Occlusion Detection for Highway Traffic Analysis with Vision-based Surveillance Systems

The vision-based traffic monitoring system provides an attractive solution in extracting various traffic parameters such as the count, speed, flow and concentration from the processing of video data captured by a camera system. The detection accuracy is however affected by various environment factors such as shadow, occlusion, and lighting. Among these, the occurrence of occlusion is one of the major problems. In this work, a new scheme is proposed to detect the occlusion and determine the exact location of each vehicle. The proposed algorithm is based on the matching of images from multiple cameras. In the proposed scheme, we do not need edge detection, region segmentation, and camera calibration operations, which often suffer from the variation of environmental conditions. Experimental results are given to verify that the proposed technique is effective for vision-based highway surveillance systems.