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Visual Tracking in High-Dimensional State Space by Appearance-Guided Particle Filtering

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3 Author(s)
Wen-Yan Chang ; Inst. of Inf. Sci., Acad. Sinica, Taipei ; Chu-Song Chen ; Yong-Dian Jian

In this paper, we propose a new approach, appearance-guided particle filtering (AGPF), for high degree-of-freedom visual tracking from an image sequence. This method adopts some known attractors in the state space and integrates both appearance and motion-transition information for visual tracking. A probability propagation model based on these two types of information is derived from a Bayesian formulation, and a particle filtering framework is developed to realize it. Experimental results demonstrate that the proposed method is effective for high degree-of-freedom visual tracking problems, such as articulated hand tracking and lip-contour tracking.

Published in:

Image Processing, IEEE Transactions on  (Volume:17 ,  Issue: 7 )