Computationally efficient graph matching via energy vector extraction

被引：2

作者：

Amato, Ariel ^{[1
,2
]}

Al Haj, Murad ^{[1
,2
]}

Llados, Josep ^{[1
,2
]}

Gonzalez, Jordi ^{[3
]}

机构：

[1] Univ Autonoma Barcelona, Comp Vis Ctr, Cerdanyola Del Valles 08193, Spain

[2] Univ Autonoma Barcelona, Dept Informat, Cerdanyola Del Valles 08193, Spain

[3] UPC, CSIC, Inst Robot & Informat Ind, Barcelona 08028, Spain

来源：

PROGRESS IN PATTERN RECOGNITION | 2007年

关键词：

D O I：

10.1007/978-1-84628-945-3_5

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a method for graph matching based on domain knowledge by quantifying representative graph features. Our method searches and extracts the most relevant cues in different graphs. Once these cues are extracted and quantified, a new energy function is used to match the different graphs based on the obtained features values. This approach has been successfully applied for deformable template matching. As a result, the matching error and the computational cost are reduced by efficiently selecting and grouping representative features.

引用

页码：47 / +

页数：2

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