A probabilistic method for tracking 3D articulated human figures in monocular image sequences is presented. Within a Bayesian framework, we define a generative model of image appea...
Hedvig Sidenbladh, Michael J. Black, David J. Flee...
A multiple-camera system for 3D pose reconstruction is presented. First, body parts of the user are detected. Each camera has a single-instruction multiple-data (SIMD) processor u...
We present a novel algorithm to jointly capture the motion and the dynamic shape of humans from multiple video streams without using optical markers. Instead of relying on kinemat...
Edilson de Aguiar, Christian Theobalt, Carsten Sto...
A likelihood formulation for human tracking is presented based upon matching feature statistics on the surface of an articulated 3D body model. A benefit of such a formulation ove...
Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...
The detection and tracking of three-dimensional human body models has progressed rapidly but successful approaches typically rely on accurate foreground silhouettes obtained using...