{"title":"Object tracking via the dynamic velocity Hough transform","authors":"P. Lappas, J. Carter, R. Damper","doi":"10.1109/ICIP.2001.958505","DOIUrl":null,"url":null,"abstract":"Motion tracking is an important task in computer vision. A new technique, the dynamic velocity Hough transform (DVHT), for tracking of parametric objects is described that extends the velocity Hough transform (VHT) to cater for arbitrary motion. Like the VHT, the new technique processes the whole image sequence, gathering global evidence of motion and structure. However, we do not assume constant linear velocity but rather allow arbitrary velocity. The method tries to find an optimal, smooth trajectory in the parameter space with maximum energy, where the latter incorporates both the structure of the moving object and the smoothness of motion. The constrained optimisation problem is solved using a temporal (time-delay) dynamic programming algorithm. Tracking in noise is much superior to the standard Hough transform.","PeriodicalId":291827,"journal":{"name":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2001.958505","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Motion tracking is an important task in computer vision. A new technique, the dynamic velocity Hough transform (DVHT), for tracking of parametric objects is described that extends the velocity Hough transform (VHT) to cater for arbitrary motion. Like the VHT, the new technique processes the whole image sequence, gathering global evidence of motion and structure. However, we do not assume constant linear velocity but rather allow arbitrary velocity. The method tries to find an optimal, smooth trajectory in the parameter space with maximum energy, where the latter incorporates both the structure of the moving object and the smoothness of motion. The constrained optimisation problem is solved using a temporal (time-delay) dynamic programming algorithm. Tracking in noise is much superior to the standard Hough transform.