2013 IEEE Conference on Computer Vision and Pattern Recognition (2007)
Minneapolis, MN, USA
June 17, 2007 to June 22, 2007
David J. Fleet , Department of Computer Science, University of Toronto, firstname.lastname@example.org
Marcus A. Brubaker , Department of Computer Science, University of Toronto, email@example.com
Aaron Hertzmann , Department of Computer Science, University of Toronto, firstname.lastname@example.org
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.
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