Graph matching based on spectral embedding with missing value

• Published in: Pattern recognition Vol. 45; no. 10; pp. 3768 - 3779
• Main Authors: Tang, Jin, Jiang, Bo, Zheng, Aihua, Luo, Bin
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.10.2012; Elsevier
• Subjects: Algorithms; Applied sciences; Association graph; Co-embedding; Dot product representation of graph; Exact sciences and technology; Graph matching; Graphs; Information theory; Information, signal and communications theory; Matching; Missing data; Missing value; Pattern recognition; Point pattern matching; Representations; Signal processing; Spectra; Telecommunications and information theory; Association graph; Co-embedding; Missing value; Point pattern matching; Dot product representation of graph; Performance evaluation; Pattern recognition; Algorithm; Missing data; Algorithm performance; Information processing; Data fusion; Pattern matching; Graph matching
• ISSN: 0031-3203; 1873-5142
• DOI: 10.1016/j.patcog.2012.03.016

This paper proposes an efficient algorithm for inexact graph matching based on spectral embedding with missing value. We commence by building an association graph model based on initial matching algorithm. Then, by dot product representation of graph with missing value, a new embedding method (co-embedding), where the correspondences between unmatched nodes are treated as missing data in an association graph, is presented. At last, a new graph matching algorithm which alternates between the co-embedding and point pattern matching is proposed. Convictive experimental results on both synthetic and real-world data demonstrate the effectiveness of the proposed graph matching algorithm. ► Inexact graph matching based on spectral embedding with missing value. ► Co-embedding with missing data in association graph. ► Experimental results show the effectiveness of our method.