Adaptive Graph Matching
Yang, Xu1; Liu, Zhi-Yong1,2,3
Source PublicationIEEE TRANSACTIONS ON CYBERNETICS
2018-05-01
Volume48Issue:5Pages:1432-1445
SubtypeArticle
AbstractEstablishing correspondence between point sets lays the foundation for many computer vision and pattern recognition tasks. It can be well defined and solved by graph matching. However, outliers may significantly deteriorate its performance, especially when outliers exist in both point sets and meanwhile the inlier number is unknown. In this paper, we propose an adaptive graph matching algorithm to tackle this problem. Specifically, a novel formulation is proposed to make the graph matching model adaptively determine the number of inliers and match them, then by relaxing the discrete domain to its convex hull the discrete optimization problem is relaxed to be a continuous one, and finally a graduated projection scheme is used to get a discrete matching solution. Consequently, the proposed algorithm could realize inlier number estimation, inlier selection, and inlier matching in one optimization framework. Experiments on both synthetic data and real world images witness the effectiveness of the proposed algorithm.
Other Abstract
KeywordGraduated Projection Graph Matching Point Correspondence Regularization Method
WOS HeadingsScience & Technology ; Technology
DOI10.1109/TCYB.2017.2697968
WOS KeywordALGORITHM ; GNCCP
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61503383 ; National Key Research and Development Plan of China(2016YFC0300801) ; 61633009 ; U1613213 ; 61375005 ; 61303174)
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000429247700008
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15484
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yang, Xu,Liu, Zhi-Yong. Adaptive Graph Matching[J]. IEEE TRANSACTIONS ON CYBERNETICS,2018,48(5):1432-1445.
APA Yang, Xu,&Liu, Zhi-Yong.(2018).Adaptive Graph Matching.IEEE TRANSACTIONS ON CYBERNETICS,48(5),1432-1445.
MLA Yang, Xu,et al."Adaptive Graph Matching".IEEE TRANSACTIONS ON CYBERNETICS 48.5(2018):1432-1445.
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