Abstract. In this paper we propose a probabilistic framework that models shape variations and infers dense and detailed 3D shapes from a single silhouette. We model two types of sh...
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
This paper describes a method for tracking human body motion from multiple views in real-time. The method extracts silhouettes in each view using background subtraction, and then ...
Jason P. Luck, Christian Debrunner, William Hoff, ...
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...
In this paper we propose a multilinear model of human pose and body shape which is estimated from a database of registered 3D body scans in different poses. The model is generated...
Nils Hasler, Hanno Ackermann, Bodo Rosenhahn, Thor...