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.