Obstacle Detection from Uncalibrated Cameras

In this paper, we propose a new approach for obstacle detection based on the analysis of images taken by uncalibrated stereo rig. This system can be divided in to two main stages. The first one deals with computing the fundamental matrix from the matching between points of interest in order to compute a dense disparity map. Whereas the second one presents a very simple and faster method for obstacle detection, by using the segmentation image. Indeed, the combination of the segmented image and the disparity map are going to permit us to extract the vertical 3D segments that will indicate us the presence of obstacles in the scene. This approach allows us to detect several numbers of obstacles of varied shapes and sizes. This obstacle detection stage can be viewed as the first stage of a free space estimator which can be implemented in a mobile robot.