Any type of obstacle detection in complex environments based on monocular vision
Zeyu Liu, Yu Chunxuan, Banggui Zheng · Chinese Control Conference · 2013
Obstacle detection has been one of the core issues of research in the field of intelligent vehicle visual navigation system, auto auxiliary driving,etc. This paper proposes a new detection method based on monocular vision, which is used to detect any type of obstacle in the rear of the vehicle when the vehicle in low-speed reversing. First, we use the Forward-Backward error(FB error) on the original image to select the easy tracking and reliable feature points. Second, using these feature points,the feature points belonging to ground are selected in top-view images converted from original images. Based on road assumption of plane, vehicle motion parameters can be estimated and we compensate for the rotation and translation of the vehicle using the estimated parameters. Finally, using the different movement between the obstacle and the road, we exclude noise points and extract obstacle region in the difference image based on motion compensation. The experimental results show that the method proposed in this paper can detect any type of obstacle.