This paper introduces a framework to track 3D human movement using Gaussian process dynamic model (GPDM) and particle filter. The framework combines the particle filter and discri...
This paper demonstrates a new visual motion estimation technique that is able to recover high degree-of-freedom articulated human body configurations in complex video sequences. W...
We propose a variational multigrid method for fast 3D interpretation of image sequences, in which a dense depth map and 3D motion are directly recovered from spatiotemporal change...
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
In the domain of computer vision, there exists a very wide application for the research of human motion capture. This paper proposes a new approach to do motion capture in video. ...