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M.I.T Media Laboratory Perceptual Computing Section Technical Report No. 415
Edited version published in the Proceedings of the Third IEEE International Conference
on Automatic Face and Gesture Recognition, April 14-16, 1998 in Nara, Japan.

Dynamic Models of Human Motion

Christopher R. Wren and Alex P. Pentland

MIT Media Laboratory; 20 Ames Street; Cambridge MA 02139 USA


This paper describes a framework for human motion understanding, defined here as estimation of the physical state of the body (the Plant) combined with interpretation of that part of the motion that cannot be predicted by the plant alone (the Behavior). The described behavior system operates in conjunction with a real-time, fully-dynamic, 3-D person tracking system that provides a mathematically concise formulation for incorporating a wide variety of physical constraints and probabilistic influences. The framework takes the form of a non-linear recursive filter that enables lower-level, probabilistic processes to take advantage of the contextual knowledge encoded in the higher-level models.


Christopher R. Wren