A RKHS interpolator-based graph matching algorithm

被引：32

作者：

van Wyk, MA

Durrani, TS

van Wyk, BJ

机构：

[1] Rand Afrikaans Univ, Cybernet Lab, ZA-2006 Gauteng, South Africa

[2] Univ Strathclyde, Dept Elect & Elect Engn, Glasgow G1 1XW, Lanark, Scotland

来源：

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2002年 / 24卷 / 07期

关键词：

graph matching; attributed relational graphs; reproducing kernel Hilbert space theory; combinatorial optimization; neural networks; pattern matching; image processing;

D O I：

10.1109/TPAMI.2002.1017624

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present a novel algorithm for performing attributed graph matching. This algorithm is derived from a generalized framework for describing functionally expanded interpolators [1] which is based on the theory of reproducing kernel Hilbert spaces. The algorithm incorporates a general approach to a wide class of graph matching problems based on attributed graphs, allowing the structure of the graphs to be based on multiple sets of attributes. No assumption is made about the adjacency structure of the graphs to be matched.

引用

页码：988 / 995

页数：8

共 56 条

[1] A parallel algorithm for graph matching and its MasPar implementation [J].