Recursive Models of Human Motion
Perception is mediated by expectation.
If we hope to build computers that help people, we must build computers
that are able to understand people. One step is the ability to understand
human activity. Human motion is a very complex phenomenon, but it is not
entirely arbitrary. The physical limitations of the body, the patterns
encoded into our physiological structures, and even the habits of motion
that we acquire over time, all combine to provide strong constraints on how
we move. Modeling these constraints is an important step toward eventual
understanding.
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Understanding Expressive Action
- Christopher R. Wren
MIT EECS Ph.D. Thesis, March 2000.
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Understanding Purposeful Human Motion
- Christopher R. Wren, Brian P. Clarkson, and Alex P. Pentland
Proceedings of the Fourth IEEE International
Conference on Automatic Face and Gesture Recognition,
Grenoble, France, March 26-30, 2000.
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Dynaman: Recursive Modeling of Human Motion
- Christopher R. Wren and Alex P. Pentland
Image and Vision Computing
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Dynamic Modeling of Human Motion
- Christopher R. Wren and Alex P. Pentland
Proceedings of the Third IEEE International
Conference on Automatic Face and Gesture Recognition, Nara,
Japan, April 14-16, 1998
This technology is built on the SmartDesk framework
Christopher R. Wren, wren@media.mit.edu
Last modified: Thu Sep 24 15:50:02 EDT 1998