The network traffic data is interpreted differently by people in different sectors. This paper proposes a framework for hierarchically visualizing the network traffic data, and customizes a set of the classic approaches or algorithms to produce visualizations in different levels. Based on the framework, we developed a prototype system Hint Vis to support analyzing network traffic data in different levels by constructing layered semantic network traffic objects and producing hierarchical visualizations. The usability of Hint Vis is demonstrated by visualizing packets going through the gateway in a LAN. Depending on the hierarchical visualizations, analysts are able to semantically navigate in the network traffic data and concentrate on what they need.
{"title":"HintVis: The Hierarchical Visualization of Network Traffic Data","authors":"Hengyuan Zhang, Xiaowu Chen, Haifeng Hu","doi":"10.1109/ICVRV.2013.33","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.33","url":null,"abstract":"The network traffic data is interpreted differently by people in different sectors. This paper proposes a framework for hierarchically visualizing the network traffic data, and customizes a set of the classic approaches or algorithms to produce visualizations in different levels. Based on the framework, we developed a prototype system Hint Vis to support analyzing network traffic data in different levels by constructing layered semantic network traffic objects and producing hierarchical visualizations. The usability of Hint Vis is demonstrated by visualizing packets going through the gateway in a LAN. Depending on the hierarchical visualizations, analysts are able to semantically navigate in the network traffic data and concentrate on what they need.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121388319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper we present a WebVRGIS based Interactive On line 3D Virtual Community which is achieved based on WebGIS technology and web VR technology. It is Multi-Dimensional(MD) web geographic information system (WebGIS) based 3D interactive on line virtual community which is a virtual real-time 3D communication systems and web systems development platform. It is capable of running on a variety of browsers. In this work, four key issues are studied: (1) Multi-source MD geographical data fusion of the WebGIS, (2) scene combination with 3D avatar, (3) massive data network dispatch, and (4) multi-user avatar real-time interactive. Our system is divided into three modules: data preprocessing, background management and front end user interaction. The core of the front interaction module is packaged in the MD map expression engine 3GWebMapper and the free plug-in network 3D rendering engine WebFlashVR. We have evaluated the robustness of our system on three campus of Ocean University of China(OUC) as a testing base. The results shows high efficiency, easy to use and robustness of our system.
{"title":"WebVRGIS: WebGIS Based Interactive Online 3D Virtual Community","authors":"Zhihan Lu, S. Réhman, Ge Chen","doi":"10.1109/ICVRV.2013.23","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.23","url":null,"abstract":"In this paper we present a WebVRGIS based Interactive On line 3D Virtual Community which is achieved based on WebGIS technology and web VR technology. It is Multi-Dimensional(MD) web geographic information system (WebGIS) based 3D interactive on line virtual community which is a virtual real-time 3D communication systems and web systems development platform. It is capable of running on a variety of browsers. In this work, four key issues are studied: (1) Multi-source MD geographical data fusion of the WebGIS, (2) scene combination with 3D avatar, (3) massive data network dispatch, and (4) multi-user avatar real-time interactive. Our system is divided into three modules: data preprocessing, background management and front end user interaction. The core of the front interaction module is packaged in the MD map expression engine 3GWebMapper and the free plug-in network 3D rendering engine WebFlashVR. We have evaluated the robustness of our system on three campus of Ocean University of China(OUC) as a testing base. The results shows high efficiency, easy to use and robustness of our system.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124388615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Multi-camera activity analysis is a key point in video surveillance of many wide-area scenes, such as airports, underground stations, shopping mall and road junctions. On the basis of previous work, this paper presents a new feature learning method based on Slow Feature Analysis (SFA) to understand activities observed across the network of cameras. The main contribution of this paper can be summarized as follows: (1) It is the first time that SFA-based learning method is introduced to multi-camera activity understanding, (2) It presents an evaluation to examine the effectiveness of SFA-based method to facilitate the learning of inter-camera activity pattern dependencies, and (3) It estimates the sensitivity of learning inter-camera time delayed dependency given different training size, which is a critical factor for accurate dependency learning and has not been largely studied by existing work before. Experiments are carried out on a dataset obtained in a trident roadway. The results demonstrate that the SFA-based method outperforms the sate of the art.
{"title":"Slow Feature Analysis for Multi-Camera Activity Understanding","authors":"Lei Zhang, Xiaoqiang Lu, Yuan Yuan","doi":"10.1109/ICVRV.2013.46","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.46","url":null,"abstract":"Multi-camera activity analysis is a key point in video surveillance of many wide-area scenes, such as airports, underground stations, shopping mall and road junctions. On the basis of previous work, this paper presents a new feature learning method based on Slow Feature Analysis (SFA) to understand activities observed across the network of cameras. The main contribution of this paper can be summarized as follows: (1) It is the first time that SFA-based learning method is introduced to multi-camera activity understanding, (2) It presents an evaluation to examine the effectiveness of SFA-based method to facilitate the learning of inter-camera activity pattern dependencies, and (3) It estimates the sensitivity of learning inter-camera time delayed dependency given different training size, which is a critical factor for accurate dependency learning and has not been largely studied by existing work before. Experiments are carried out on a dataset obtained in a trident roadway. The results demonstrate that the SFA-based method outperforms the sate of the art.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127385162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Virtual Geographic Environment (VGE) is still a hot topic of research in recent years, but the research on symbols which express of the VGE is rare. An automatic generation model of VGE symbols based on semantic features analysis is propounded in this paper following that the concept, structure and characteristics of VGE symbols are analyzed. The method of achieving the automatic generation is also discussed. This paper's research is a useful exploration for knowledge analysis and mining in the virtual geographic environment.
{"title":"New Thought of Virtual Geographic Environment Symbols","authors":"Keman Peng, Jiangpeng Tian, Qing Xia, Lan Zhang","doi":"10.1109/ICVRV.2013.67","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.67","url":null,"abstract":"Virtual Geographic Environment (VGE) is still a hot topic of research in recent years, but the research on symbols which express of the VGE is rare. An automatic generation model of VGE symbols based on semantic features analysis is propounded in this paper following that the concept, structure and characteristics of VGE symbols are analyzed. The method of achieving the automatic generation is also discussed. This paper's research is a useful exploration for knowledge analysis and mining in the virtual geographic environment.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129030032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The resolution of space object images observed by ground-based telescope is greatly limited due to the influence of atmospheric turbulence. An improved blind deconvolution method is presented to enhance the performance of turbulence degraded images restoration. Firstly, a mixed noise model based blind deconvolution cost function is deduced under Gaussian and Poisson noise contamination of measurement. Then, point spread function (PSF) is described by wavefront phase aberrations in the pupil plane according to Fourier Optics theory. In this way, the estimation of PSF is generated from the wavefront phase parameterization instead of pixel domain value. Lastly, the cost function is converted from constrained optimization problem to non-constrained optimization problem by means of parameterization of object image and PSF. Experimental results show that the proposed method can recover high quality image from turbulence degraded images effectively.
{"title":"Phase Estimation Based Blind Deconvolution for Turbulence Degraded Images","authors":"Afeng Yang, Min Lu, Shuhua Teng, Jixiang Sun","doi":"10.1109/ICVRV.2013.53","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.53","url":null,"abstract":"The resolution of space object images observed by ground-based telescope is greatly limited due to the influence of atmospheric turbulence. An improved blind deconvolution method is presented to enhance the performance of turbulence degraded images restoration. Firstly, a mixed noise model based blind deconvolution cost function is deduced under Gaussian and Poisson noise contamination of measurement. Then, point spread function (PSF) is described by wavefront phase aberrations in the pupil plane according to Fourier Optics theory. In this way, the estimation of PSF is generated from the wavefront phase parameterization instead of pixel domain value. Lastly, the cost function is converted from constrained optimization problem to non-constrained optimization problem by means of parameterization of object image and PSF. Experimental results show that the proposed method can recover high quality image from turbulence degraded images effectively.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131510924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jiashu Dai, Ting-quan Deng, Tianzhen Dong, Kejia Yi
In a real surveillance scenario, tracking an object usually interfered by the background information. To deal with this problem, this paper proposed a video tracking algorithm based on tensor neighborhood preserving discriminant embedding. The neighborhood relationships of an object within object class and background class are reasonable described by the object image patches similarities which are defined by histograms of oriented gradients. In order to distinguish between the object and background, we formulate an discriminant objective function that maximizing the scatters of object within object class while minimizing the scatters of object with background class, meanwhile maintaining the same neighborhood topological structure in lower dimensional tensor subspace. Finally, we can get the optimal estimate of the object state through Bayesian estimation framework. Experimental evaluations against two state-of-the-art tracking methods demonstrate the robustness and effectiveness of the proposed algorithm.
{"title":"Video Tracking via Tensor Neighborhood Preserving Discriminant Embedding","authors":"Jiashu Dai, Ting-quan Deng, Tianzhen Dong, Kejia Yi","doi":"10.1109/ICVRV.2013.47","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.47","url":null,"abstract":"In a real surveillance scenario, tracking an object usually interfered by the background information. To deal with this problem, this paper proposed a video tracking algorithm based on tensor neighborhood preserving discriminant embedding. The neighborhood relationships of an object within object class and background class are reasonable described by the object image patches similarities which are defined by histograms of oriented gradients. In order to distinguish between the object and background, we formulate an discriminant objective function that maximizing the scatters of object within object class while minimizing the scatters of object with background class, meanwhile maintaining the same neighborhood topological structure in lower dimensional tensor subspace. Finally, we can get the optimal estimate of the object state through Bayesian estimation framework. Experimental evaluations against two state-of-the-art tracking methods demonstrate the robustness and effectiveness of the proposed algorithm.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"9 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126005628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
3D scene segmentation is important but difficult especially when one object makes contact with another in scenes. This paper presents a new algorithm for automatic object extraction with the help of a shape repository, which is an effective approach applicable to 3D meshes without scene graphs. In the new algorithm, connected components are first computed and taken as initial clusters. Then, based on the global shape similarities between the supposed mergence of two shapes and any shape from the shape repository, we make a decision as to whether two close shapes should be merged or not. Our iterative merging scheme is performed until none of the close shapes can be merged. Experiments show that this method is very efficient on some indoor scenes.
{"title":"3D Scene Segmentation with a Shape Repository","authors":"L. Wan, Z. Miao, Dongxia Chang, Yigang Cen","doi":"10.1109/ICVRV.2013.48","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.48","url":null,"abstract":"3D scene segmentation is important but difficult especially when one object makes contact with another in scenes. This paper presents a new algorithm for automatic object extraction with the help of a shape repository, which is an effective approach applicable to 3D meshes without scene graphs. In the new algorithm, connected components are first computed and taken as initial clusters. Then, based on the global shape similarities between the supposed mergence of two shapes and any shape from the shape repository, we make a decision as to whether two close shapes should be merged or not. Our iterative merging scheme is performed until none of the close shapes can be merged. Experiments show that this method is very efficient on some indoor scenes.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115005691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sunburst is a hierarchical data visualization method which is filled by radial sectors, for the problem that sectors of Sunburst are placed in disorder and space utilization rate is low, Self-Adapting Sunburst Algorithm (SASA) has been proposed. Nodes are allocated their areas according to their attribute value, and siblings of same parents are made in ascending order according to the size of areas, adjusting the position of sectors. Meanwhile, based on total number of nodes in each layer, SASA dynamically determines width of this circular ring, following the principle "more nodes wider circular ring and fewer nodes thinner circular ring", and in this way, it can optimize the size of nested ring in Sunburst and improve space utilization rate. Finally, User Locating Efficiency (ULE) and Arc Ratio (AR) is put forward to examine SASA, Experimental results show that this algorithm can indeed optimize sector's arrangement, as well as make space utilization better.
{"title":"A Hierarchical Data Visualization Algorithm: Self-Adapting Sunburst Algorithm","authors":"Gong Li-wei, Chen Yi, Zhang Xin-Yue, Sun Yue-Hong","doi":"10.1109/ICVRV.2013.36","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.36","url":null,"abstract":"Sunburst is a hierarchical data visualization method which is filled by radial sectors, for the problem that sectors of Sunburst are placed in disorder and space utilization rate is low, Self-Adapting Sunburst Algorithm (SASA) has been proposed. Nodes are allocated their areas according to their attribute value, and siblings of same parents are made in ascending order according to the size of areas, adjusting the position of sectors. Meanwhile, based on total number of nodes in each layer, SASA dynamically determines width of this circular ring, following the principle \"more nodes wider circular ring and fewer nodes thinner circular ring\", and in this way, it can optimize the size of nested ring in Sunburst and improve space utilization rate. Finally, User Locating Efficiency (ULE) and Arc Ratio (AR) is put forward to examine SASA, Experimental results show that this algorithm can indeed optimize sector's arrangement, as well as make space utilization better.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133511514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A Level-of-Detail model is proposed to improve the efficiency of hair rendering. The model considers the simplification on both strands density and controlling points of strand curves, which common used uniquely by traditional solutions. On the other hand, we provide artists a novel constraint tool that inspired by existing hair styling method. Artists can determine LOD parameters value in 3D space by their own ideas but not only by viewing distance, whether there is a hair model or not. Another benefit of spatial constraint using is that those separating hair strands can clamp together dynamically if they are growing under working from the same hairstyle constraint. Thus strands can merge into hair wisp model through K-d tree searching for nearest control points. Result shows a notable improvement on photo realistic hair rendering with our model.
{"title":"Level-of-Detail Modeling with Artist-Defined Constraints for Photorealistic Hair Rendering","authors":"Li Kang, Jin Wuxia, Gen Guohua, Han Yi","doi":"10.1109/ICVRV.2013.43","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.43","url":null,"abstract":"A Level-of-Detail model is proposed to improve the efficiency of hair rendering. The model considers the simplification on both strands density and controlling points of strand curves, which common used uniquely by traditional solutions. On the other hand, we provide artists a novel constraint tool that inspired by existing hair styling method. Artists can determine LOD parameters value in 3D space by their own ideas but not only by viewing distance, whether there is a hair model or not. Another benefit of spatial constraint using is that those separating hair strands can clamp together dynamically if they are growing under working from the same hairstyle constraint. Thus strands can merge into hair wisp model through K-d tree searching for nearest control points. Result shows a notable improvement on photo realistic hair rendering with our model.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133041268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A variational segmentation approach of color-texture images is proposed in this lecture. To improve the description ability, we use our proposed color-texture descriptor in [1] to describe color-texture. Due to heterogeneous image objects and nonlinear variation exist in color-texture image, it is not appropriate to use one single/multiple constant in Chan and Vese model for describing each phase [2-3]. Consequently, a multiphase successive active contour model (MSACM) with the multi variable Gaussian distribution is proposed to describe each phase. For geodesic active contour (GAC) has a stronger ability in capturing boundary, therefore, a newly approach inco rporates the GAC with MSACM model is designed to enhance the detection ability for concave edge. As the optimization of our proposed MSACM model is NP hard problem, we cannot discrete the variational energy function of MSACM model directly, and then the multilayer graph method is adopted for getting approximate solution. To investigate the segmentation performance, lastly, a substantial of color texture images are applied for testing, and our approach achieves a significantly better performance on capture ability of concave boundary, and accuracy.
{"title":"Variational Formulation and Multilayer Graph Based Color-Texture Image Segmentation in Multiphase","authors":"Yong Yang, Ling Guo, Tianjiang Wang","doi":"10.1109/ICVRV.2013.17","DOIUrl":"https://doi.org/10.1109/ICVRV.2013.17","url":null,"abstract":"A variational segmentation approach of color-texture images is proposed in this lecture. To improve the description ability, we use our proposed color-texture descriptor in [1] to describe color-texture. Due to heterogeneous image objects and nonlinear variation exist in color-texture image, it is not appropriate to use one single/multiple constant in Chan and Vese model for describing each phase [2-3]. Consequently, a multiphase successive active contour model (MSACM) with the multi variable Gaussian distribution is proposed to describe each phase. For geodesic active contour (GAC) has a stronger ability in capturing boundary, therefore, a newly approach inco rporates the GAC with MSACM model is designed to enhance the detection ability for concave edge. As the optimization of our proposed MSACM model is NP hard problem, we cannot discrete the variational energy function of MSACM model directly, and then the multilayer graph method is adopted for getting approximate solution. To investigate the segmentation performance, lastly, a substantial of color texture images are applied for testing, and our approach achieves a significantly better performance on capture ability of concave boundary, and accuracy.","PeriodicalId":179465,"journal":{"name":"2013 International Conference on Virtual Reality and Visualization","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114807175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：