State-driven particle filter for multi-person tracking
ACIVS'12 Proceedings of the 14th international conference on Advanced Concepts for Intelligent Vision Systems
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The effectiveness of the conventional Mean Shift tracking algorithm diminishes for fast moving targets and complete occlusion. In this paper an improved Mean Shift algorithm comprising a fast failure recovery strategy that aims to deal with randomly moving targets and complete occlusion as encountered in crowded scenes is presented. Experimental results show that after complete occlusion or target loss, the new algorithm can effectively recover and continue to successfully track targets in complex scenarios.