Tracking people with probabilistic appearance models
Andrew Senior · 2002
This paper describes a real-time computer vision system for tracking people in monocular video sequences. The system tracks people as they move through the camera’s field of view, by a combination of background subtraction and the learning of appearance models. The appearance models allow objects to be tracked through occlusions using a probabilistic pixel reclassification algorithm. The system is evaluated on the three test sequences of the PETS 2002 dataset, for which tracking results and processing time requirements are presented.