Research On The Method Of Moving Pedestrian Detection And Tracking

The technique of moving pedestrian detection and tracking in urban traffic scenes is one of the key techniques for Intelligent Vehicle Navigation System. And the research on it will do great contribution to the development of Intelligent Vehicles and the safety of city traffic.To ensure the safety and smoothness of the pedestrian flow, this dissertation is focused on the study of moving pedestrian detection and tracking in urban traffic scenes by using the data from a fixed CCD camera. Firstly, this dissertation describes the process of extract the pedestrians from the complex scenes and how to track the pedestrians. Then, the method of pedestrians' motion analysis is discussed.The self-adaptive background subtraction method and the motion area segmentation method were adopted here to segment the moving pedestrians. On the basis of background difference image, the dynamic multi-thresholds method and the morphologic operation were used to extract the pedestrians. So the noises brought by the difference images were restrained. And also, the rupture in the images including pedestrians can be joined together. Then, the pedestrians can be extracted exactly.During the process of matching, the template for pedestrian matching and recognizing in image sequence was presented by fusing several characters of targets. A new method based on gray model GM(1,1) was proposed to predict the motion of pedestrians. So the detecting area is reduced greatly. The center of the tracking window was elected as the tracking point representing the pedestrian. The influences of the pedestrians' self motion were restrained, so the robustness of the tracking method was improved. The experiment results of tracking are satisfying. What's more, the method of extraction the parameters of pedestrian traffic was discussed. This is necessary to comprehend the pedestrians' motion. It is the theoretical basis to solve the existing problems in navigation system of Intelligent Vehicles and the monitor and control system of traffic.Experimental results of two real urban traffic scenes showed that this method could detect and track pedestrians robustly. The results indicate that this method is effective.