• DocumentCode
    419781
  • Title

    Graph matching using spectral embedding and alignment

  • Author

    Bai, Xiao ; Yu, Hang ; Hancock, Edwin R.

  • Author_Institution
    Dept. of Comput. Sci., York Univ., UK
  • Volume
    3
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    398
  • Abstract
    This paper describes how graph-spectral methods can be used to transform the node correspondence problem into one of point-set alignment. We commence by using the ISOMAP algorithm to embed the nodes of a graph in a low-dimensional Euclidean space. With the nodes in the graph transformed to points in a metric space, we can recast the problem of graph matching into that of aligning the points. Here, we use a variant of the Scott and Longuet-Higgins algorithm to find point correspondences. We experiment with the resulting algorithm on a number of real-world problems.
  • Keywords
    graph theory; pattern matching; singular value decomposition; ISOMAP algorithm; Longuet-Higgins algorithm; Scott algorithm; graph matching; graph spectral method; low dimensional Euclidean space; node correspondence problem; point set alignment method; singular value decomposition; spectral embedding method; Computer science; Data structures; Eigenvalues and eigenfunctions; Extraterrestrial measurements; Iterative algorithms; Mathematics; Matrix decomposition; Pattern matching; Robustness; Singular value decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2128-2
  • Type

    conf

  • DOI
    10.1109/ICPR.2004.1334550
  • Filename
    1334550