Spatial divide and conquer with motion cues for tracking through clutter

Zhaozheng Yin, Robert Collins

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

18 Scopus citations

Abstract

Tracking can be considered a two-class classification problem between the foreground object and its surrounding background. Feature selection to better discriminate object from background is thus a critical step to ensure tracking robustness. In this paper, a spatial divide and conquer approach is used to subdivide foreground and background into smaller regions, with different features being selected to distinguish between different pairs of object and background regions. Temporal cues are incorporated into the process using foreground motion prediction and motion segmentation. Appearance weight maps tailored to each spatial region are merged and combined with the motion information to form a joint weight image suitable for mean-shift tracking. Examples are presented to illustrate that divide and conquer feature selection combined with motion cues handles spatial background clutter and camouflage well.

Original languageEnglish (US)
Title of host publicationProceedings - 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
Pages570-577
Number of pages8
DOIs
StatePublished - 2006
Event2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006 - New York, NY, United States
Duration: Jun 17 2006Jun 22 2006

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume1
ISSN (Print)1063-6919

Other

Other2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2006
Country/TerritoryUnited States
CityNew York, NY
Period6/17/066/22/06

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition

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