A unified formulation of a class of graph matching techniques

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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Author(s)

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Detail(s)

Original languageEnglish
Pages (from-to)223-234
Journal / PublicationPattern Recognition
Volume95
Online published20 Jun 2019
Publication statusPublished - Nov 2019

Abstract

In this paper, we show that graph matching methods based on relaxation labeling, spectral graph theory and tensor theory have the same mathematical form by employing power iteration technique. Besides, the differences among these methods are also fully discussed and can be proven that distinctions have little impact on the final matching result. Moreover, we propose a fast compatibility building procedure to accelerate the preprocessing speed which is considered to be the main time consuming part of graph matching. Finally, several experiments are conducted to verify our findings.

Research Area(s)

  • Graph matching, Relaxation labeling, Spectral graph theory, Tensor theory

Citation Format(s)

A unified formulation of a class of graph matching techniques. / Zhu, Yuan; Zhou, Jiufeng; Yan, Hong.

In: Pattern Recognition, Vol. 95, 11.2019, p. 223-234.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review