Behavior understanding at railway station by postures and the pseud-trellis analysis of trajectories

Protection of critical transportation infrastructure such as railroad station is an important topic in these days. In this paper, we develop a new rule based approach to video surveillance system for detecting situations where pedestrians may be in peril, as well as suspicious action or interactions at railroad station. We analyze here two general types of pedestrian involved behaviors: (i) single pedestrian or no interaction, (ii) multiple pedestrian interactions. The behavior analysis is accomplished through the development of geometric and motion visual features for each pedestrian. The performance evaluation is carried out by using the video streams taken in the rail road stations. The results show that our algorithm is very simple and effective.