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 ...
Representing articulated objects as a graphical model has gained much popularity in recent years, often the root node of the graph describes the global position and orientation of...
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...
Source separation techniques like independent component analysis and the more recent non-negative matrix factorization are gaining widespread use for the monaural separation of in...
This paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through Gaussian process latent variable model. The dime...