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
Link To Document :
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