K. Bürger, Roland Fraedrich, D. Merhof, R. Westermann
{"title":"用于不确定粒子轨迹交互式可视化的即时访问地图","authors":"K. Bürger, Roland Fraedrich, D. Merhof, R. Westermann","doi":"10.1117/12.906872","DOIUrl":null,"url":null,"abstract":"Visitation maps are an effective means to analyze the frequency of similar occurrences in large sets of uncertain particle \ntrajectories. A visitation map counts for every cell the number of trajectories passing through this cell, and it can then \nbe used to visualize pathways of a certain visitation percentage. In this paper, we introduce an interactive method for the \nconstruction and visualization of high-resolution 3D visitation maps for large numbers of trajectories. To achieve this we \nemploy functionality on recent GPUs to efficiently voxelize particle trajectories into a 3D texture map. In this map we \nvisualize envelopes enclosing particle pathways that are followed by a certain percentage of particles using direct volume \nrendering techniques. By combining visitation map construction with GPU-based Monte-Carlo particle tracing we can \neven demonstrate the instant construction of a visitation map from a given vector field. To facilitate the visualization of \nsafety regions around possible trajectories, we further generate Euclidean distance transform volumes to these trajectories \non the fly. We demonstrate the application of our approach for visualizing the variation of stream lines in 3D flows due \nto different numerical integration schemes or errors introduced through data transformation operations, as well as for \nvisualizing envelopes of probabilistic fiber bundles in DTI tractography.","PeriodicalId":89305,"journal":{"name":"Visualization and data analysis","volume":"69 1","pages":"82940P"},"PeriodicalIF":0.0000,"publicationDate":"2012-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Instant visitation maps for interactive visualization of uncertain particle trajectories\",\"authors\":\"K. Bürger, Roland Fraedrich, D. Merhof, R. Westermann\",\"doi\":\"10.1117/12.906872\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Visitation maps are an effective means to analyze the frequency of similar occurrences in large sets of uncertain particle \\ntrajectories. A visitation map counts for every cell the number of trajectories passing through this cell, and it can then \\nbe used to visualize pathways of a certain visitation percentage. In this paper, we introduce an interactive method for the \\nconstruction and visualization of high-resolution 3D visitation maps for large numbers of trajectories. To achieve this we \\nemploy functionality on recent GPUs to efficiently voxelize particle trajectories into a 3D texture map. In this map we \\nvisualize envelopes enclosing particle pathways that are followed by a certain percentage of particles using direct volume \\nrendering techniques. By combining visitation map construction with GPU-based Monte-Carlo particle tracing we can \\neven demonstrate the instant construction of a visitation map from a given vector field. To facilitate the visualization of \\nsafety regions around possible trajectories, we further generate Euclidean distance transform volumes to these trajectories \\non the fly. We demonstrate the application of our approach for visualizing the variation of stream lines in 3D flows due \\nto different numerical integration schemes or errors introduced through data transformation operations, as well as for \\nvisualizing envelopes of probabilistic fiber bundles in DTI tractography.\",\"PeriodicalId\":89305,\"journal\":{\"name\":\"Visualization and data analysis\",\"volume\":\"69 1\",\"pages\":\"82940P\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-01-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Visualization and data analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.906872\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Visualization and data analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.906872","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Instant visitation maps for interactive visualization of uncertain particle trajectories
Visitation maps are an effective means to analyze the frequency of similar occurrences in large sets of uncertain particle
trajectories. A visitation map counts for every cell the number of trajectories passing through this cell, and it can then
be used to visualize pathways of a certain visitation percentage. In this paper, we introduce an interactive method for the
construction and visualization of high-resolution 3D visitation maps for large numbers of trajectories. To achieve this we
employ functionality on recent GPUs to efficiently voxelize particle trajectories into a 3D texture map. In this map we
visualize envelopes enclosing particle pathways that are followed by a certain percentage of particles using direct volume
rendering techniques. By combining visitation map construction with GPU-based Monte-Carlo particle tracing we can
even demonstrate the instant construction of a visitation map from a given vector field. To facilitate the visualization of
safety regions around possible trajectories, we further generate Euclidean distance transform volumes to these trajectories
on the fly. We demonstrate the application of our approach for visualizing the variation of stream lines in 3D flows due
to different numerical integration schemes or errors introduced through data transformation operations, as well as for
visualizing envelopes of probabilistic fiber bundles in DTI tractography.