Detection of independently moving objects through stereo vision and ego-motion extraction

Vision-based autonomous vehicles must face numerous challenges in order to be effective in practical areas. Among these lies the detection and localization of independent-moving objects, so as to track or avoid them. In this paper a method that address this particular issue is presented. Information from stereo and motion is used to extract the ego-motion of the vehicle. Known defects of this estimation are exploited to detect independent-moving obstacles. This method allows an early and reliable detection, even for objects partially occluded. Besides, it highlights the errors in the disparity map, which can be used, in future works, to correct depth-estimation, through motion-estimation.