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Particle Filter Tracking Based on Fragment Multi-cue Integration

Lichuan Gu, Jianxiao Liu, Chengji Wang, Mengru Cao


A novel particle filter tracking algorithm is presented in this paper by using fragment multi-cue integration. The proposed tracker enhances the suggested FragTracker algorithm to employ an adaptive cue integration scheme. This is done by employing particle filter framework, each particle represents an image fragment described by edge and color cues, the weight of each particle is designed to be updated by adaptive multi-cue integration. Additional, the template of each fragment are updated during tracking by distinguishing occlusions and appearance changes, which is done by risk decision theory. The template is unchanged if the target is occluded; some fragments of template are updated if appearance change. In the experiments and comparisons, the applicable conditions of the proposed adaptive model are discussed, and its robustness and effectiveness are demonstrated.


particle filter tracking, fragments tracking, multi-cue integration.

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