Hidden Markov Models for Optical Flow Analysis in Crowds

This paper presents an event detector for emergencies in crowds. Assuming a single camera and a dense crowd we rely on optical flow instead of tracking statistics as a feature to extract information from the crowd video data. The optical flow features are encoded with hidden Markov models to allow for the detection of emergency or abnormal events in the crowd. In order to increase the detection sensitivity a local modelling approach is used. The results with simulated crowds show the effectiveness of the proposed approach on detecting abnormalities in dense crowds