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Boosted Interactively Distributed Particle Filter for automatic multi-object tracking

8 years 8 months ago
Boosted Interactively Distributed Particle Filter for automatic multi-object tracking
In this paper, we propose a Boosted Interactively Distributed Particle Filter (BIDPF) to address the problem of automatic multi-object tracking in the application of player tracking in broadcast soccer video. The interactively distributed particle filter technique (IDPF) is adopted to handle the mutual occlusions among targets. The proposal distribution using a mixture model that incorporates information from the dynamic model and the boosting detection is introduced into the IDPF framework. The boosting proposal distribution quickly detects targets, while the IDPF process keeps the identity of targets during mutual occlusions. Moreover, the foreground obervation is extracted by using the color model of the playfield to speed up the boosting detection and reduce false alarms. The foreground is also used to develop a data-driven potential model to improve the IDPF performance. We test the proposed approach on several video sequences and the results demonstrate that our system is able t...
Yi Wu, Xiaofeng Tong, Yimin Zhang, Hanqing Lu
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICIP
Authors Yi Wu, Xiaofeng Tong, Yimin Zhang, Hanqing Lu
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