An original approach for automatic plane extraction by omnidirectional vision

Whereas some methods for plane extraction have been proposed, this problem still remains an open issue due to the complexity of the task. This paper especially focuses on the extraction of points lying on a plane (such as the ground and buildings walls) in sequences acquired by a central omnidirectional camera. Our approach is based on the epipolar constraint for planar scenes (i.e. homography) on a pair of omnidirectional images to detect some interest points belonging to a plane. Our main contribution is the introduction of a new method, called "2-point algorithm for homography", that imposes some constraints on the homography using vanishing point (VP) information. Compared to the widely used DLT (4-point) algorithm, experiments on real data demonstrated that the proposed "2-point algorithm for homography" is more robust to noise and false matching, even when the plane to extract is not dominant in the image. Finally, we show that our system provides key clues for ground segmentation by GrabCut.