An Affine SIFT Matching Algorithm Based on Local Patch Shape Estimation

In this paper we present an affine SIFT matching method to achieve reliable correspondence points in stereo matching with large viewpoint changes. We extended the affine invariant of the conventional SIFT approach by estimating the shape of the local patch around the interest point. Since we can obtain the scale information by SIFT detector, a second moment matrix (SMM) descriptor was employed to describe the shape. Furthermore, by comparing the shapes of the potential matches, we can normalize the template of SIFT descriptor and obtain the initial affine transformation. At last, we applied the iterative based method to achieve a fine registration with the estimated initial transformation parameters. The experiment results show that the proposed method is more robust to viewpoint changes and the accuracy of registration is better than feature based methods.