U-V-Disparity based Obstacle Detection with 3D Camera and Steerable Filter

This paper presents an obstacle detection system which is robust to non-flat road surface and interference of illumination. A 3D camera is used to generate depth information without the need of camera calibration. The depth map is then transformed into U-V-disparity domain, where obstacles and ground surface are projected as lines. Hough Transform is employed to extract line features; it has been modified to fit the characteristic of the U-V-disparity in order to boost the speed and accuracy. In addition, steerable filters are applied to the u-v histogram before Hough Transform for noise reduction. By categorising extracted lines according to their position and posture, road surface and on-road obstacles can be detected. Finally, results obtained using both U and V disparity maps are combined to eliminate road side surface and post processing. Experiments show that the proposed system is Able to detect obstacles accurately under various environments.