Outlier robust point correspondence based on GNCCP
Yang, Xu; Qiao, Hong; Liu, Zhi-Yong; Zhi-Yong Liu
AbstractGraph matching is a fundamental problem in pattern recognition and computer vision. In this paper we introduce a novel graph matching algorithm to find the specified number of best vertex assignments between two labeled weighted graphs. The problem is first explicitly formulated as the minimization of a quadratic objective function and then solved by an optimization algorithm based on the recently proposed graduated nonconvexity and concavity procedure (GNCCP). Simulations on both synthetic data and real world images witness the effectiveness of the proposed method. (C) 2015 Elsevier B.V. All rights reserved
KeywordFeature Correspondence Graph Matching Gnccp
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence
WOS IDWOS:000351015900002
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Cited Times:9[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorZhi-Yong Liu
AffiliationChinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yang, Xu,Qiao, Hong,Liu, Zhi-Yong,et al. Outlier robust point correspondence based on GNCCP[J]. PATTERN RECOGNITION LETTERS,2015(55):8-14.
APA Yang, Xu,Qiao, Hong,Liu, Zhi-Yong,&Zhi-Yong Liu.(2015).Outlier robust point correspondence based on GNCCP.PATTERN RECOGNITION LETTERS(55),8-14.
MLA Yang, Xu,et al."Outlier robust point correspondence based on GNCCP".PATTERN RECOGNITION LETTERS .55(2015):8-14.
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