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Proceedings Paper

Deformable target tracking via particle filter
Author(s): Junqing Wang; Zelin Shi; Shabai Huang
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Paper Abstract

We propose an algorithm, which tracks a deformable object in complex scene based on Bayesian estimation in Particle filter framework. In Particle filter framework, both dynamic model and measure model of Particle filter, which utilizes information of structure of target edges and gray level distribution of neighbors of target edges, are respectively constructed in term of interframe correlation in the context of object tracking. The fuzzy metric is constructed to measure the similarity between histograms of template and candidate sub-regions. The tracking window can be adaptively changed with the variation of object appearance. The strategy for template update is applied according to confidence level threshold. Both judgement of occlusion and solution to occlusion are given in term of threshold and temporal window. Those experimental results illustrate that this algorithm can stably track deformable target under complex background at the low computing cost.

Paper Details

Date Published: 3 November 2005
PDF: 7 pages
Proc. SPIE 6044, MIPPR 2005: Image Analysis Techniques, 60440V (3 November 2005); doi: 10.1117/12.654792
Show Author Affiliations
Junqing Wang, Shenyang Institute of Automation, Chinese Academy of Sciences (China)
Graduate School of Chinese Academy of Sciences (China)
Zelin Shi, Graduate School of Chinese Academy of Sciences (China)
Shabai Huang, Graduate School of Chinese Academy of Sciences (China)

Published in SPIE Proceedings Vol. 6044:
MIPPR 2005: Image Analysis Techniques
Deren Li; Hongchao Ma, Editor(s)

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