A unified formulation of a class of graph matching techniques

被引:0
作者
Zhu, Yuan [1 ,2 ]
Zhou, Jiufeng [3 ]
Yan, Hong [4 ]
机构
[1] China Univ Geosci, Sch Automat, Wuhan, Peoples R China
[2] Hubei Key Lab Adv Control & Intelligent Automat C, Wuhan, Hubei, Peoples R China
[3] Amazoncom Inc, Seattle, WA 98109 USA
[4] City Univ Hong Kong, Dept Elect & Engn, Hong Kong, Peoples R China
关键词
Graph matching; Relaxation labeling; Spectral graph theory; Tensor theory; COMPATIBILITY COEFFICIENTS; RELAXATION;
D O I
10.1016/j.patcog.2019.06.008
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 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. (C) 2019 Elsevier Ltd. All rights reserved.
引用
收藏
页码:223 / 234
页数:12
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