We investigate the spectral approaches to the problem of point pattern matching, and present a spectral feature descriptors based on partial least square (PLS). Given keypoints of two images, we define the position similarity matrices respectively, and extract the spectral features from the matrices by PLS, which indicate geometric distribution and inner relationships of the keypoints. Then the keypoints matching is done by bipartite graph matching. The experiments on both synthetic and real-world data corroborate the robustness and invariance of the algorithm.
© 2009 Chinese Optics Letters
Weidong Yan, Zheng Tian, Lulu Pan, and Mingtao Ding, "Spectral feature matching based on partial least squares," Chin. Opt. Lett. 7, 201-205 (2009)