We pose the problem of 3D human tracking as one of inference in a graphical model. Unlike traditional kinematic tree representations, our model of the body is a collection of loos...
Leonid Sigal, Sidharth Bhatia, Stefan Roth, Michae...
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 ...
In a wide range of business areas dealing with text data streams, including CRM, knowledge management, and Web monitoring services, it is an important issue to discover topic tren...
Tracking heart motion plays an essential role in the diagnosis of cardiovascular diseases. This study investigates overlap priors for variational tracking of the Left Ventricle (LV...
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...