Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision

Motion Capture from Movies

Jim Rehg
Cambridge Research Lab
Compaq Computer Corporation

Wednesday, February 23, 2000
refreshments 4:05PM, talk begins 4:15PM
TCseq201, Lecture Hall B


Video is the primary archival source for human movement, with examples ranging from sports coverage of Olympic events to dance routines in Hollywood movies. If the human figure could be tracked reliably in unconstrained monocular video, much of this archive could be unlocked for analysis. Significant technical challenges exist, however, due to the complexity of human movement, the variability of human appearance, and the loss of 3-D information.

My talk will describe some recent progress in modeling and estimating figure motion from monocular video. Two important themes are the separation of 2-D (registration) and 3-D (reconstruction) effects in kinematic modeling, and the role of learning in dynamic modeling. In particular, I will describe a framework for learning switching linear dynamic system models from data and show its application to figure motion. I will describe some applications to video editing and computer animation currently underway at Compaq Research.

About the Speaker

Jim Rehg received his Ph.D. from Carnegie Mellon University in 1995. He subsequently joined the Cambridge Research Lab where he leads the vision-based human sensing project. His research interests include computer vision, novel user-interfaces, and parallel computing.
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Last modified: Tue Feb 22 12:28:13 PST 2000