A real-time traffic monitoring system by stochastic model combination

In order to model and to control traffics efficiently, precise traffic monitoring is very important. For those purposes, we developed a real-time system which is able to detect various events such as accidents, congestion, stalled vehicles, fallen objects, etc., and also able to record images before and after the events. This system is based on dedicated tracking algorithm called the spatio-temporal MRF model, which is very robust against occlusions and variations in illumination. Combined with stochastic reasoning, our system was able to classify above events against cluttered situations in traffic images. Finally, by operating the system by a roadside for six months, our system proven to be very successful.