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Multi-Pose Face Tracking Using Particle Filter and Checklist

By 王凱民 and Kai-Ming Wang


[[abstract]]Automatic and robust detection and tracking of faces is essential in the surveillance application, especially when the main targets are about people. In this research, we propose a novel multi-pose face tracking method. Our method is based on the Condensation algorithm with modified transition and likelihood function. A dynamic update structure, called Checklist, is designed to help identify the current face post from the target history and for storing the latest face. Furthermore, template-matching-based algorithm is used to recover lost face during tracking. Experimental results show that the proposed algorithm can deal with the change of poses and illumination. It is also able to extract target face information even when the tracking is lost for whatever reason.

Topics: 多視角的人臉追蹤;粒子濾波, multi-pose face tracking;particle filter, [[classification]]42
Year: 2011
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