Vehicle detection and tracking with low-angle cameras

Abstract

Vision-based vehicle detection is a critical task for traffic monitoring in modern Intelligent Traffic Systems (ITS). Due to the low-angle nature of most traffic surveillance cameras installed in the real world, vehicle detection in such case has to deal with one fundamental challenge — occlusion, which renders most traditional vehicle detection methods ineffective. In this paper, instead of detecting the vehicle as a whole, we propose a vehicle detection algorithm based on windshield model matching. By detecting windshield directly, the algorithm achieves robustness to occlusion. Together with camera calibration and vehicle tracking, the system is able to provide reliable traffic state estimation. Experiments on real traffic videos demonstrate the better performance of our system compared to the state-of-the-art algorithm.