Behavior understandings based on state transition of postures and locations at railway station

Public safety and security in the railway station is significant. This paper describes a development of a framework composed of pedestrian detection and tracking, analysis based on both interactions between postures and location contexts and interactions between multiple pedestrians for behavior understanding in the railway station. In the railway station, a lot of pedestrians are passing through, and occlusions occur frequently. The occlusions have an influence on the accuracy of trajectories, and postures recognitions. Our framework uses ST-MRF model to reduce the influence of the occlusions. We also develop a method correcting the foot position of the occluded pedestrians to improve the accuracy of trajectories. In addition, the posture of occluded pedestrians can not be seen in single camera situation. For the problem, we develop a pedestrian matching technique between two cameras to detect the postures of the occluded pedestrians by selecting the camera without occlusions adaptively. By our framework, we improve the precision of behavior understandings in the railway station including occluded conditions.