Multi-Attributed Graph Matching With Multi-Layer Graph Structure and Multi-Layer Random Walks

This paper addresses the multi-attributed graph matching problem, which considers multiple attributes jointly while preserving the characteristics of each attribute for graph matching. Since most of conventional graph matching algorithms integrate multiple attributes to construct a single unified attribute in an oversimplified manner, the information from multiple attributes is often not completely utilized. In order to solve this problem, we propose a novel multi-layer graph structure that can preserve the characteristics of each attribute in separated layers, and also propose a multi-attributed graph matching algorithm based on random walk centrality with the proposed multi-layer graph structure. We compare the proposed algorithm with other state-of-the-art graph matching algorithms based on a single-layer structure using synthetic and real data sets and demonstrate the superior performance of the proposed multi-layer graph structure and the multi-attributed graph matching algorithm.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2018-05
Language
English
Article Type
Article
Keywords

ASSIGNMENT

Citation

IEEE TRANSACTIONS ON IMAGE PROCESSING, v.27, no.5, pp.2314 - 2325

ISSN
1057-7149
DOI
10.1109/TIP.2017.2779264
URI
http://hdl.handle.net/10203/240910
Appears in Collection
ME-Journal Papers(저널논문)
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