Mono-vision based moving object detection in complex traffic scenes

Abstract

Vision-based dynamic objects motion segmentation can significantly help to understand the context around vehicles, and furthermore improve road traffic safety and autonomous navigation. Therefore, moving object detection in complex traffic scene becomes an inevitable issue for ADAS and autonomous vehicles. In this paper, we propose an approach that combines different multiple views geometry constraints to achieve moving objects detection using only a monocular camera. Self-assigned weights are estimated online moderating the contribution of each constraint. Such a combination enhances the detection performance in degenerated situations. According to the experimental results, the proposed approach provides accurate moving objects detections in dynamic traffic scenarios with large camera motions.