion/2018/035900a353/17D45WB0qbv",
"parentPublication": {
"id": "proceedings/ucc-companion/2018/0359/0",
"title": "2018 IEEE/ACM International Conference on Utility and Cloud Computing Companion (UCC Companion)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/apsec/2021/3784/0/378400a572",
"title": "Topic Trends in Issue Tracking System of Extended Reality Frameworks",
"doi": null,
"abstractUrl": "/proceedings-article/apsec/2021/378400a572/1B4m7XRlTcQ",
"parentPublication": {
"id": "proceedings/apsec/2021/3784/0",
"title": "2021 28th Asia-Pacific Software Engineering Conference (APSEC)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/vrw/2022/8402/0/840200a163",
"title": "Extended Reality and Internet of Things for Hyper-Connected Metaverse Environments",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a163/1CJcCfnUSbK",
"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": "proceedings/vrw/2022/8402/0/840200a554",
"title": "Absence Agents: Mitigating Interruptions in Extended Reality Remote Collaboration",
"doi": null,
"abstractUrl": "/proceedings-article/vrw/2022/840200a554/1CJdFFKBZfi",
"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/5555/01/09772329",
"title": "Using Extended Reality in Flight Simulators: A Literature Review",
"doi": null,
"abstractUrl": "/journal/tg/5555/01/09772329/1DgjDn5nymI",
"parentPublication": {
"id": "trans/tg",
"title": "IEEE Transactions on Visualization & Computer Graphics",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cw/2022/6814/0/681400a195",
"title": "Using Extended Reality to Teach Protection of Civilians in Higher Military Education",
"doi": null,
"abstractUrl": "/proceedings-article/cw/2022/681400a195/1I6RMFjiO0U",
"parentPublication": {
"id": "proceedings/cw/2022/6814/0",
"title": "2022 International Conference on Cyberworlds (CW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2022/5365/0/536500a322",
"title": "Extended Reality Training for Business and Education: The New Generation of Learning Experiences",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a322/1J7W77jxOlq",
"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/2022/5365/0/536500a710",
"title": "Ex-Cit XR: Expert-elicitation of XR Techniques for Disengaging from IVEs",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2022/536500a710/1J7WgdWP768",
"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/2021/1298/0/129800a018",
"title": "Accessible Tangible User Interfaces in eXtended Reality Experiences for Cultural Heritage",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a018/1yeQGLRgXHW",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ismar-adjunct/2021/1298/0/129800a254",
"title": "Designing an Extended Reality Application to Expand Clinic-Based Sensory Strategies for Autistic Children Requiring Substantial Support: Participation of Practitioners",
"doi": null,
"abstractUrl": "/proceedings-article/ismar-adjunct/2021/129800a254/1yeQH3JIyDS",
"parentPublication": {
"id": "proceedings/ismar-adjunct/2021/1298/0",
"title": "2021 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNsbGvCQ",
"title": "2016 30th International Conference on Advanced Information Networking and Applications Workshops (WAINA)",
"acronym": "waina",
"groupId": "1001766",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNAYoKjL",
"doi": "10.1109/WAINA.2016.69",
"title": "Towards Data Interoperability: Turning Domain Specific Knowledge to Agnostic across the Data Lifecycle",
"normalizedTitle": "Towards Data Interoperability: Turning Domain Specific Knowledge to Agnostic across the Data Lifecycle",
"abstract": "Today's rich digital environment is characterised by the exponential increase of the amount of \"born digital\" data, following the penetration of real (e.g. sensors, wearable devices, etc.) and virtual (e.g. online platforms, user generated content, etc.) Internet connected sources. While the majority of the research outcomes is focused on the processing and connectivity aspects, a key question relates to data utilization in cross-application cases: If everything is connected and identified uniquely, how is it possible to use the data from a sensor of an unidentified domain in a different application domain? In this paper an approach enabling the interconnection and utilization of domain specific data to a considerably different domain is presented. A functional scenario of that approach is proposed, trying to address the challenges and the needs emerging in the Internet of Things era, from a view point of increasing data utilization out of a specific's data lifecycle. Semantic data interoperability, integration, annotation, management, discovery, and analysis are issues being considered in the proposed approach.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Today's rich digital environment is characterised by the exponential increase of the amount of \"born digital\" data, following the penetration of real (e.g. sensors, wearable devices, etc.) and virtual (e.g. online platforms, user generated content, etc.) Internet connected sources. While the majority of the research outcomes is focused on the processing and connectivity aspects, a key question relates to data utilization in cross-application cases: If everything is connected and identified uniquely, how is it possible to use the data from a sensor of an unidentified domain in a different application domain? In this paper an approach enabling the interconnection and utilization of domain specific data to a considerably different domain is presented. A functional scenario of that approach is proposed, trying to address the challenges and the needs emerging in the Internet of Things era, from a view point of increasing data utilization out of a specific's data lifecycle. Semantic data interoperability, integration, annotation, management, discovery, and analysis are issues being considered in the proposed approach.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Today's rich digital environment is characterised by the exponential increase of the amount of \"born digital\" data, following the penetration of real (e.g. sensors, wearable devices, etc.) and virtual (e.g. online platforms, user generated content, etc.) Internet connected sources. While the majority of the research outcomes is focused on the processing and connectivity aspects, a key question relates to data utilization in cross-application cases: If everything is connected and identified uniquely, how is it possible to use the data from a sensor of an unidentified domain in a different application domain? In this paper an approach enabling the interconnection and utilization of domain specific data to a considerably different domain is presented. A functional scenario of that approach is proposed, trying to address the challenges and the needs emerging in the Internet of Things era, from a view point of increasing data utilization out of a specific's data lifecycle. Semantic data interoperability, integration, annotation, management, discovery, and analysis are issues being considered in the proposed approach.",
"fno": "2461a109",
"keywords": [
"Interoperability",
"Sensors",
"Semantics",
"Internet",
"Data Models",
"DSL",
"Middleware",
"Domain Specific",
"Semantics",
"Interoperability",
"Domain Agnostic"
],
"authors": [
{
"affiliation": null,
"fullName": "Athanasios Kiourtis",
"givenName": "Athanasios",
"surname": "Kiourtis",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Argyro Mavrogiorgou",
"givenName": "Argyro",
"surname": "Mavrogiorgou",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Dimosthenis Kyriazis",
"givenName": "Dimosthenis",
"surname": "Kyriazis",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Ilias Maglogiannis",
"givenName": "Ilias",
"surname": "Maglogiannis",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Marinos Themistocleous",
"givenName": "Marinos",
"surname": "Themistocleous",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "waina",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-03-01T00:00:00",
"pubType": "proceedings",
"pages": "109-114",
"year": "2016",
"issn": null,
"isbn": "978-1-5090-2461-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "2461a103",
"articleId": "12OmNvAAtuY",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "2461a115",
"articleId": "12OmNyyeWvR",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/aiccsa/2017/3581/0/3581b470",
"title": "HealthIoT Ontology for Data Semantic Representation and Interpretation Obtained from Medical Connected Objects",
"doi": null,
"abstractUrl": "/proceedings-article/aiccsa/2017/3581b470/12OmNrFTr9F",
"parentPublication": {
"id": "proceedings/aiccsa/2017/3581/0",
"title": "2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/compsacw/2014/3578/0/3578a528",
"title": "Integrating the Modelica DSL into a Platform for Model-Based Tool Interoperability",
"doi": null,
"abstractUrl": "/proceedings-article/compsacw/2014/3578a528/12OmNrGb2c4",
"parentPublication": {
"id": "proceedings/compsacw/2014/3578/0",
"title": "2014 IEEE 38th International Computer Software and Applications Conference Workshops (COMPSACW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ms/2015/7284/0/7284a313",
"title": "Semantic Gateway as a Service Architecture for IoT Interoperability",
"doi": null,
"abstractUrl": "/proceedings-article/ms/2015/7284a313/12OmNwDSduF",
"parentPublication": {
"id": "proceedings/ms/2015/7284/0",
"title": "2015 IEEE International Conference on Mobile Services (MS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/smartcomp/2018/4705/0/470501a434",
"title": "Interoperability in the Smart City: A Semantic Approach for Merging Flexibility with Strictness",
"doi": null,
"abstractUrl": "/proceedings-article/smartcomp/2018/470501a434/12OmNyGtjff",
"parentPublication": {
"id": "proceedings/smartcomp/2018/4705/0",
"title": "2018 IEEE International Conference on Smart Computing (SMARTCOMP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ichi/2015/9548/0/9548a463",
"title": "Providing Full Semantic Interoperability for the Fast Healthcare Interoperability Resources Schemas with Resource Description Framework",
"doi": null,
"abstractUrl": "/proceedings-article/ichi/2015/9548a463/12OmNyugySO",
"parentPublication": {
"id": "proceedings/ichi/2015/9548/0",
"title": "2015 International Conference on Healthcare Informatics (ICHI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cloud/2018/7235/0/723501a958",
"title": "A Cloud-Agnostic Container Orchestrator for Improving Interoperability",
"doi": null,
"abstractUrl": "/proceedings-article/cloud/2018/723501a958/13xI8AsfhNH",
"parentPublication": {
"id": "proceedings/cloud/2018/7235/0",
"title": "2018 IEEE 11th International Conference on Cloud Computing (CLOUD)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ickg/2022/5101/0/510100a071",
"title": "An Architecture and a Methodology Enabling Interoperability within and across Universities",
"doi": null,
"abstractUrl": "/proceedings-article/ickg/2022/510100a071/1KxTV6xfkFG",
"parentPublication": {
"id": "proceedings/ickg/2022/5101/0",
"title": "2022 IEEE International Conference on Knowledge Graph (ICKG)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icsa-c/2019/1876/0/08712380",
"title": "Reinforcement Learning for IoT Interoperability",
"doi": null,
"abstractUrl": "/proceedings-article/icsa-c/2019/08712380/1a3x1BDajyU",
"parentPublication": {
"id": "proceedings/icsa-c/2019/1876/0",
"title": "2019 IEEE International Conference on Software Architecture Companion (ICSA-C)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iccvw/2019/5023/0/502300d227",
"title": "Hallucinating Agnostic Images to Generalize Across Domains",
"doi": null,
"abstractUrl": "/proceedings-article/iccvw/2019/502300d227/1i5mCc7GXcc",
"parentPublication": {
"id": "proceedings/iccvw/2019/5023/0",
"title": "2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/seaa/2021/2705/0/270500a214",
"title": "StalkCD: A Model-Driven Framework for Interoperability and Analysis of CI/CD Pipelines",
"doi": null,
"abstractUrl": "/proceedings-article/seaa/2021/270500a214/1y2JyvFBroY",
"parentPublication": {
"id": "proceedings/seaa/2021/2705/0",
"title": "2021 47th Euromicro Conference on Software Engineering and Advanced Applications (SEAA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "12OmNzuZUzq",
"title": "2016 IEEE 16th International Conference on Data Mining (ICDM)",
"acronym": "icdm",
"groupId": "1000179",
"volume": "0",
"displayVolume": "0",
"year": "2016",
"__typename": "ProceedingType"
},
"article": {
"id": "12OmNCfjeBN",
"doi": "10.1109/ICDM.2016.0171",
"title": "Bayesian Rule Sets for Interpretable Classification",
"normalizedTitle": "Bayesian Rule Sets for Interpretable Classification",
"abstract": "A Rule Set model consists of a small number of short rules for interpretable classification, where an instance is classified as positive if it satisfies at least one of the rules. The rule set provides reasons for predictions, and also descriptions of a particular class. We present a Bayesian framework for learning Rule Set models, with prior parameters that the user can set to encourage the model to have a desired size and shape in order to conform with a domain-specific definition of interpretability. We use an efficient inference approach for searching for the MAP solution and provide theoretical bounds to reduce computation. We apply Rule Set models to ten UCI data sets and compare the performance with other interpretable and non-interpretable models.",
"abstracts": [
{
"abstractType": "Regular",
"content": "A Rule Set model consists of a small number of short rules for interpretable classification, where an instance is classified as positive if it satisfies at least one of the rules. The rule set provides reasons for predictions, and also descriptions of a particular class. We present a Bayesian framework for learning Rule Set models, with prior parameters that the user can set to encourage the model to have a desired size and shape in order to conform with a domain-specific definition of interpretability. We use an efficient inference approach for searching for the MAP solution and provide theoretical bounds to reduce computation. We apply Rule Set models to ten UCI data sets and compare the performance with other interpretable and non-interpretable models.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "A Rule Set model consists of a small number of short rules for interpretable classification, where an instance is classified as positive if it satisfies at least one of the rules. The rule set provides reasons for predictions, and also descriptions of a particular class. We present a Bayesian framework for learning Rule Set models, with prior parameters that the user can set to encourage the model to have a desired size and shape in order to conform with a domain-specific definition of interpretability. We use an efficient inference approach for searching for the MAP solution and provide theoretical bounds to reduce computation. We apply Rule Set models to ten UCI data sets and compare the performance with other interpretable and non-interpretable models.",
"fno": "07837984",
"keywords": [
"Bayes Methods",
"Inference Mechanisms",
"Learning Artificial Intelligence",
"Pattern Classification",
"Bayesian Rule Sets",
"Interpretable Classification",
"Learning Rule Set Models",
"Domain Specific Interpretability Definition",
"Inference Approach",
"MAP",
"UCI Data Sets",
"Bayes Methods",
"Computational Modeling",
"Data Models",
"Simulated Annealing",
"Search Problems",
"Predictive Models",
"Data Mining",
"Interpretable Machine Learning",
"Association Rules",
"Classifier",
"Bayesian Modeling"
],
"authors": [
{
"affiliation": null,
"fullName": "Tong Wang",
"givenName": "Tong",
"surname": "Wang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Cynthia Rudin",
"givenName": "Cynthia",
"surname": "Rudin",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Finale Velez-Doshi",
"givenName": "Finale",
"surname": "Velez-Doshi",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Yimin Liu",
"givenName": "Yimin",
"surname": "Liu",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Erica Klampfl",
"givenName": "Erica",
"surname": "Klampfl",
"__typename": "ArticleAuthorType"
},
{
"affiliation": null,
"fullName": "Perry MacNeille",
"givenName": "Perry",
"surname": "MacNeille",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2016-12-01T00:00:00",
"pubType": "proceedings",
"pages": "1269-1274",
"year": "2016",
"issn": "2374-8486",
"isbn": "978-1-5090-5473-2",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "07837983",
"articleId": "12OmNwcUjXv",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "07837985",
"articleId": "12OmNvsDHHO",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icpr/2014/5209/0/5209d576",
"title": "VC-Dimension of Rule Sets",
"doi": null,
"abstractUrl": "/proceedings-article/icpr/2014/5209d576/12OmNwtEEOi",
"parentPublication": {
"id": "proceedings/icpr/2014/5209/0",
"title": "2014 22nd International Conference on Pattern Recognition (ICPR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/acomp/2015/8234/0/8234a020",
"title": "Extracting Rule RF in Educational Data Classification: From a Random Forest to Interpretable Refined Rules",
"doi": null,
"abstractUrl": "/proceedings-article/acomp/2015/8234a020/12OmNx5piQK",
"parentPublication": {
"id": "proceedings/acomp/2015/8234/0",
"title": "2015 International Conference on Advanced Computing and Applications (ACOMP)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/uksim/2012/4682/0/4682a033",
"title": "Ant Colony Optimization for Rule Induction with Simulated Annealing for Terms Selection",
"doi": null,
"abstractUrl": "/proceedings-article/uksim/2012/4682a033/12OmNy5zssM",
"parentPublication": {
"id": "proceedings/uksim/2012/4682/0",
"title": "Computer Modeling and Simulation, International Conference on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ems/2011/4619/0/4619a070",
"title": "Hybrid Ant Colony Optimization and Simulated Annealing for Rule Induction",
"doi": null,
"abstractUrl": "/proceedings-article/ems/2011/4619a070/12OmNz3bdKb",
"parentPublication": {
"id": "proceedings/ems/2011/4619/0",
"title": "Computer Modeling and Simulation, UKSIM European Symposium on",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/gcis/2009/3571/1/05209008",
"title": "Constructing Interpretable Genetic Fuzzy Rule-Based System for Breast Cancer Diagnostic",
"doi": null,
"abstractUrl": "/proceedings-article/gcis/2009/05209008/12OmNzwZ6uD",
"parentPublication": {
"id": "gcis/2009/3571/1",
"title": "2009 WRI Global Congress on Intelligent Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2022/5099/0/509900a071",
"title": "Concise and interpretable multi-label rule sets",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2022/509900a071/1KpCp18mUSs",
"parentPublication": {
"id": "proceedings/icdm/2022/5099/0",
"title": "2022 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/big-data/2019/0858/0/09006159",
"title": "RAPID: Rapid and Precise Interpretable Decision Sets",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2019/09006159/1hJs9MOHO4U",
"parentPublication": {
"id": "proceedings/big-data/2019/0858/0",
"title": "2019 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/csci/2019/5584/0/558400a519",
"title": "Converting Neural Networks to Rule Foam",
"doi": null,
"abstractUrl": "/proceedings-article/csci/2019/558400a519/1jdDYx90Qhy",
"parentPublication": {
"id": "proceedings/csci/2019/5584/0",
"title": "2019 International Conference on Computational Science and Computational Intelligence (CSCI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/candar/2020/8221/0/822100a153",
"title": "Extraction of Interpretable Decision Sets in Graph Databases",
"doi": null,
"abstractUrl": "/proceedings-article/candar/2020/822100a153/1sA9aJNGR0c",
"parentPublication": {
"id": "proceedings/candar/2020/8221/0",
"title": "2020 Eighth International Symposium on Computing and Networking (CANDAR)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/candarw/2021/2835/0/283500a159",
"title": "Heuristic extraction of co-occurrence patterns for effective construction of graph-based interpretable decision sets",
"doi": null,
"abstractUrl": "/proceedings-article/candarw/2021/283500a159/1zw5Ko80pgY",
"parentPublication": {
"id": "proceedings/candarw/2021/2835/0",
"title": "2021 Ninth International Symposium on Computing and Networking Workshops (CANDARW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "17D45VtKipN",
"title": "2017 IEEE International Conference on Big Data (Big Data)",
"acronym": "big-data",
"groupId": "1802964",
"volume": "0",
"displayVolume": "0",
"year": "2017",
"__typename": "ProceedingType"
},
"article": {
"id": "17D45W1Oa4h",
"doi": "10.1109/BigData.2017.8258215",
"title": "Improving expectation maximization algorithm over stellar data",
"normalizedTitle": "Improving expectation maximization algorithm over stellar data",
"abstract": "Stellar data, only a few years ago, measured in the .1M of objects. Now, sets are routinely 1M. With the launch of ESA's Gaia in 2013, we expect 1000M stellar objects measured more precisely and with more measurements. Without question, astronomy is about Big Data and clustering is a very common task over astronomy domain. The expectation-maximization algorithm is among the top 10 data mining algorithms used in scientific and industrial applications, however, we observe that astronomical community does not make use of it as a clustering algorithm. In this work, we cluster ∼ 1M stellar objects (simulated Galactic spectral data) via the traditional expectation-maximization algorithm for clustering (EM-T) and our extended EM-T algorithm that we call EM∗ and present the experimental results.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Stellar data, only a few years ago, measured in the .1M of objects. Now, sets are routinely 1M. With the launch of ESA's Gaia in 2013, we expect 1000M stellar objects measured more precisely and with more measurements. Without question, astronomy is about Big Data and clustering is a very common task over astronomy domain. The expectation-maximization algorithm is among the top 10 data mining algorithms used in scientific and industrial applications, however, we observe that astronomical community does not make use of it as a clustering algorithm. In this work, we cluster ∼ 1M stellar objects (simulated Galactic spectral data) via the traditional expectation-maximization algorithm for clustering (EM-T) and our extended EM-T algorithm that we call EM∗ and present the experimental results.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Stellar data, only a few years ago, measured in the .1M of objects. Now, sets are routinely 1M. With the launch of ESA's Gaia in 2013, we expect 1000M stellar objects measured more precisely and with more measurements. Without question, astronomy is about Big Data and clustering is a very common task over astronomy domain. The expectation-maximization algorithm is among the top 10 data mining algorithms used in scientific and industrial applications, however, we observe that astronomical community does not make use of it as a clustering algorithm. In this work, we cluster ∼ 1M stellar objects (simulated Galactic spectral data) via the traditional expectation-maximization algorithm for clustering (EM-T) and our extended EM-T algorithm that we call EM∗ and present the experimental results.",
"fno": "08258215",
"keywords": [
"Convergence",
"Clustering Algorithms",
"Big Data",
"Astronomy",
"Covariance Matrices",
"Extraterrestrial Measurements",
"Hidden Markov Models",
"Expectation Maximization",
"Astronomy",
"Data Reduction",
"Big Data",
"Clustering",
"Heap"
],
"authors": [
{
"affiliation": "Department of Computer Science, Indiana University, Bloomington, IN 47405, United States",
"fullName": "Hasan Kurban",
"givenName": "Hasan",
"surname": "Kurban",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Science, Indiana University, Bloomington, IN 47405, United States",
"fullName": "Can Kockan",
"givenName": "Can",
"surname": "Kockan",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Science, Indiana University, Bloomington, IN 47405, United States",
"fullName": "Mark Jenne",
"givenName": "Mark",
"surname": "Jenne",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Department of Computer Science, Indiana University, Bloomington, IN 47405, United States",
"fullName": "Mehmet M. Dalkilic",
"givenName": "Mehmet M.",
"surname": "Dalkilic",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "big-data",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2017-12-01T00:00:00",
"pubType": "proceedings",
"pages": "2559-2568",
"year": "2017",
"issn": null,
"isbn": "978-1-5386-2715-0",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "08258214",
"articleId": "17D45W9KVIh",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "08258216",
"articleId": "17D45WHONsg",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/icdm/2006/2701/0/270100522",
"title": "Stability Region Based Expectation Maximization for Model-based Clustering",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2006/270100522/12OmNAoDhTs",
"parentPublication": {
"id": "proceedings/icdm/2006/2701/0",
"title": "Sixth International Conference on Data Mining (ICDM'06)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icme/2006/0366/0/04036999",
"title": "FEMA: A Fast Expectation Maximization Algorithm based on Grid and PCA",
"doi": null,
"abstractUrl": "/proceedings-article/icme/2006/04036999/12OmNBSBk0b",
"parentPublication": {
"id": "proceedings/icme/2006/0366/0",
"title": "2006 IEEE International Conference on Multimedia and Expo",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2007/3122/0/3122a904",
"title": "Clustering Analysis Using Data Range Aware Seeding and Agglomerative Expectation Maximization",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2007/3122a904/12OmNBt3qqu",
"parentPublication": {
"id": "proceedings/sitis/2007/3122/0",
"title": "2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cse/2015/8297/0/8297a082",
"title": "Clustering of Complex Data-Sets Using Fractal Similarity Measures and Uncertainties",
"doi": null,
"abstractUrl": "/proceedings-article/cse/2015/8297a082/12OmNCbU36K",
"parentPublication": {
"id": "proceedings/cse/2015/8297/0",
"title": "2015 IEEE 18th International Conference on Computational Science and Engineering (CSE)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/cluster/2012/4807/0/4807a275",
"title": "Accelerating Expectation-Maximization Algorithms with Frequent Updates",
"doi": null,
"abstractUrl": "/proceedings-article/cluster/2012/4807a275/12OmNyRg4zX",
"parentPublication": {
"id": "proceedings/cluster/2012/4807/0",
"title": "2012 IEEE International Conference on Cluster Computing",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2008/3493/0/3493a359",
"title": "Expectation-Maximization x Self-Organizing Maps for Image Classification",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2008/3493a359/12OmNz2TCHn",
"parentPublication": {
"id": "proceedings/sitis/2008/3493/0",
"title": "2008 IEEE International Conference on Signal Image Technology and Internet Based Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sitis/2013/3211/0/3211b071",
"title": "Simple Example: Clustering Images Using Expectation Maximization",
"doi": null,
"abstractUrl": "/proceedings-article/sitis/2013/3211b071/12OmNzV70z9",
"parentPublication": {
"id": "proceedings/sitis/2013/3211/0",
"title": "2013 International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tp/2008/07/ttp2008071146",
"title": "TRUST-TECH-Based Expectation Maximization for Learning Finite Mixture Models",
"doi": null,
"abstractUrl": "/journal/tp/2008/07/ttp2008071146/13rRUwIF6eQ",
"parentPublication": {
"id": "trans/tp",
"title": "IEEE Transactions on Pattern Analysis & Machine Intelligence",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/host/2019/8064/0/08740839",
"title": "STELLAR: A Generic EM Side-Channel Attack Protection through Ground-Up Root-cause Analysis",
"doi": null,
"abstractUrl": "/proceedings-article/host/2019/08740839/1b1xmA5fbqM",
"parentPublication": {
"id": "proceedings/host/2019/8064/0",
"title": "2019 IEEE International Symposium on Hardware Oriented Security and Trust (HOST)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/td/2020/11/09106834",
"title": "Fully Homomorphic based Privacy-Preserving Distributed Expectation Maximization on Cloud",
"doi": null,
"abstractUrl": "/journal/td/2020/11/09106834/1kkFIGzQg80",
"parentPublication": {
"id": "trans/td",
"title": "IEEE Transactions on Parallel & Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1KfQshha0dW",
"title": "2022 IEEE International Conference on Big Data (Big Data)",
"acronym": "big-data",
"groupId": "10020192",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1KfRSfulXnG",
"doi": "10.1109/BigData55660.2022.10020714",
"title": "Star-Bridge: a topological multidimensional subgraph analysis to detect fraudulent nodes and rings in telecom networks",
"normalizedTitle": "Star-Bridge: a topological multidimensional subgraph analysis to detect fraudulent nodes and rings in telecom networks",
"abstract": "Fraud mechanisms have evolved from isolated actions performed by single individuals to complex criminal networks. This paper aims to contribute to the identification of potentially relevant nodes in fraud networks. Whilst traditional methods for fraud detection rely on identifying abnormal patterns, this paper proposes STARBRIDGE: a new linear and scalable, ranked out, parameter free method to identify fraudulent nodes and rings based on Bridging, Influence and Control metrics. This is applied to the telecommunications domain where fraudulent nodes form a star-bridge-star pattern. Over 75% of nodes involved in fraud denote control, bridging centrality and doubled the influence scores, when compared to non-fraudulent nodes in the same role, stars and bridges being chief positions.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Fraud mechanisms have evolved from isolated actions performed by single individuals to complex criminal networks. This paper aims to contribute to the identification of potentially relevant nodes in fraud networks. Whilst traditional methods for fraud detection rely on identifying abnormal patterns, this paper proposes STARBRIDGE: a new linear and scalable, ranked out, parameter free method to identify fraudulent nodes and rings based on Bridging, Influence and Control metrics. This is applied to the telecommunications domain where fraudulent nodes form a star-bridge-star pattern. Over 75% of nodes involved in fraud denote control, bridging centrality and doubled the influence scores, when compared to non-fraudulent nodes in the same role, stars and bridges being chief positions.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Fraud mechanisms have evolved from isolated actions performed by single individuals to complex criminal networks. This paper aims to contribute to the identification of potentially relevant nodes in fraud networks. Whilst traditional methods for fraud detection rely on identifying abnormal patterns, this paper proposes STARBRIDGE: a new linear and scalable, ranked out, parameter free method to identify fraudulent nodes and rings based on Bridging, Influence and Control metrics. This is applied to the telecommunications domain where fraudulent nodes form a star-bridge-star pattern. Over 75% of nodes involved in fraud denote control, bridging centrality and doubled the influence scores, when compared to non-fraudulent nodes in the same role, stars and bridges being chief positions.",
"fno": "10020714",
"keywords": [
"Fraud",
"Graph Theory",
"Security Of Data",
"Telecommunication Control",
"Telecommunication Networks",
"Telecommunication Security",
"Abnormal Patterns",
"Complex Criminal Networks",
"Control Metrics",
"Fraud Denote Control",
"Fraud Detection",
"Fraud Networks",
"Fraudulent Nodes",
"Free Method",
"Isolated Actions",
"Nonfraudulent Nodes",
"Star Bridge Star Pattern",
"STARBRIDGE",
"Telecom Networks",
"Topological Multidimensional Subgraph Analysis",
"Bridges",
"Measurement",
"Industries",
"Network Topology",
"Shape",
"Stars",
"Big Data",
"Fraud Type",
"Fraud Enabler",
"Fraud Networks",
"Network Control",
"Bridging Centrality"
],
"authors": [
{
"affiliation": "Iscte - Instituto Universitário de Lisboa Mobileum,Lisbon,Portugal",
"fullName": "Pedro Fidalgo",
"givenName": "Pedro",
"surname": "Fidalgo",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Instituto de Telecomunicações,Iscte - Instituto Universitário de Lisboa,Lisbon,Portugal",
"fullName": "Rui J. Lopes",
"givenName": "Rui J.",
"surname": "Lopes",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University,Pittsburgh,USA",
"fullName": "Christos Faloutsos",
"givenName": "Christos",
"surname": "Faloutsos",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "big-data",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-12-01T00:00:00",
"pubType": "proceedings",
"pages": "2239-2242",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-8045-1",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "10020394",
"articleId": "1KfT3GoRWKs",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "10020713",
"articleId": "1KfSdPqDytG",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/big-data/2015/9926/0/07364134",
"title": "Analysis of star ratings in consumer reviews: A case study of Yelp",
"doi": null,
"abstractUrl": "/proceedings-article/big-data/2015/07364134/12OmNASraBc",
"parentPublication": {
"id": "proceedings/big-data/2015/9926/0",
"title": "2015 IEEE International Conference on Big Data (Big Data)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iscc/1997/7852/0/00616068",
"title": "An efficient multicast protocol for WDM star-coupler networks",
"doi": null,
"abstractUrl": "/proceedings-article/iscc/1997/00616068/12OmNvpw7e6",
"parentPublication": {
"id": "proceedings/iscc/1997/7852/0",
"title": "Proceedings Second IEEE Symposium on Computer and Communications",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpads/1994/6555/0/00590312",
"title": "Algorithms for node disjoint paths in incomplete star networks",
"doi": null,
"abstractUrl": "/proceedings-article/icpads/1994/00590312/12OmNwFid3h",
"parentPublication": {
"id": "proceedings/icpads/1994/6555/0",
"title": "Proceedings of 1994 International Conference on Parallel and Distributed Systems",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/pdcat/2014/8334/0/8334a113",
"title": "Fault-Tolerant Routing in (n, k) - Star Graphs",
"doi": null,
"abstractUrl": "/proceedings-article/pdcat/2014/8334a113/12OmNyaGeIQ",
"parentPublication": {
"id": "proceedings/pdcat/2014/8334/0",
"title": "2014 15th International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/ictai/2018/7449/0/744900a315",
"title": "Obstacle-Avoiding Euclidean Steiner Trees by n-Star Bundles",
"doi": null,
"abstractUrl": "/proceedings-article/ictai/2018/744900a315/17D45Wc1IJv",
"parentPublication": {
"id": "proceedings/ictai/2018/7449/0",
"title": "2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigcomp/2019/7789/0/08679414",
"title": "Network-Based Feature Extraction Method for Fraud Detection via Label Propagation",
"doi": null,
"abstractUrl": "/proceedings-article/bigcomp/2019/08679414/18XkkNccQsE",
"parentPublication": {
"id": "proceedings/bigcomp/2019/7789/0",
"title": "2019 IEEE International Conference on Big Data and Smart Computing (BigComp)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/bigdatasecurity-hpsc-ids/2022/8069/0/806900a174",
"title": "Node Similarity-based Search Method for Medical Insurance Heterogeneous Information Network",
"doi": null,
"abstractUrl": "/proceedings-article/bigdatasecurity-hpsc-ids/2022/806900a174/1EykEmpyAE0",
"parentPublication": {
"id": "proceedings/bigdatasecurity-hpsc-ids/2022/8069/0",
"title": "2022 IEEE 8th 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": "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/icdmw/2022/4609/0/460900b217",
"title": "Hybrid Oversampling Technique Based on Star Topology and Rejection Methodology for Classifying Imbalanced Data",
"doi": null,
"abstractUrl": "/proceedings-article/icdmw/2022/460900b217/1KBqWX6rwMU",
"parentPublication": {
"id": "proceedings/icdmw/2022/4609/0",
"title": "2022 IEEE International Conference on Data Mining Workshops (ICDMW)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/sti/2022/9045/0/10103259",
"title": "Exploiting Deep Learning Based Classification Model for Detecting Fraudulent Schemes over Ethereum Blockchain",
"doi": null,
"abstractUrl": "/proceedings-article/sti/2022/10103259/1MBEWEIdfsA",
"parentPublication": {
"id": "proceedings/sti/2022/9045/0",
"title": "2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
{
"proceeding": {
"id": "1KpChQa9kQ0",
"title": "2022 IEEE International Conference on Data Mining (ICDM)",
"acronym": "icdm",
"groupId": "1000179",
"volume": "0",
"displayVolume": "0",
"year": "2022",
"__typename": "ProceedingType"
},
"article": {
"id": "1KpCFhWLcas",
"doi": "10.1109/ICDM54844.2022.00088",
"title": "Toward Unsupervised Outlier Model Selection",
"normalizedTitle": "Toward Unsupervised Outlier Model Selection",
"abstract": "Today there exists no shortage of outlier detection algorithms in the literature, yet the complementary and critical problem of unsupervised outlier model selection (UOMS) is vastly understudied. In this work, we propose ELECT, a new approach to select an effective candidate model, i.e. an outlier detection algorithm and its hyperparameter(s), to employ on a new dataset without any labels. At its core, ELECT is based on meta-learning; transferring prior knowledge (e.g. model performance) on historical datasets that are similar to the new one to facilitate UOMS. Uniquely, it employs a dataset similarity measure that is performance-based, which is more direct and goal-driven than other measures used in the past. ELECT adaptively searches for similar historical datasets, as such, it can serve an output on-demand, being able to accommodate varying time budgets. Extensive experiments show that ELECT significantly outperforms a wide range of basic UOMS baselines, including no model selection (always using the same popular model such as iForest) as well as more recent selection strategies based on meta-features.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Today there exists no shortage of outlier detection algorithms in the literature, yet the complementary and critical problem of unsupervised outlier model selection (UOMS) is vastly understudied. In this work, we propose ELECT, a new approach to select an effective candidate model, i.e. an outlier detection algorithm and its hyperparameter(s), to employ on a new dataset without any labels. At its core, ELECT is based on meta-learning; transferring prior knowledge (e.g. model performance) on historical datasets that are similar to the new one to facilitate UOMS. Uniquely, it employs a dataset similarity measure that is performance-based, which is more direct and goal-driven than other measures used in the past. ELECT adaptively searches for similar historical datasets, as such, it can serve an output on-demand, being able to accommodate varying time budgets. Extensive experiments show that ELECT significantly outperforms a wide range of basic UOMS baselines, including no model selection (always using the same popular model such as iForest) as well as more recent selection strategies based on meta-features.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Today there exists no shortage of outlier detection algorithms in the literature, yet the complementary and critical problem of unsupervised outlier model selection (UOMS) is vastly understudied. In this work, we propose ELECT, a new approach to select an effective candidate model, i.e. an outlier detection algorithm and its hyperparameter(s), to employ on a new dataset without any labels. At its core, ELECT is based on meta-learning; transferring prior knowledge (e.g. model performance) on historical datasets that are similar to the new one to facilitate UOMS. Uniquely, it employs a dataset similarity measure that is performance-based, which is more direct and goal-driven than other measures used in the past. ELECT adaptively searches for similar historical datasets, as such, it can serve an output on-demand, being able to accommodate varying time budgets. Extensive experiments show that ELECT significantly outperforms a wide range of basic UOMS baselines, including no model selection (always using the same popular model such as iForest) as well as more recent selection strategies based on meta-features.",
"fno": "509900a773",
"keywords": [
"Data Handling",
"Unsupervised Learning",
"Basic UOMS Baselines",
"Dataset Similarity Measure",
"ELECT",
"Outlier Detection Algorithm",
"Unsupervised Outlier Model Selection",
"Deep Learning",
"Adaptation Models",
"Filling",
"Data Models",
"Task Analysis",
"Anomaly Detection",
"Faces",
"Outlier Detection",
"Model Selection",
"Automated Machine Learning",
"Meta Learning"
],
"authors": [
{
"affiliation": "Carnegie Mellon University",
"fullName": "Yue Zhao",
"givenName": "Yue",
"surname": "Zhao",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University",
"fullName": "Sean Zhang",
"givenName": "Sean",
"surname": "Zhang",
"__typename": "ArticleAuthorType"
},
{
"affiliation": "Carnegie Mellon University",
"fullName": "Leman Akoglu",
"givenName": "Leman",
"surname": "Akoglu",
"__typename": "ArticleAuthorType"
}
],
"idPrefix": "icdm",
"isOpenAccess": false,
"showRecommendedArticles": true,
"showBuyMe": true,
"hasPdf": true,
"pubDate": "2022-11-01T00:00:00",
"pubType": "proceedings",
"pages": "773-782",
"year": "2022",
"issn": null,
"isbn": "978-1-6654-5099-7",
"notes": null,
"notesType": null,
"__typename": "ArticleType"
},
"webExtras": [],
"adjacentArticles": {
"previous": {
"fno": "509900a763",
"articleId": "1KpCK9urjhK",
"__typename": "AdjacentArticleType"
},
"next": {
"fno": "509900a783",
"articleId": "1KpCC81QEXC",
"__typename": "AdjacentArticleType"
},
"__typename": "AdjacentArticlesType"
},
"recommendedArticles": [
{
"id": "proceedings/vts/2013/5542/0/06548885",
"title": "Selection of tests for outlier detection",
"doi": null,
"abstractUrl": "/proceedings-article/vts/2013/06548885/12OmNrHB1R9",
"parentPublication": {
"id": "proceedings/vts/2013/5542/0",
"title": "2013 IEEE 31st VLSI Test Symposium (VTS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2016/5473/0/07837865",
"title": "Unsupervised Feature Selection for Outlier Detection by Modelling Hierarchical Value-Feature Couplings",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2016/07837865/12OmNwJPMZ7",
"parentPublication": {
"id": "proceedings/icdm/2016/5473/0",
"title": "2016 IEEE 16th International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/iri/2017/1562/0/1562a559",
"title": "Estimating Outlier Score Probabilities",
"doi": null,
"abstractUrl": "/proceedings-article/iri/2017/1562a559/12OmNwekjHx",
"parentPublication": {
"id": "proceedings/iri/2017/1562/0",
"title": "2017 IEEE International Conference on Information Reuse and Integration (IRI)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/services/2018/7374/0/737400a015",
"title": "Ship Trajectory Outlier Detection Service System Based on Collaborative Computing",
"doi": null,
"abstractUrl": "/proceedings-article/services/2018/737400a015/14Fq12gisla",
"parentPublication": {
"id": "proceedings/services/2018/7374/0",
"title": "2018 IEEE World Congress on Services (SERVICES)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icdm/2018/9159/0/08594923",
"title": "Outlier Detection in Urban Traffic Flow Distributions",
"doi": null,
"abstractUrl": "/proceedings-article/icdm/2018/08594923/17D45VObpR0",
"parentPublication": {
"id": "proceedings/icdm/2018/9159/0",
"title": "2018 IEEE International Conference on Data Mining (ICDM)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icicta/2018/8308/0/830800a005",
"title": "Abnormal Detection Research Based on Outlier Mining",
"doi": null,
"abstractUrl": "/proceedings-article/icicta/2018/830800a005/17D45WHONlZ",
"parentPublication": {
"id": "proceedings/icicta/2018/8308/0",
"title": "2018 11th International Conference on Intelligent Computation Technology and Automation (ICICTA)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/5555/01/09737003",
"title": "ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions",
"doi": null,
"abstractUrl": "/journal/tk/5555/01/09737003/1BN1NassR7q",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "proceedings/icpads/2022/7315/0/731500a908",
"title": "DPSS: Dynamic Parameter Selection for Outlier Detection on Data Streams",
"doi": null,
"abstractUrl": "/proceedings-article/icpads/2022/731500a908/1LRlOpmxrCE",
"parentPublication": {
"id": "proceedings/icpads/2023/7315/0",
"title": "2022 IEEE 28th International Conference on Parallel and Distributed Systems (ICPADS)",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tc/5555/01/10113794",
"title": "Efficient and Robust KPI Outlier Detection for Large-Scale Datacenters",
"doi": null,
"abstractUrl": "/journal/tc/5555/01/10113794/1MNbTs1XcIM",
"parentPublication": {
"id": "trans/tc",
"title": "IEEE Transactions on Computers",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
},
{
"id": "trans/tk/2020/08/08668550",
"title": "Generative Adversarial Active Learning for Unsupervised Outlier Detection",
"doi": null,
"abstractUrl": "/journal/tk/2020/08/08668550/1lgLieNNufu",
"parentPublication": {
"id": "trans/tk",
"title": "IEEE Transactions on Knowledge & Data Engineering",
"__typename": "ParentPublication"
},
"__typename": "RecommendedArticleType"
}
],
"articleVideos": []
}
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.