Tracking groups of people

A computer vision system for tracking multiple people in relatively unconst rained environments is described. Tracking is performed at three levels of abstraction: regions, people, and groups. A novel, adaptive background subt raction method that combines color and gradient information is used to cope with shadows and unreliable color cues. People are tracked through mutual occlusions as they form groups and separate from one another. Strong use is made of color information to disambiguate occlusion and to provide qualita tive estimates of depth ordering and position during occlusion. Simple inte ractions with objects can also be detected. The system is tested using both indoor and outdoor sequences. It is robust and should provide a useful mec hanism for bootstrapping and reinitialization of tracking using more specif ic but less robust human models. (C) 2000 Academic Press.