On-the-fly object modeling while tracking

Zhaozheng Yin, Robert Collins

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Scopus citations

Abstract

To implement a persistent tracker, we build a set of view-dependent object appearance models adaptively and automatically while tracking an object under different viewing angles. This collection of acquired models is indexed with respect to the view sphere. The acquired models aid recovery from tracking failure due to occlusion and changing view angle. In this paper, view-dependent object appearance is represented by intensity patches around detected Harris corners. The intensity patches from a model are matched to the current frame by solving a bipartite linear assignment problem with outlier exclusion and missed inlier recovery. Based on these reliable matches, the change in object rotation, translation and scale is estimated between consecutive frames using Procrustes analysis. The experimental results show good performance using a collection of view-specific patch-based models for detection and tracking of vehicles in low-resolution airborne video.

Original languageEnglish (US)
Title of host publication2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
DOIs
StatePublished - Oct 12 2007
Event2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07 - Minneapolis, MN, United States
Duration: Jun 17 2007Jun 22 2007

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Other

Other2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR'07
CountryUnited States
CityMinneapolis, MN
Period6/17/076/22/07

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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