Abstract. This paper addresses the problem of probabilistically modeling 3D human motion for synthesis and tracking. Given the high dimensional nature of human motion, learning an ...
This paper describes a framework for learning probabilistic models of objects and scenes and for exploiting these models for tracking complex, deformable, or articulated objects i...
This paper presents a novel algorithm for estimating complex human motion from 3D video. We base our algorithm on a model-based approach which uses a complete surface mesh of a 3D...
Estimating geometric structure from uncalibrated images accurately enough for high quality rendering is difficult. We present a method where only coarse geometric structure is trac...
Understanding the human gait is an important objective towards improving elderly mobility. In turn, gait analyses largely depend on kinematic and dynamic measurements. While the m...
Samantha Ng, Adel H. Fakih, Adam Fourney, Pascal P...