• DocumentCode
    838485
  • Title

    Correspondence matching with modal clusters

  • Author

    Carcassoni, Marco ; Hancock, Edwin R.

  • Author_Institution
    Dept. of Comput. Sci., York Univ., UK
  • Volume
    25
  • Issue
    12
  • fYear
    2003
  • Firstpage
    1609
  • Lastpage
    1615
  • Abstract
    The modal correspondence method of Shapiro and Brady aims to match point-sets by comparing the eigenvectors of a pairwise point proximity matrix. Although elegant by means of its matrix representation, the method is notoriously susceptible to differences in the relational structure of the point-sets under consideration. In this paper, we demonstrate how the method can be rendered robust to structural differences by adopting a hierarchical approach. To do this, we place the modal matching problem in a probabilistic setting in which the correspondences between pairwise clusters can be used to constrain the individual point correspondences. We demonstrate the utility of the method on a number of synthetic and real-world point-pattern matching problems.
  • Keywords
    eigenvalues and eigenfunctions; pattern matching; eigenvectors; hierarchical approach; matching; modal clusters; modal correspondence; pairwise clusters; pairwise point proximity matrix; probabilistic setting; real world point pattern matching; Computer vision; Graph theory; Laplace equations; Matrix decomposition; Object recognition; Pattern matching; Polynomials; Robustness; Spectral analysis; Statistics;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2003.1251153
  • Filename
    1251153