DocumentCode :
2543761
Title :
The Role of Graph Topology for Graph Matching
Author :
Lu, Jianfeng ; Yang, Jingyu
Author_Institution :
Sch. of Comput. Sci., Nanjing Univ. of Sci. & Technol., Nanjing, China
fYear :
2009
fDate :
4-6 Nov. 2009
Firstpage :
1
Lastpage :
5
Abstract :
Graph matching plays a key role in structural pattern recognition. However, for concrete application, an appropriate feature graph topology must be chosen. In this paper, this issue is investigated by comparing the performance of four different graph topologies with respect to four types of feature graphs and two algebraically graph matching methods: least squares method (LSM) and eigenspectral methods. Results clearly demonstrate that standard delaunay triangulation topology is not as successful as other nearest neighbor models for graph matching.
Keywords :
eigenvalues and eigenfunctions; graph theory; least squares approximations; mesh generation; pattern matching; spectral analysis; Delaunay triangulation topology; eigenspectral method; feature graph topology; graph matching; least square method; structural pattern recognition; Application software; Computer science; Computer vision; Concrete; Least squares methods; Nearest neighbor searches; Object recognition; Pattern matching; Pattern recognition; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2009. CCPR 2009. Chinese Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4199-0
Type :
conf
DOI :
10.1109/CCPR.2009.5344140
Filename :
5344140
Link To Document :
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