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Lecture Notes in Computer Science
3D visual tracking is useful for many applications. In this paper, we propose two different ways for different system configurations to optimize particle filter for enhancing 3D tracking performances. On the one hand, a new data fusion method is proposed to obtain the optimal importance density function for active vision systems. With this method, the importance density function in particle filter can be modified to represent posterior states by particle crowds in a better way. Thus, it makesdoi:10.1007/978-3-642-16584-9_71 fatcat:yfxoss74rzcupcppwwnn2xpssm