Christopher R. Wren and Alex P. Pentland
To Appear in: Image and Vision Computing
This paper describes a real-time, fully-dynamic, \mbox{3-D} person tracking system that is able to tolerate full (temporary) occlusions and whose performance is substantially unaffected by the presence of multiple people. The framework provides a mathematically concise formulation for incorporating a wide variety of physical constraints and probabilistic influences. The framework takes the form of a recursive filter that enables pixel-level, probabilistic processes to take advantage of the contextual knowledge encoded in the higher-level models. Results are shown that demonstrate both qualitative and quantitative gains in tracking performance.
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