Direct Obstacle Detection and Motion from Spatio-Temporal Derivatives

Autonomous vehicles need a means of detecting obstructions on its path, to avoid collision. In this paper, a novel approach to obstacle detection is presented. A camera moves on a visible ground plane with the optical axis parallel to the ground. Camera motion parameters are linearly related to rst order spatio-temporal derivatives of the taken image sequence; image ow is not needed. Motion is robustly estimated using RANSAC. An error measure for each image point corresponds to the likelihood of an obstacle in that point.