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Proceedings Paper

Multifeature fusion tracking in a particle filter framework
Author(s): Lizhi Pei; Peng Zhang; Runsheng Wang
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Paper Abstract

Particle filtering has been proven very successful for non-gaussian and non-linear estimation problems. In this study we used the particle filtering technique with multiple features to track the moving object effectively in video image. The object tracking system relies on the deterministic search of window, whose color content matches a reference histogram model. A simple histogram-based color model is used to develop our observation system. Secondly and finally, we describe a new approach for moving object tracking with particle filter by PCA transform technique. Our observation system of particle filter uses the combination of color and PCA features with a likelihood measurement. Experiment results show that the algorithm can effectively handle the effect of illumination, and is stable and robust.

Paper Details

Date Published: 30 October 2009
PDF: 5 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 74954T (30 October 2009); doi: 10.1117/12.833995
Show Author Affiliations
Lizhi Pei, National Univ. of Defense Technology (China)
Peng Zhang, National Univ. of Defense Technology (China)
Runsheng Wang, National Univ. of Defense Technology (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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