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Eigenvector Sign Correction for Spectral Correspondence Matching

  • Muhammad Haseeb
  • Edwin R. Hancock
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)

Abstract

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.

Keywords

Eigenvector Direction Correction Symmetric Polynomials Correspondence Matching Point Pattern Matching 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Muhammad Haseeb
    • 1
    • 2
  • Edwin R. Hancock
    • 1
  1. 1.Department of Computer ScienceUniversity of YorkUK
  2. 2.Department of Computer ScienceUniversity of PeshawarPakistan

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