Path detection in video surveillance

摘要

This paper addresses the problem of automatically extracting frequently used pedestrian pathways from video sequences of natural outdoor scenes. Path models are learnt from the accumulation of trajectory data over long time periods, and can be used to augment the classification of subsequent track data. In particular, labelled paths provide an efficient means for compressing the trajectory data for logging purposes. In addition, the model can be used to compute a probabilistic prediction of the pedestrian's location many time steps ahead, and to aid the recognition of unusual behaviour identified as atypical object motion.