Robust vehicle detection for highway surveillance via rear-view monitoring
Akio Yoneyama, Chia‐Hung Yeh, C.‐C. Jay Kuo · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2003
Vision-based highway monitoring systems play an important role in transportation management and services owing to their powerful ability to extract a variety of information. Detection accuracy of vision-based systems is however sensitive to environmental factors such as lighting, shadow and weather conditions, and it is still a challenging problem to maintain detection robustness at all time. In this research, we present a novel method to enhance detection and tracking accuracy at the nighttime based on rear-view monitoring. In the meanwhile, a method is proposed to improve the background detection and extraction, which usually serves as the first step to moving object region detection. Finally, the effectiveness of the rear-view technique will be analyzed. We compare the tracking accuracy between the front-view and the rear-view techniques, and show that the proposed system can achieve higher detection accuracy at nighttime.