Tracking articulated objects in image sequences remains a challenging problem, particularly in terms of the ability to localize the individual parts of an object given selfocclusi...
This paper describes a probabilistic multiple-hypothesis framework for tracking highly articulated objects. In this framework, the probability density of the tracker state is repr...
This paper proposes a novel tracking strategy that can robustly track a person or other object within a fixed environment using a pan, tilt, and zoom camera with the help of a pre...
Yiming Ye, John K. Tsotsos, Karen Bennet, Eric Har...
We have developed a computer vision system, including both facial feature extraction and recognition, that automatically discriminates among subtly different facial expressions. E...
James Jenn-Jier Lien, Takeo Kanade, Jeffrey F. Coh...
We present an approach for active segmentation based on integration of several cues. It serves as a framework for generation of object hypotheses of previously unseen objects in n...