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The changing of dynamic models in object tracking can cause high errors in state estimation algorithms. In this paper, we propose a method, adaptive hybrid mean shift and particle filter (AHMSPF), to solve this problem. AHMSPF consists of three stages. First, the mean shift algorithm is employed to search an object candidate near the target state. Then, if this candidate is good enough, it will be...
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