IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2 Bayesian Pixel Classification for Human Tracking Breckenridge, Colorado January 05-January 07 ISBN: 0-7695-2271-8
We present a monocular object tracker, able to detect and track multiple objects in non-controlled environments. Bayesian per-pixel classification is used to build a tracking framework that segments an image into foreground and background objects, based on observations of object appearances and motions. Gaussian mixtures are used to build the color appearance models. The system adapts to changing lighting conditions, handles occlusions, and works in real-time.
Citation:
Daniel Roth, Petr Doubek, Luc Van Gool, "Bayesian Pixel Classification for Human Tracking," wacv-motion, vol. 2, pp.78-83, IEEE Workshop on Motion and Video Computing (WACV/MOTION'05) - Volume 2, 2005 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||