This paper presents a novel approach for model-based realtime tracking of highly articulated structures such as humans. This approach is based on an algorithm which efficiently pr...
The recent emergence of multi-core processors enables a new trend in the usage of computers. Computer vision applications, which require heavy computation and lots of bandwidth, u...
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 ...
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 the application of a kernel particle filter for 3D body tracking in a video stream acquired from a single uncalibrated camera. Using intensity-based and color...