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Proceedings Paper

Robust visual tracking using multiple cues and improved particle filter
Author(s): Guodong Tian; Hongling Wang
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Paper Abstract

A robust visual tracking method which can be used in complex environments is presented in this paper. The color cue and the shape cue are utilized to represent the target and fused together by democratic integration method. The multi-cue object representation is incorporated into the framework of particle filter which is a powerful probabilistic method for visual tracking. To each sample of the particle filter a mean shift operation is applied, which make the samples more effective such that the number of particles needed is significantly decreased. Unlike regular mean shift, in our method the number of mean shift iterations is limited according to the reliability of the color cue for two purposes. One is to prevent the particles from being misled by mean shift when the color cue is unreliable. The other is to reduce the waste of computation. Experimental results show that our method greatly improves the robustness and reduces the computational cost compared with the state-of-art methods.

Paper Details

Date Published: 30 October 2009
PDF: 10 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74953E (30 October 2009); doi: 10.1117/12.832755
Show Author Affiliations
Guodong Tian, Beijing Univ. of Posts and Telecommunications (China)
Hongling Wang, Beijing Univ. of Posts and Telecommunications (China)

Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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