Abstract：A novel particle filter based on mean shift is presented. The standard particle filter is supposed to track a target in a whole state space. The proposed algorithm decomposes the target state space into two independent subspaces: a displacement subspace and a deformation subspace. Mean shift algorithm embedded in the particle filter is utilized to track the state transfer in displacement subspace while the particle filter is used to track the transfer in deformation space. In this way, the particle filter tracks the target in a lower order subspace and thus its realtime performance is improved. On the other hand, the mean shift algorithm is granted a new capability to track the target deformation. The validity and efficiency of the new algorithm are demonstrated by a series of real time tracking experiments.
刘志明，韦巍. 基于均值变换的ParticleFilter实时跟踪算法[J]. 模式识别与人工智能, 2006, 19(6): 825-830.
LIU ZhiMing, WEI Wei. Object Tracking Using Particle Filter Based on Mean Shift. , 2006, 19(6): 825-830.
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2006, Vol. 19 
