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2013 IEEE Conference on Computer Vision and Pattern Recognition (2007)
Minneapolis, MN, USA
June 17, 2007 to June 22, 2007
ISBN: 1-4244-1179-3
pp: 1-8
David J. Fleet , Department of Computer Science, University of Toronto, fleet@cs.toronto.edu
Marcus A. Brubaker , Department of Computer Science, University of Toronto, mbrubake@cs.toronto.edu
Aaron Hertzmann , Department of Computer Science, University of Toronto, hertzman@cs.toronto.edu
ABSTRACT
We introduce a physics-based model for 3D person tracking. Based on a biomechanical characterization of lower-body dynamics, the model captures important physical properties of bipedal locomotion such as balance and ground contact, generalizes naturally to variations in style due to changes in speed, step-length, and mass, and avoids common problems such as footskate that arise with existing trackers. The model dynamics comprises a two degree-of-freedom representation of human locomotion with inelastic ground contact. A stochastic controller generates impulsive forces during the toe-off stage of walking and spring-like forces between the legs. A higher-dimensional kinematic observation model is then conditioned on the underlying dynamics. We use the model for tracking walking people from video, including examples with turning, occlusion, and varying gait.
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CITATION
David J. Fleet, Marcus A. Brubaker, Aaron Hertzmann, "Physics-Based Person Tracking Using Simplified Lower-Body Dynamics", 2013 IEEE Conference on Computer Vision and Pattern Recognition, vol. 00, no. , pp. 1-8, 2007, doi:10.1109/CVPR.2007.383342
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