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...
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
We present a Bayesian framework for learning higherorder transition models in video surveillance networks. Such higher-order models describe object movement between cameras in the...
—A user’s focus of attention plays an important role in human–computer interaction applications, such as a ubiquitous computing environment and intelligent space, where the u...
We present a novel probabilistic framework for rigid tracking and segmentation of shapes observed from multiple cameras. Most existing methods have focused on solving each of thes...