IMAGE TRACKING OF MOTORCYCLES AND VEHICLES ON URBAN ROADS AND ITS APPLICATION TO TRAFFIC MONITORING AND ENFORCEMENT

Image tracking has increasingly gained attention for use in vision-based traffic monitoring and surveillance applications. For many cities in Asia countries, it is desirable to detect multiple motorcycles as well as cars for urban traffic monitoring and enforcement. In this paper, a novel contour initialization and tracking algorithm is presented to track multiple motorcycles and vehicles at any position on the roadway. This method has the capability to detect moving vehicles of various sizes and to generate their initial contours for image tracking. The proposed method is not constrained by lane boundaries or vehicle size. To track vehicles on roadways, dynamic models are designed to predict the horizontal and vertical positions of vehicle contours. A Kalman filter is designed to update the prediction based on real-time image measurement. Practical experimental studies using video clips are presented to evaluate the performance of the proposed method. Traffic parameters such as traffic flow, vehicle speeds and traffic density are obtained with satisfactory accuracy.