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...
We explore a novel motion feature as the appropriate basis for classifying or describing a number of fine motor human activities.Ourapproach not only estimates motion directions a...
Jiang Gao, Alexander G. Hauptmann, Howard D. Wactl...
We explore an approach to 3D people tracking with learned motion models and deterministic optimization. The tracking problem is formulated as the minimization of a differentiable ...
Temporal difference (TD) learning has been used to learn strong evaluation functions in a variety of two-player games. TD-gammon illustrated how the combination of game tree search...