Eigenvector Sign Correction for Spectral Correspondence Matching
In this paper we describe a method to correct the sign of eigenvectors of the proximity matrix for the problem of correspondence matching. The signs of the eigenvectors of a proximity matrix are not unique and play an important role in computing the correspondences between a set of feature points. We use the coefficients of the elementary symmetric polynomials to make the direction of the eigenvectors of the two proximity matrices consistent with each other for the problem correspondence matching. We compare our method to other methods presented in the literature. The empirical results show that using the coefficients of the elementary symmetric polynomials for eigenvectors sign correction is a better choice to solve the problem.
KeywordsEigenvector Direction Correction Symmetric Polynomials Correspondence Matching Point Pattern Matching
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