Probabilistic matching of lines for their homography
A probabilistic matching of lines, which form a homography in two images, is formulated in the framework of the forward stepwise regression. A membership matrix represents the likelihood of line correspondences to the homography. The correspondence measure is borrowed from the forward stepwise regression so that the squared error of the homography and the number of correspondences are balanced simultaneously. An alternating scheme for optimizing the membership and homography is provided. The experimental results on synthetic and real images validate the proposed method.