We describe an approach to building brain-computer interfaces (BCI) based on graphical models for probabilistic inference and learning. We show how a dynamic Bayesian network (DBN...
We propose a Dynamic Bayesian Network (DBN) model for upper body tracking. We first construct a Bayesian Network (BN) to represent the human upper body structure and then incorpo...
This paper presents a sensor management scheme based on maximizing the expected R´enyi Information Divergence at each sample, applied to the problem of tracking multiple targets. ...
Christopher M. Kreucher, Keith Kastella, Alfred O....
An on-line algorithm for multi-object tracking is presented for monitoring a real-world scene from a single fixed camera. Potential objects are detected with adaptive backgrounds ...
We develop a theory for the temporal integration of visual motion motivated by psychophysical experiments. The theory proposes that input data are temporally grouped and used to p...
Alan L. Yuille, Pierre-Yves Burgi, Norberto M. Grz...