Vision-Based Vehicle and Pedestrian Tracking of Intersection Videos
Mohammad Shokrolah Shirazi, Brendan Morris · International Journal of Artificial Intelligence Tools · 2016
Vehicle and pedestrian tracking is a key component for vision-based safety analysis which can use motion and appearance cues of road users. Since appearance-based detectors generate false alarms and provide lower speed, motion-based detectors are preferred but they work poorly when pedestrians or vehicles stop due to traffic signals. In this paper, a tracking system is proposed to track waiting and moving road users by fusion of motion and appearance cues at detection level. The enhanced optical flow tracker handles the partial occlusion problem, and it cooperates with the detection module to provide long-term tracks of vehicles and pedestrians. The system evaluation shows 13% and 43% improvement in tracking of vehicles and pedestrians respectively, and finally heat-maps show benefits of using the proposed system through the visual depiction of intersection usage.