Physical simulation for probabilistic motion tracking

Human motion tracking is an important problem in computer vision. Most prior approaches have concentrated on efficient inference algorithms and prior motion models; however, few can explicitly account for physical plausibility of recovered motion. The primary purpose of this work is to enforce physical plausibility in the tracking of a single articulated human subject. Towards this end, we propose a fullbody 3D physical simulation-based prior that explicitly incorporates motion control and dynamics into the Bayesian filtering framework. We consider the human's motion to be generated by a "control loop". In this control loop, Newtonian physics approximates the rigid-body motion dynamics of the human and the environment through the application and integration of forces. Collisions generate interaction forces to prevent physically impossible hypotheses. This allows us to properly model human motion dynamics, ground contact and environment interactions. For efficient infere...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Marek Vondrak, Leonid Sigal, Odest Chadwicke Jenkins
• Keywords: Computer Vision, CVPR 2008, Human Motion Dynamics, Human Motion Tracking, Motion Control, Prior Motion Models, Rigid-body Motion Dynamics