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"title": "Shapes2Toon: Generating Cartoon Characters from Simple Geometric Shapes",
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"abstract": "Cartoons are an important part of our entertain-ment culture. Though drawing a cartoon is not for everyone, creating it using an arrangement of basic geometric primitives that approximates that character is a fairly frequent technique in art. The key motivation behind this technique is that human bodies-as well as cartoon figures-can be split down into various basic geometric primitives. Numerous tutorials are available that demonstrate how to draw figures using an appropriate arrangement of fundamental shapes, thus assisting us in creating cartoon characters. This technique is very beneficial for children in terms of teaching them how to draw cartoons. In this paper, we develop a tool-shape2toon-that aims to automate this approach by utilizing a generative adversarial network which combines geometric primitives (i.e. circles) and generate a cartoon figure (i.e. Mickey Mouse) depending on the given approximation. For this purpose, we created a dataset of geometrically represented cartoon characters. We apply an image-to-image translation technique on our dataset and report the results in this paper. The experimental results show that our system can generate cartoon characters from input layout of geometric shapes. In addition, we demonstrate a web-based tool as a practical implication of our work.",
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"abstract": "In this paper we propose an algorithm for stereoscopic image inpainting, given the inpainting mask in both images. We also assume that depth map is known in one of the images of the stereo pair, taken as reference. This image is clustered in homogeneous color regions using a mean-shift procedure. In each clustered region, depths are fitted by planes and then extended into the mask. Then we inpaint the visible parts of each extended region using a modified exemplar-based inpainting algorithm. Finally, we extend the algorithm to stereoscopic image inpainting. We display some experiments showing the performance of the proposed algorithm.",
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"abstract": "This paper describes general framework of photo-realistic 3D visualization of urban building with digital map, Lidar point and close-range image in photogrammetry community. First, Vanish Point (VP) geometry deduced from classic photogrammetry co-linear equation is used to obtain camera Interior Of Parameter (IOP) and Exterior Of Parameter (EOP) using groups of mutually orthogonal space lines appeared in buildings; Next, \"line photogrammetry\" is introduced to precisely reconstruct building geometrical model. To this end, coarse building geometry model is generated from digital map and Lidar poin, and further refined with constrains from abundant image line features; After that, texture for each building facet is well reconstructed by applying photogrammetry differential rectification to eliminate texture distortion and detecting texture elements to remove occlusion as well; Finally, two experiments are presented by integrating digital map with ground-level still image and low-altitude aerial video image strips for photo-realistic 3D visualization of building respectively. Contributions are also concluded.",
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"abstract": "The gravity model and intensity model of urban flow was developed for analyzing spatial contacts in urban agglomerations. The paper analyzes the economic contacts of urban agglomeration between major cities in Jiangxi province and different regions in China. The study shows that the intensities of economic contacts of urban agglomeration between major cities in Jiangxi province and other regions in whole country are different greatly. The contacts between the 11 cities and Wuhan urban agglomeration, Yangtze urban agglomeration, Chang-Zhu-Tan urban agglomeration and Wanjiang urban agglomeration are more close and complicated than those of the west, the southwest and the east region. Meanwhile, the tendency and intensity of urban flows in Jiangxi province is misplaced, the economic capacity of main cities doesn’t match with their outward service abilities. Therefore, a more systematical and measurable quantitative analysis is needed in demonstrating economic contacts of urban agglomerations in different regions.",
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"content": "The gravity model and intensity model of urban flow was developed for analyzing spatial contacts in urban agglomerations. The paper analyzes the economic contacts of urban agglomeration between major cities in Jiangxi province and different regions in China. The study shows that the intensities of economic contacts of urban agglomeration between major cities in Jiangxi province and other regions in whole country are different greatly. The contacts between the 11 cities and Wuhan urban agglomeration, Yangtze urban agglomeration, Chang-Zhu-Tan urban agglomeration and Wanjiang urban agglomeration are more close and complicated than those of the west, the southwest and the east region. Meanwhile, the tendency and intensity of urban flows in Jiangxi province is misplaced, the economic capacity of main cities doesn’t match with their outward service abilities. Therefore, a more systematical and measurable quantitative analysis is needed in demonstrating economic contacts of urban agglomerations in different regions.",
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"abstract": "This paper presents a system to reconstruct piecewise planar and compact floorplans from images, which are then converted to high quality texture-mapped models for free- viewpoint visualization. There are two main challenges in image-based floorplan reconstruction. The first is the lack of 3D information that can be extracted from images by Structure from Motion and Multi-View Stereo, as indoor scenes abound with non-diffuse and homogeneous surfaces plus clutter. The second challenge is the need of a sophisti- cated regularization technique that enforces piecewise pla- narity, to suppress clutter and yield high quality texture mapped models. Our technical contributions are twofold. First, we propose a novel structure classification technique to classify each pixel to three regions (floor, ceiling, and wall), which provide 3D cues even from a single image. Second, we cast floorplan reconstruction as a shortest path problem on a specially crafted graph, which enables us to enforce piecewise planarity. Besides producing compact piecewise planar models, this formulation allows us to di- rectly control the number of vertices (i.e., density) of the output mesh. We evaluate our system on real indoor scenes, and show that our texture mapped mesh models provide compelling free-viewpoint visualization experiences, when compared against the state-of-the-art and ground truth.",
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"content": "This paper presents a system to reconstruct piecewise planar and compact floorplans from images, which are then converted to high quality texture-mapped models for free- viewpoint visualization. There are two main challenges in image-based floorplan reconstruction. The first is the lack of 3D information that can be extracted from images by Structure from Motion and Multi-View Stereo, as indoor scenes abound with non-diffuse and homogeneous surfaces plus clutter. The second challenge is the need of a sophisti- cated regularization technique that enforces piecewise pla- narity, to suppress clutter and yield high quality texture mapped models. Our technical contributions are twofold. First, we propose a novel structure classification technique to classify each pixel to three regions (floor, ceiling, and wall), which provide 3D cues even from a single image. Second, we cast floorplan reconstruction as a shortest path problem on a specially crafted graph, which enables us to enforce piecewise planarity. Besides producing compact piecewise planar models, this formulation allows us to di- rectly control the number of vertices (i.e., density) of the output mesh. We evaluate our system on real indoor scenes, and show that our texture mapped mesh models provide compelling free-viewpoint visualization experiences, when compared against the state-of-the-art and ground truth.",
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"abstract": "In this paper, we introduce a method for building LOD (levels of detail) modeling from urban multi-view stereo (MVS) meshes. Using city MVS meshes as input, our algorithm proceeds in three main steps: segmentation, contour extraction and modeling. With the prior knowledge and span constraint, we first segment the scene with an adapted variational measure to discover the underlying structures. The next contour extraction step projects the vertical structures onto the ground as line segments and extract the facade contours from them with a Markov random field. In the last modeling step, the contours are used to label the roof sections out and extruded to generate models of LODs with semantics. Experiments on complex and noisy urban meshes show that our approach could generate compact and accurate building models when compared with stateof- art methods.",
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"content": "Urban building energy consumption is one important part of the total social energy consumption. How to predict building energy consumption of urban development trends and master the changes of urban building energy consumption are important link of building energy-saving. In order to forecast urban building energy consumption from both the macro and micro aspects, multi-layer feed forward artificial neural network based on BP algorithm is proposed in the paper and used MATLAB implements to design and train of improving BP neural network. A macro urban building energy consumption prediction model and a micro urban building energy consumption prediction model are established in the paper, they are the city electricity demand prediction model and air-conditioning system energy consumption prediction model. The accuracy and feasibility of the prediction models were studied by calculation the difference between practical data and simulation model predictions.",
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"abstract": "The structural features of the rail transit network in a city are significantly affected when a new urban rail transit line is additionally opened. The traditional prediction method to estimate the passenger flow distribution based on historical passenger flow data is no longer applicable. Although the existing gravity model can be used to predict the flow distribution of passengers after a new line is opened, it cannot show the characteristics of passenger flow in a station since the average travel impedance calculation method is employed and it doesn't take the station attributes into consideration. In order to address this problem, a new gravity model integrating station attributes is proposed in this paper. The model can be used to predict the passenger flow distribution with fitted parameters, and different travel characteristics are considered in this model. Taking Chengdu Metro as an example, all the stations are clustered according to their attributes, and the prediction results are calculated with the traditional dual-constrained gravity model and the proposed gravity model, respectively. In the end, we have made a comparison, which shows the advantages of the proposed model when the station attributes are considered.",
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"content": "The structural features of the rail transit network in a city are significantly affected when a new urban rail transit line is additionally opened. The traditional prediction method to estimate the passenger flow distribution based on historical passenger flow data is no longer applicable. Although the existing gravity model can be used to predict the flow distribution of passengers after a new line is opened, it cannot show the characteristics of passenger flow in a station since the average travel impedance calculation method is employed and it doesn't take the station attributes into consideration. In order to address this problem, a new gravity model integrating station attributes is proposed in this paper. The model can be used to predict the passenger flow distribution with fitted parameters, and different travel characteristics are considered in this model. Taking Chengdu Metro as an example, all the stations are clustered according to their attributes, and the prediction results are calculated with the traditional dual-constrained gravity model and the proposed gravity model, respectively. In the end, we have made a comparison, which shows the advantages of the proposed model when the station attributes are considered.",
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"abstract": "Character shape reconstruction for the scene character is challenging and interesting because scene character usually suffers from uneven illumination, complex background, perspective distortion. To address such ill conditions, we propose to utilize Histogram Gradient Division (HGD) and Reverse Gradient Orientation (RGO) to select Candidate Text Pixels (CTPs) for a given input character. Ring Radius Transform is applied on each pixel in a CTP image to obtain radius map where each pixel is assigned a value which is the radius to the nearest CTP. Candidate medial axis pixels are those having maximum radius values in their neighborhoods. We find such pixels on horizontal, vertical, principal diagonal and secondary diagonal directions to determine the respective medial axis pixels. The union of all medial axis pixels at each pixel location is considered as a candidate medial axis pixel of the character. Then color difference and k-means clustering are employed to eliminate false candidate medial axis. The potential medial axis values are used to reconstruct the shape of the character. The method is tested on 1025 characters of complex foreground and background from ICDAR 2003 dataset in terms of shape reconstruction and recognition rate. Experimental results demonstrate the effectiveness of our proposed method for complex foreground and background characters in terms of character recognition rate and reconstruction error.",
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"content": "Character shape reconstruction for the scene character is challenging and interesting because scene character usually suffers from uneven illumination, complex background, perspective distortion. To address such ill conditions, we propose to utilize Histogram Gradient Division (HGD) and Reverse Gradient Orientation (RGO) to select Candidate Text Pixels (CTPs) for a given input character. Ring Radius Transform is applied on each pixel in a CTP image to obtain radius map where each pixel is assigned a value which is the radius to the nearest CTP. Candidate medial axis pixels are those having maximum radius values in their neighborhoods. We find such pixels on horizontal, vertical, principal diagonal and secondary diagonal directions to determine the respective medial axis pixels. The union of all medial axis pixels at each pixel location is considered as a candidate medial axis pixel of the character. Then color difference and k-means clustering are employed to eliminate false candidate medial axis. The potential medial axis values are used to reconstruct the shape of the character. The method is tested on 1025 characters of complex foreground and background from ICDAR 2003 dataset in terms of shape reconstruction and recognition rate. Experimental results demonstrate the effectiveness of our proposed method for complex foreground and background characters in terms of character recognition rate and reconstruction error.",
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"abstract": "In the ceramic tile industry bulk amount of ceramic tiles are manufactured, it is very difficult to monitor the quality of each and every tiles manually. Lot of human resources are required for the defect detection of the tiles. Also it is quite tedious and time consuming method. Considering this criteria, an automated defect detection and classification technique has been proposed in this report that can have ensured the better quality of tiles in manufacturing process as well as production rate. Our proposed method plays an important role in ceramic tiles industries to detect the defects and to control the quality of ceramic tiles. This automated classification method helps us to monitor the defects within a very short period of time and also to decide about the recovery process so that the defected tiles may not be mixed with the good quality tiles.",
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"abstract": "In view of the problems of small scale and low contrast of ceramic tile defects, various types of ceramic tile surface defects, and difficulty in realizing high-precision ceramic tile defect detection, a ceramic tile surface defect detection model based on improved Cascade RCNN is proposed to locate and identify the types of ceramic tile surface defects in different texture backgrounds. The improved ResNest network is used to improve the classification ability of the algorithm and optimize the performance of the model. The improved feature pyramid enhanced the feature extraction ability of the algorithm, and improved the accuracy of detecting small-scale defects and low-contrast defects of ceramic tiles. The whole connection structure of the last layer of cascade detectors was modified to double-head structure, which improved the ability of detectors to perform classification and regression tasks, and solved the problem of various kinds of defects on the surface of ceramic tiles. After data collection, 2810 tiles defect pictures were obtained, and then 7934 tiles defect slices were obtained by image segmentation, and the slices were made into tiles defect data sets. Experiments show that this method can achieve 77.8<sup>%</sup> MAP and 93.9% average positive detection rate, which is higher than Faster RCNN and original Cascade RCNN.",
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"content": "In view of the problems of small scale and low contrast of ceramic tile defects, various types of ceramic tile surface defects, and difficulty in realizing high-precision ceramic tile defect detection, a ceramic tile surface defect detection model based on improved Cascade RCNN is proposed to locate and identify the types of ceramic tile surface defects in different texture backgrounds. The improved ResNest network is used to improve the classification ability of the algorithm and optimize the performance of the model. The improved feature pyramid enhanced the feature extraction ability of the algorithm, and improved the accuracy of detecting small-scale defects and low-contrast defects of ceramic tiles. The whole connection structure of the last layer of cascade detectors was modified to double-head structure, which improved the ability of detectors to perform classification and regression tasks, and solved the problem of various kinds of defects on the surface of ceramic tiles. After data collection, 2810 tiles defect pictures were obtained, and then 7934 tiles defect slices were obtained by image segmentation, and the slices were made into tiles defect data sets. Experiments show that this method can achieve 77.8<sup>%</sup> MAP and 93.9% average positive detection rate, which is higher than Faster RCNN and original Cascade RCNN.",
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"abstract": "Causal discovery for high-dimensional observations is a useful tool in many fields such as climate analysis and financial market analysis. A linear Trace method has been proposed to identify the causal direction between two linearly coupled high-dimensional observations X and Y. However, in reality, the relations between X and Y are usually nonlinear and consequently the linear Trace method may fail. In this paper, we propose a method to infer the nonlinear causal relations for two high-dimensional observations X and Y. The idea is to map the observations to high dimensional Reproducing Kernel Hilbert Space (RKHS) such that the nonlinear relations become simple linear ones. We show that the linear Trace condition holds for the causal direction but it is violated for the anti-causal direction in RKHS. Based on this theoretical result, we develop a simple algorithm to infer the causal direction for nonlinearly coupled causal pairs. Synthetic data and real world data experiments are conducted to show the effectiveness of our proposed method.",
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"content": "Causal discovery for high-dimensional observations is a useful tool in many fields such as climate analysis and financial market analysis. A linear Trace method has been proposed to identify the causal direction between two linearly coupled high-dimensional observations X and Y. However, in reality, the relations between X and Y are usually nonlinear and consequently the linear Trace method may fail. In this paper, we propose a method to infer the nonlinear causal relations for two high-dimensional observations X and Y. The idea is to map the observations to high dimensional Reproducing Kernel Hilbert Space (RKHS) such that the nonlinear relations become simple linear ones. We show that the linear Trace condition holds for the causal direction but it is violated for the anti-causal direction in RKHS. Based on this theoretical result, we develop a simple algorithm to infer the causal direction for nonlinearly coupled causal pairs. Synthetic data and real world data experiments are conducted to show the effectiveness of our proposed method.",
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"abstract": "Power Normalizations (PN) are very useful non-linear operators in the context of Bag-of-Words data representations as they tackle problems such as feature imbalance. In this paper, we reconsider these operators in the deep learning setup by introducing a novel layer that implements PN for non-linear pooling of feature maps. Specifically, by using a kernel formulation, our layer combines the feature vectors and their respective spatial locations in the feature maps produced by the last convolutional layer of CNN. Linearization of such a kernel results in a positive definite matrix capturing the second-order statistics of the feature vectors, to which PN operators are applied. We study two types of PN functions, namely (i) MaxExp and (ii) Gamma, addressing their role and meaning in the context of nonlinear pooling. We also provide a probabilistic interpretation of these operators and derive their surrogates with well-behaved gradients for end-to-end CNN learning. We apply our theory to practice by implementing the PN layer on a ResNet-50 model and showcase experiments on four benchmarks for fine-grained recognition, scene recognition, and material classification. Our results demonstrate state-of-the-part performance across all these tasks.",
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"abstract": "We propose an efficient technique for normal map acquisition, using a cheap and easy to build setup. Our setup consists solely of off-the-shelf components, such as an LCD screen, a digital camera and a linear polarizer filter. The LCD screen is employed as a linearly polarized light source emitting gradient patterns, whereas the digital camera is used to capture the incident illumination reflected off the scanned object's surface. Also, by exploiting the fact that light emitted by an LCD screen has the property of being linearly polarized, we use the filter to surpress any specular highlights. Based on the observed Lambertian reflection of only four different light patterns, we are able to obtain a detailed normal map of the scanned surface. Overall, our techniques produces convincing results, even on weak specular materials.",
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"content": "We propose an efficient technique for normal map acquisition, using a cheap and easy to build setup. Our setup consists solely of off-the-shelf components, such as an LCD screen, a digital camera and a linear polarizer filter. The LCD screen is employed as a linearly polarized light source emitting gradient patterns, whereas the digital camera is used to capture the incident illumination reflected off the scanned object's surface. Also, by exploiting the fact that light emitted by an LCD screen has the property of being linearly polarized, we use the filter to surpress any specular highlights. Based on the observed Lambertian reflection of only four different light patterns, we are able to obtain a detailed normal map of the scanned surface. Overall, our techniques produces convincing results, even on weak specular materials.",
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"affiliation": "Shandong University",
"fullName": "Siyan Dong",
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"affiliation": "Stanford University",
"fullName": "Qingnan Fan",
"givenName": "Qingnan",
"surname": "Fan",
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{
"affiliation": "Stanford University",
"fullName": "He Wang",
"givenName": "He",
"surname": "Wang",
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{
"affiliation": "Peking University",
"fullName": "Ji Shi",
"givenName": "Ji",
"surname": "Shi",
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"fullName": "Li Yi",
"givenName": "Li",
"surname": "Yi",
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"fullName": "Thomas Funkhouser",
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"affiliation": "Peking University",
"fullName": "Baoquan Chen",
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{
"affiliation": "Stanford University",
"fullName": "Leonidas Guibas",
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"content": "A new head mounted display (HMD) that provides a large field of view with a high-resolution insert is proposed and designed. Previously, this type of HMD has been designed using mechanical or sequential scanning devices, which are bulky and expensive. The proposed high-resolution insert HMD (HRI-HMD) is innovative and it uses only electronic devices that can be easily integrated with the optical components. The potential benefit of the HRI-HMD comes not only from its improved visual quality via a high-resolution insert but also from its increased human-computer interaction capability via eye tracking. The design principles and envisioned applications of the HRI-HMD are described, and the feasibility of the HRI-HMD is demonstrated by designing a prototype model.",
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"abstract": "In e-learning area, the content development method is one of the most important research topics. This paper proposes a presentation method of visual contents (a text, a still image) in synchronization with narration (sound content) and a pointer to make the efficiency of the resource allocation of cognitive memory capacity increase, and make the transmitted amount of information maximize, based on a human's cognitive-information-processing model \"Dual Channel model.\" Under various contents presentation environment {(1)Narration, (2)Text (with narration / without narration), (3)Still images, (4)Still images + text (with narration / without narration), (5)Video, and (6)Video + text} in e-learning, we performed some control experiments (measure the point of fixation for e-learning students by an eye mark recorder, memorization and a contents understanding test and the questionnaire) with or without pointer. The results showed the validity of this model and the effectiveness of the proposed content development method in e-learning.",
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"normalizedAbstract": "Object-oriented (OO) paradigm learning is not an easy task; the literature reports that regardless of whether this is learned as the first paradigm (objects-first) or vice versa (objects-later) the way to ensure that students really learn OO concepts is unclear. Learning this as a second paradigm (now preferred by 92% of the 25 world-best universities) implies different challenges than those presented in the objects-first paradigm. On the other hand, Software Visualization (SV) is the graphic display of information about a software system. There is an SV called Program Animation (PA) in which the computer determines and shows what happens during the execution of a program. It is based on some metaphor that should facilitate the understanding of programs. Several metaphors have been proposed (City, Solar-system, Islands). Most of them allow users to get a static view of the system and in some cases the exploration of its modules and its dependencies. We have developed a metaphor (and a tool called LabOO) to dynamically represent OO concepts from code. Unlike other PA systems, it aims to track what conceptually happens when a succession of OO instructions is executed. The tool receives as input a program written in an object-oriented language and displays the dynamic representation of what happens (based on the metaphor) when that program is executed. The tool facilitates the learning of concepts such as object, class, inheritance, method, and message. Results of an initial study show promising results about the value of this tool.",
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"Computer Aided Instruction",
"Computer Science Education",
"Data Visualisation",
"Object Oriented Languages",
"Object Oriented Methods",
"Object Oriented Programming",
"Program Visualisation",
"Solar System",
"PA Systems",
"OO Instructions",
"Object Oriented Language",
"Software System",
"3 D Metaphor",
"Software Code Visualization",
"Object Oriented Concept Learning",
"Objects First Paradigm",
"Objects Later Paradigm",
"Program Animation",
"Lab OO",
"Visualization",
"Technological Innovation",
"Solid Modeling",
"Codes",
"Three Dimensional Displays",
"Urban Areas",
"Writing",
"Software Visualization",
"Object Oriented Learning",
"Object Oriented Design",
"Object Oriented Thinking"
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"affiliation": "Universidad Autónoma de San Luis Potosi,Department of Computer Science,San Luis Potosi,Mexico",
"fullName": "Alberto S. Nunez-Varela",
"givenName": "Alberto S.",
"surname": "Nunez-Varela",
"__typename": "ArticleAuthorType"
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{
"affiliation": "Universidad Autónoma de San Luis Potosi,Department of Computer Science,San Luis Potosi,Mexico",
"fullName": "Francisco E. Martinez-Perez",
"givenName": "Francisco E.",
"surname": "Martinez-Perez",
"__typename": "ArticleAuthorType"
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{
"affiliation": "Universidad Autónoma de San Luis Potosi,Department of Computer Science,San Luis Potosi,Mexico",
"fullName": "Sandra E. Nava-Munoz",
"givenName": "Sandra E.",
"surname": "Nava-Munoz",
"__typename": "ArticleAuthorType"
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{
"affiliation": "Universidad Autónoma de San Luis Potosi,Department of Computer Science,San Luis Potosi,Mexico",
"fullName": "Cesar Guerra García",
"givenName": "Cesar Guerra",
"surname": "García",
"__typename": "ArticleAuthorType"
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{
"affiliation": "University of Colorado at Colorado Springs,Department of Computer Science,Colorado Springs,USA",
"fullName": "Jugal Kalita",
"givenName": "Jugal",
"surname": "Kalita",
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"affiliation": "Universidad Autónoma de Baja California Tijuana,Fac. de Ciencias Químicas e Ing,Baja California,México",
"fullName": "Reyes Juárez-Ramírez",
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"title": "Computer Modeling and Simulation, UKSIM European Symposium on",
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"abstract": "Today, it is difficult to reuse and share spatial data, because of the explosive growth of heterogeneous data and the specific characteristics of spatial data that different local agencies accumulate. A spatial analysis of subsurface spatial information, that which is part of the National Spatial Data Infrastructure, needs related spatial information such as topographical maps, geological maps, and underground facility maps. The existing methods, however, which use a standard format or a spatial datawarehouse, cannot consider semantic heterogeneity. In this study, the layered ontology model, which consists of a generic concept, a measurement unit, a spatial model, and a subsurface spatial information, was developed. Besides, the current ontology building method designed by experts is an expensive and time-consuming process. The MDA-based metamodel (UML Profile) of ontology was developed for easy understanding and flexibility of environmental change. The semantic quality of the developed ontology model was evaluated with the reasoning engine, Pellet. Improved semantic sharing and strengthened capacities to develop a GIS experts system using the knowledge representation ability of ontology are expected.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Today, it is difficult to reuse and share spatial data, because of the explosive growth of heterogeneous data and the specific characteristics of spatial data that different local agencies accumulate. A spatial analysis of subsurface spatial information, that which is part of the National Spatial Data Infrastructure, needs related spatial information such as topographical maps, geological maps, and underground facility maps. The existing methods, however, which use a standard format or a spatial datawarehouse, cannot consider semantic heterogeneity. In this study, the layered ontology model, which consists of a generic concept, a measurement unit, a spatial model, and a subsurface spatial information, was developed. Besides, the current ontology building method designed by experts is an expensive and time-consuming process. The MDA-based metamodel (UML Profile) of ontology was developed for easy understanding and flexibility of environmental change. The semantic quality of the developed ontology model was evaluated with the reasoning engine, Pellet. Improved semantic sharing and strengthened capacities to develop a GIS experts system using the knowledge representation ability of ontology are expected.",
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"normalizedAbstract": "Today, it is difficult to reuse and share spatial data, because of the explosive growth of heterogeneous data and the specific characteristics of spatial data that different local agencies accumulate. A spatial analysis of subsurface spatial information, that which is part of the National Spatial Data Infrastructure, needs related spatial information such as topographical maps, geological maps, and underground facility maps. The existing methods, however, which use a standard format or a spatial datawarehouse, cannot consider semantic heterogeneity. In this study, the layered ontology model, which consists of a generic concept, a measurement unit, a spatial model, and a subsurface spatial information, was developed. Besides, the current ontology building method designed by experts is an expensive and time-consuming process. The MDA-based metamodel (UML Profile) of ontology was developed for easy understanding and flexibility of environmental change. The semantic quality of the developed ontology model was evaluated with the reasoning engine, Pellet. Improved semantic sharing and strengthened capacities to develop a GIS experts system using the knowledge representation ability of ontology are expected.",
"fno": "3886a460",
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"Ontology Modeling",
"Semantic Sharing",
"Model Driven Architecture",
"Subsurface Spatial Information",
"GIS"
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"affiliation": null,
"fullName": "Lee Sang-Hoon",
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"doi": "10.1109/ICCP48838.2020.9105209",
"title": "Towards Learning-based Inverse Subsurface Scattering",
"normalizedTitle": "Towards Learning-based Inverse Subsurface Scattering",
"abstract": "Given images of translucent objects, of unknown shape and lighting, we aim to use learning to infer the optical parameters controlling subsurface scattering of light inside the objects. We introduce a new architecture, the inverse transport network (ITN), that aims to improve generalization of an encoder network to unseen scenes, by connecting it with a physically-accurate, differentiable Monte Carlo renderer capable of estimating image derivatives with respect to scattering material parameters. During training, this combination forces the encoder network to predict parameters that not only match groundtruth values, but also reproduce input images. During testing, the encoder network is used alone, without the renderer, to predict material parameters from a single input image. Drawing insights from the physics of radiative transfer, we additionally use material parameterizations that help reduce estimation errors due to ambiguities in the scattering parameter space. Finally, we augment the training loss with pixelwise weight maps that emphasize the parts of the image most informative about the underlying scattering parameters. We demonstrate that this combination allows neural networks to generalize to scenes with completely unseen geometries and illuminations better than traditional networks, with 38.06% reduced parameter error on average.",
"abstracts": [
{
"abstractType": "Regular",
"content": "Given images of translucent objects, of unknown shape and lighting, we aim to use learning to infer the optical parameters controlling subsurface scattering of light inside the objects. We introduce a new architecture, the inverse transport network (ITN), that aims to improve generalization of an encoder network to unseen scenes, by connecting it with a physically-accurate, differentiable Monte Carlo renderer capable of estimating image derivatives with respect to scattering material parameters. During training, this combination forces the encoder network to predict parameters that not only match groundtruth values, but also reproduce input images. During testing, the encoder network is used alone, without the renderer, to predict material parameters from a single input image. Drawing insights from the physics of radiative transfer, we additionally use material parameterizations that help reduce estimation errors due to ambiguities in the scattering parameter space. Finally, we augment the training loss with pixelwise weight maps that emphasize the parts of the image most informative about the underlying scattering parameters. We demonstrate that this combination allows neural networks to generalize to scenes with completely unseen geometries and illuminations better than traditional networks, with 38.06% reduced parameter error on average.",
"__typename": "ArticleAbstractType"
}
],
"normalizedAbstract": "Given images of translucent objects, of unknown shape and lighting, we aim to use learning to infer the optical parameters controlling subsurface scattering of light inside the objects. We introduce a new architecture, the inverse transport network (ITN), that aims to improve generalization of an encoder network to unseen scenes, by connecting it with a physically-accurate, differentiable Monte Carlo renderer capable of estimating image derivatives with respect to scattering material parameters. During training, this combination forces the encoder network to predict parameters that not only match groundtruth values, but also reproduce input images. During testing, the encoder network is used alone, without the renderer, to predict material parameters from a single input image. Drawing insights from the physics of radiative transfer, we additionally use material parameterizations that help reduce estimation errors due to ambiguities in the scattering parameter space. Finally, we augment the training loss with pixelwise weight maps that emphasize the parts of the image most informative about the underlying scattering parameters. We demonstrate that this combination allows neural networks to generalize to scenes with completely unseen geometries and illuminations better than traditional networks, with 38.06% reduced parameter error on average.",
"fno": "09105209",
"keywords": [
"Estimation Theory",
"Image Processing",
"Learning Artificial Intelligence",
"Monte Carlo Methods",
"Neural Nets",
"Rendering Computer Graphics",
"Translucent Objects",
"Unknown Shape",
"Lighting",
"Optical Parameters",
"Inverse Transport Network",
"Monte Carlo Renderer",
"Image Derivatives",
"Scattering Material Parameters",
"Scattering Parameter Space",
"Neural Networks",
"Learning Based Inverse Subsurface Scattering",
"Subsurface Scattering",
"Inverse Scattering",
"Differentiable Rendering",
"Inverse Transport Networks"
],
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{
"affiliation": "Robotics Institute, Carnegie Mellon University,Pittsburgh,PA,15213",
"fullName": "Chengqian Che",
"givenName": "Chengqian",
"surname": "Che",
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{
"affiliation": "Cornell University,Computer Science Department,Ithaca,NY,14850",
"fullName": "Fujun Luan",
"givenName": "Fujun",
"surname": "Luan",
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{
"affiliation": "University of California Irvine,Computer Science Department,Irvine,CA,92697",
"fullName": "Shuang Zhao",
"givenName": "Shuang",
"surname": "Zhao",
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"affiliation": "Cornell University,Computer Science Department,Ithaca,NY,14850",
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"affiliation": "Robotics Institute, Carnegie Mellon University,Pittsburgh,PA,15213",
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"abstract": "This study investigated the effects of thermal and frictional cues during a forced-choice material identification task. Thermal properties of the three materials presented (pine, Lexan, aluminum) were conveyed using either real materials or a temperature-controlled aluminum pad to simulate real material effusivities. Friction either varied for the real materials presented, or was constant when the temperature-controlled aluminum simulation pad was presented. Experiments 1 and 2 employed natural materials, while experiments 3 and 4 involved thermal simulations. Thermal cues alone were allowed in experiments 1 and 3 by allowing participants only static exploration with the index finger, with cutaneous contact only in the normal direction. In Experiments 2 and 4, there was dynamic exploration by lateral stroking of the index finger, allowing both thermal and friction cues to be transmitted. Dependent measures included a judgment of the material that was explored, as well as contact forces. The simulation of material effusivity was shown to be valid as participants had identification accuracies that were similar to real materials during static exploration. Material identification accuracy was higher when congruent cues were presented and was lower when incongruent cues were presented. Peak normal force was higher during static exploration, compared to dynamic. These results were interpreted in terms of a framework of single modality competition and cooperation.",
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"content": "This study investigated the effects of thermal and frictional cues during a forced-choice material identification task. Thermal properties of the three materials presented (pine, Lexan, aluminum) were conveyed using either real materials or a temperature-controlled aluminum pad to simulate real material effusivities. Friction either varied for the real materials presented, or was constant when the temperature-controlled aluminum simulation pad was presented. Experiments 1 and 2 employed natural materials, while experiments 3 and 4 involved thermal simulations. Thermal cues alone were allowed in experiments 1 and 3 by allowing participants only static exploration with the index finger, with cutaneous contact only in the normal direction. In Experiments 2 and 4, there was dynamic exploration by lateral stroking of the index finger, allowing both thermal and friction cues to be transmitted. Dependent measures included a judgment of the material that was explored, as well as contact forces. The simulation of material effusivity was shown to be valid as participants had identification accuracies that were similar to real materials during static exploration. Material identification accuracy was higher when congruent cues were presented and was lower when incongruent cues were presented. Peak normal force was higher during static exploration, compared to dynamic. These results were interpreted in terms of a framework of single modality competition and cooperation.",
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"title": "Proceedings 1992 IEEE International Conference on Robotics and Automation",
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"abstract": "Two key problem areas in the dynamics of rigid bodies with multiple frictional contacts are solved. First, the modeling of rigid body collisions is addressed. Second, an accurate model that will predict the contact forces is sought. The emphasis is on correct phenomenological and quantitative modeling. An approach to the simulation of mechanical systems with multiple, frictional constraints is proposed which is free of inconsistencies. This method is illustrated with the help of a simple planar example.<>",
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"abstract": "This work addresses a numerical study of static equilibrium states of finite dimensional systems with frictional contact and its application to the particular problem of friction between two geological layers with different viscosity. Its formulation as a complementarity eigenproblem requires the building up of mass M and stiffness K matrices to solve the eigenvalue equations for the relative deformation of two contacting materials.",
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"affiliation": "Department of PhysicsUniversity of Minho",
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"abstract": "Piecewise cubic and quartic polynomial curves with adjustable interpolation points are presented in this paper. The adjustable interpolation points are represented by local shape parameters and the given control points. Based on the choice of endpoint tangents of curve segments, piecewise cubic C1, piecewise cubic G2 and piecewise quartic C2 curves are given. The representations of the piecewise cubic C1 curves and the piecewise quartic C2 curves are integrated representations of approximating and interpolating curves. By changing the values of the local shape parameters, local approximating curves and local interpolating curves can be generated respectively.",
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"abstract": "To reduce the edge saw tooth and blur of image during the digital image interpolation, a new image interpolation method base on Pulse-Coupled Neural Networks (PCNN) is proposed. Firstly, the clusters and the propagation paths of pulse are obtained by using the synchronous pulse burst property of PCNN. Different interpolation methods are used in the inner of clusters and at the intervals of clusters to complete all interpolations of image. The results of experiments indicate that the interpolation algorithm is more effective and satisfying than the classical algorithms in terms of both Peak Signal-to-Noise Ratio ( PSNR) and visual quality.",
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"abstract": "Shape morphing, as the efficient means to enhance the visual effects, is widely used in computer animation. In this paper, we propose a novel approach to perform shape morphing for point set surface based on vertex deformation gradient. The basic idea of our approach is to interpolate the vertex deformation gradients of the input point set surfaces with polar factorization, and the in-between point set surface is reconstructed with a quadratic energy optimization by minimizing the difference between the interpolated and the actual deformation gradient. Due to the differential property of the deformation gradient and polar factorization, this optimization can avoid the shrinkage and wrinkles problem in the linear interpolation method. The vertex deformation gradient is defined on each point of the point set surface, a closed form solution of which is also presented from the view of quadratic energy optimization. Several examples are presented to demonstrate the effectiveness of our proposed method.",
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"abstract": "Detection of salient image regions without prior knowledge of their contents remains a challenge task in computer vision. In this paper, we propose a new saliency detection model based on graph Laplacian computation. This new model has two key steps: firstly, we use an image matting Laplacian model for locating the preliminary visual saliency region. Then, an unsupervised feature selection method in CIELab space is used to improve the accuracy of salient object detection. Experimental results show that the new algorithm can achieve better performance than the existing state of the art.",
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"abstract": "In architectural and mechanical engineering, man-made CAD models often have some prominent contours and regular shapes. These features are important to the visual perception. Traditional mesh simplification methods are not very suitable for this kind of models because in the simplified results some important mini structures and shape regularities are always missed. In this paper, we propose a new simplification algorithm that is tailored for man-made CAD models and can maintain the processed model’s most prominent contours and the global shape features. To achieve this purpose, in the simplification process, we avoid as much as possible contracting the vertexes on those contours. At the same time, we simplify the contour curves as a whole. The algorithm proceeds as follows. Firstly, the division contours of all surfaces are detected and all component edges are subsequently classified. Secondly, targeting at minimizing the objective function of contracting vertexes along the contours, all edges are simplified by QEM (Quadric Error Metric). In this way, the missing of important mini structures can be minimized. After this step, the intermediate simplification result is obtained, and one simplified polygon is generated for each surface’s division contour. Thirdly, using those polygons as starting point, an approximation polygon for each surface contour is generated by maximizing the shape similarity between each contour and the corresponding polygon and at the same time minimizing the change of the global features of the contours. Finally, the vertexes of all those simplified polygons in the intermediate result are adjusted based on the approximated polygons to form the final simplified model, in which the polygons will guarantee the maintenance of the global shape features of the original contours. The experiments and comparisons demonstrated that, our method not only can avoid the loss of important mini structures of the original model, but also can maintain global prominent shape features such as symmetry and edge equality, etc.",
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"content": "In architectural and mechanical engineering, man-made CAD models often have some prominent contours and regular shapes. These features are important to the visual perception. Traditional mesh simplification methods are not very suitable for this kind of models because in the simplified results some important mini structures and shape regularities are always missed. In this paper, we propose a new simplification algorithm that is tailored for man-made CAD models and can maintain the processed model’s most prominent contours and the global shape features. To achieve this purpose, in the simplification process, we avoid as much as possible contracting the vertexes on those contours. At the same time, we simplify the contour curves as a whole. The algorithm proceeds as follows. Firstly, the division contours of all surfaces are detected and all component edges are subsequently classified. Secondly, targeting at minimizing the objective function of contracting vertexes along the contours, all edges are simplified by QEM (Quadric Error Metric). In this way, the missing of important mini structures can be minimized. After this step, the intermediate simplification result is obtained, and one simplified polygon is generated for each surface’s division contour. Thirdly, using those polygons as starting point, an approximation polygon for each surface contour is generated by maximizing the shape similarity between each contour and the corresponding polygon and at the same time minimizing the change of the global features of the contours. Finally, the vertexes of all those simplified polygons in the intermediate result are adjusted based on the approximated polygons to form the final simplified model, in which the polygons will guarantee the maintenance of the global shape features of the original contours. The experiments and comparisons demonstrated that, our method not only can avoid the loss of important mini structures of the original model, but also can maintain global prominent shape features such as symmetry and edge equality, etc.",
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"normalizedAbstract": "In architectural and mechanical engineering, man-made CAD models often have some prominent contours and regular shapes. These features are important to the visual perception. Traditional mesh simplification methods are not very suitable for this kind of models because in the simplified results some important mini structures and shape regularities are always missed. In this paper, we propose a new simplification algorithm that is tailored for man-made CAD models and can maintain the processed model’s most prominent contours and the global shape features. To achieve this purpose, in the simplification process, we avoid as much as possible contracting the vertexes on those contours. At the same time, we simplify the contour curves as a whole. The algorithm proceeds as follows. Firstly, the division contours of all surfaces are detected and all component edges are subsequently classified. Secondly, targeting at minimizing the objective function of contracting vertexes along the contours, all edges are simplified by QEM (Quadric Error Metric). In this way, the missing of important mini structures can be minimized. After this step, the intermediate simplification result is obtained, and one simplified polygon is generated for each surface’s division contour. Thirdly, using those polygons as starting point, an approximation polygon for each surface contour is generated by maximizing the shape similarity between each contour and the corresponding polygon and at the same time minimizing the change of the global features of the contours. Finally, the vertexes of all those simplified polygons in the intermediate result are adjusted based on the approximated polygons to form the final simplified model, in which the polygons will guarantee the maintenance of the global shape features of the original contours. The experiments and comparisons demonstrated that, our method not only can avoid the loss of important mini structures of the original model, but also can maintain global prominent shape features such as symmetry and edge equality, etc.",
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"fullName": "Bangjun Lei",
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"title": "Subdivision Surface Simplification",
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"abstract": "A modified quadric error metric (QEM) for simplification of Loop subdivision surfaces is presented. The suggested error metric not only measures the geometric difference but also controls the smoothness and well-shapedness of the triangles that result from the decimation process. Minimizing the error with respect to the original limit surface, our method allows for drastic simplification of Loop control meshes with convenient control over the reproduction of sharp features.",
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"content": "A modified quadric error metric (QEM) for simplification of Loop subdivision surfaces is presented. The suggested error metric not only measures the geometric difference but also controls the smoothness and well-shapedness of the triangles that result from the decimation process. Minimizing the error with respect to the original limit surface, our method allows for drastic simplification of Loop control meshes with convenient control over the reproduction of sharp features.",
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"fullName": "Won-Ki Jeong",
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"title": "Digital Media and its Application in Museum & Heritage/Digital Media and its Application in Museum & Heritage, Workshop on",
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"title": "A Novel Blind Robust Digital Watermarking on 3D Meshes",
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"abstract": "A novel blind watermarking method on 3D meshes is proposed in this paper. PCA (Primary Component Analysis) is used for 3D meshes' preprocessing. Octree structure is obtained after octree partition of 3D meshes. Meaningful watermark is then embedded into SC (Single Child) nodes in bottom level of octree. This method is robust against translation, rotation, uniform scaling and vertex reordering attacks with a big embedding space. Higher nodes of octree are used to construct `Zero-watermark', which can resist simplification, noise and remeshing attacks. This method can be used directly on point cloud as it does nothing with topology of meshes. Keywords PCA, Octree-codec, robust, blind watermarking",
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"content": "A novel blind watermarking method on 3D meshes is proposed in this paper. PCA (Primary Component Analysis) is used for 3D meshes' preprocessing. Octree structure is obtained after octree partition of 3D meshes. Meaningful watermark is then embedded into SC (Single Child) nodes in bottom level of octree. This method is robust against translation, rotation, uniform scaling and vertex reordering attacks with a big embedding space. Higher nodes of octree are used to construct `Zero-watermark', which can resist simplification, noise and remeshing attacks. This method can be used directly on point cloud as it does nothing with topology of meshes. Keywords PCA, Octree-codec, robust, blind watermarking",
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"normalizedAbstract": "A novel blind watermarking method on 3D meshes is proposed in this paper. PCA (Primary Component Analysis) is used for 3D meshes' preprocessing. Octree structure is obtained after octree partition of 3D meshes. Meaningful watermark is then embedded into SC (Single Child) nodes in bottom level of octree. This method is robust against translation, rotation, uniform scaling and vertex reordering attacks with a big embedding space. Higher nodes of octree are used to construct `Zero-watermark', which can resist simplification, noise and remeshing attacks. This method can be used directly on point cloud as it does nothing with topology of meshes. Keywords PCA, Octree-codec, robust, blind watermarking",
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"fullName": "Jun Shu",
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"proceeding": {
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"title": "2015 IEEE Symposium on 3D User Interfaces (3DUI)",
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"abstract": "Chirocentric 3D user interfaces are sometimes hailed as the “holy grail” of human-computer interaction. However, implementations of these UIs can require cumbersome devices (such as tethered wearable datagloves), be limited in terms of functionality or obscure the algorithms used for hand pose and gesture recognition. These limitations inhibit designing, deploying and formally evaluating such interfaces. To ameliorate this situation, we describe the implementation of a practical chirocentric UI platform, targeted at immersive virtual environments with infrared tracking systems. Our main contributions are two machine learning techniques for the recognition of hand gestures (trajectories of the user's hands over time) and hand poses (configurations of the user's fingers) based on marker clouds and rigid body data. We report on the preliminary use of our system for the implementation of a bimanual 3DUI for a large immersive tiled display. We conclude with plans on using our system as a platform for the design and evaluation of bimanual chirocentric UIs, based on the Framework for Interaction Fidelity Analysis (FIFA).",
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"content": "Chirocentric 3D user interfaces are sometimes hailed as the “holy grail” of human-computer interaction. However, implementations of these UIs can require cumbersome devices (such as tethered wearable datagloves), be limited in terms of functionality or obscure the algorithms used for hand pose and gesture recognition. These limitations inhibit designing, deploying and formally evaluating such interfaces. To ameliorate this situation, we describe the implementation of a practical chirocentric UI platform, targeted at immersive virtual environments with infrared tracking systems. Our main contributions are two machine learning techniques for the recognition of hand gestures (trajectories of the user's hands over time) and hand poses (configurations of the user's fingers) based on marker clouds and rigid body data. We report on the preliminary use of our system for the implementation of a bimanual 3DUI for a large immersive tiled display. We conclude with plans on using our system as a platform for the design and evaluation of bimanual chirocentric UIs, based on the Framework for Interaction Fidelity Analysis (FIFA).",
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"normalizedAbstract": "Chirocentric 3D user interfaces are sometimes hailed as the “holy grail” of human-computer interaction. However, implementations of these UIs can require cumbersome devices (such as tethered wearable datagloves), be limited in terms of functionality or obscure the algorithms used for hand pose and gesture recognition. These limitations inhibit designing, deploying and formally evaluating such interfaces. To ameliorate this situation, we describe the implementation of a practical chirocentric UI platform, targeted at immersive virtual environments with infrared tracking systems. Our main contributions are two machine learning techniques for the recognition of hand gestures (trajectories of the user's hands over time) and hand poses (configurations of the user's fingers) based on marker clouds and rigid body data. We report on the preliminary use of our system for the implementation of a bimanual 3DUI for a large immersive tiled display. We conclude with plans on using our system as a platform for the design and evaluation of bimanual chirocentric UIs, based on the Framework for Interaction Fidelity Analysis (FIFA).",
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"affiliation": "Department of Computer Science, Stony Brook University, USA",
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"title": "Immersive gesture interfaces for 3D map navigation in HMD-based virtual environments",
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"abstract": "Immersive environments that approximate natural interaction with physical 3D objects are designed to increase the user's sense of presence and improve performance by allowing users to transfer existing skills and expertise from real to virtual environments. However, limitations of current Virtual Reality technologies, e.g., low-fidelity real-time physics simulations and tracking problems, make it difficult to ascertain the full potential of finger-based 3D manipulation techniques. This paper decomposes 3D object manipulation into the component movements, taking into account both physical constraints and mechanics. We fabricate five physical devices that simulate these movements in a measurable way under experimental conditions. We then implement the devices in an immersive environment and conduct an experiment to evaluate direct finger-based against ray-based object manipulation. The key contribution of this work is the careful design and creation of physical and virtual devices to study physics-based 3D object manipulation in a rigorous manner in both real and virtual setups.",
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"abstract": "After the introduction of VRML, 3D web browsing has become a popular form of networked virtual reality. However, it is still a great challenge for a novice user equipped with a regular desktop PC to navigate in most virtual worlds of moderate complexity. We think the main problem is due to the fact that a user usually uses a 2D mouse to provide low-level navigation control but the display frame rate is not high enough for this servo loop. In this paper, we consider an alternative metaphor of allowing a user to specify locations of interests on a 2D-layout map and let the system automatically generate the animation of guided tours in virtual architectural environments. Specifically, we aim to generate animations of customizable tour paths and its associated human/camera motions in an on-line manner according to high-level user inputs. We describe an auto-navigation system, in which several efficient path-planning algorithms adapted from robotics are used. This system has been implemented in Java and adopts common VRML browsers as its 3D interface. We also use the geometric model of our departmental building as an example to demonstrate the efficiency and effectiveness of the system.",
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"abstract": "In predictive redirected walking applications, planning the redirection and path prediction are crucial for a safe and effective redirection. Common predictive redirection algorithms require many simplifications and limitations concerning the real and the virtual environments to achieve a real-time performance. These limitations include for example that the tracking space needs to be convex, and only a single user is supported. In this paper, we present a novel approach called PReWAP which addresses many of these shortcomings. We introduce artificial potential fields to represent the real environment which are able to handle non-convex environments and multiple co-located users. Further, we show how this new approach can be integrated into a model predictive controller which will allow various redirection techniques and multiple gains to be applied.",
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"content": "In predictive redirected walking applications, planning the redirection and path prediction are crucial for a safe and effective redirection. Common predictive redirection algorithms require many simplifications and limitations concerning the real and the virtual environments to achieve a real-time performance. These limitations include for example that the tracking space needs to be convex, and only a single user is supported. In this paper, we present a novel approach called PReWAP which addresses many of these shortcomings. We introduce artificial potential fields to represent the real environment which are able to handle non-convex environments and multiple co-located users. Further, we show how this new approach can be integrated into a model predictive controller which will allow various redirection techniques and multiple gains to be applied.",
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"Collision Avoidance",
"Mobile Robots",
"Predictive Control",
"Virtual Reality",
"Virtual Environments",
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"Model Predictive Controller",
"Redirection Techniques",
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"Path Prediction",
"Predictive Redirection Algorithms",
"Legged Locomotion",
"Trajectory",
"Planning",
"Aerospace Electronics",
"Virtual Reality",
"Prediction Algorithms",
"Predictive Models",
"Human Centered Computing",
"Virtual Reality",
"Computing Methodologies",
"Motion Path Planning"
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"affiliation": "ETH Zurich, Innovation Center Virtual Reality, Zurich, Switzerland",
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