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
Link To Document :
بازگشت