Wide baseline stereo matching based on SIFT and SVD
Zhang Lei · Journal of China University of Mining and Technology · 2011
A new feature matching algorithm based on the singular value decomposition(SVD) was proposed(SVD-NCC).In this algorithm,affine deformation was firstly corrected for matching window by using the scale and orientation information of SIFT features,and then the matching matrix was established base on the normalized cross correlation(NCC) and SVD,and the correspondences can be determined based on the matching matrix.In the practical strategy for this algorithm,the optimal SIFT features with good spatial distribution and large information content were first selected,then these SIFT features were matched by using the SVD-NCC algorithm,and then the fundamental matrix can be estimated by using these initial correspondences.Other SIFT features were matched by using epipolar geometric constraint.The test results for the wide baseline image sequences indicate that the proposed algorithm can increase the amount and accuracy of corresponding points.