Simultaneous tracking of pedestrians and vehicles by the spatio-temporal Markov random field model

To achieve efficient traffic flow, it is important to base control of traffic signals on observation of pedestrian flow as well as vehicle flow. In consideration of safety, it is also important to analyze behavioral relationship between pedestrians and vehicles, which can be conductive to accidents at intersections. Toward the goals of efficiency and safety, we developed a precise tracking algorithm based on the spatio-temporal MRF model which is able to track both pedestrians and vehicles simultaneously against occlusions in the images. Based on experimental results, this model was able to simultaneously track pedestrians and vehicles against occlusion even in very cluttered situations. Consequently, the S-T MRF model was proven to be effective for traffic monitoring at urban intersections.