{"title":"Collision and event detection using geometric features in spatio-temporal volumes","authors":"M. Bolduc, F. Deschênes","doi":"10.1109/CRV.2005.26","DOIUrl":null,"url":null,"abstract":"In video sequences, edges in 2D images (frames) produces 3D surface in the spatio-temporal volume, in this paper, we propose to consider temporal collisions between edges, and thus objects, as 3D ridges in the spatio-temporal volume. Collisions (i.e. ridge points) can be located using the maximum principal curvature and the principal curvature direction. Using the detected collisions, we then propose a technique to detect overlapping objects events in an image sequence, by neither computing depth or optical flow. We present successful experiments on real image sequences.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"337 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2005.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In video sequences, edges in 2D images (frames) produces 3D surface in the spatio-temporal volume, in this paper, we propose to consider temporal collisions between edges, and thus objects, as 3D ridges in the spatio-temporal volume. Collisions (i.e. ridge points) can be located using the maximum principal curvature and the principal curvature direction. Using the detected collisions, we then propose a technique to detect overlapping objects events in an image sequence, by neither computing depth or optical flow. We present successful experiments on real image sequences.