Vision-based vehicle queue analysis at junctions

This paper presents a tracking method for vision-based queue analysis at junctions including queue length and waiting time estimation of vehicles. The tracking method works based on improving the optical flow method to track small and low quality vehicles with overlong waiting time. The improvement process is performed to keep track of overlong stopped vehicles with high level of robustness against occlusion by crossing pedestrians. The results of experiments are presented by estimating queue length, waiting time distribution and number of waiting vehicles for the highly cluttered video of a Las Vegas junction. The accuracy of the system is evaluated by comparing the queue analysis results with the ground truth.