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A Continuation Method for Graph Matching Based Feature Correspondence

文献类型：期刊论文

作者Yang, Xu2; Liu, Zhi-Yong1,2,3; Qiao, Hong1,2,3
刊名IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
出版日期2020-08-01
卷号42期号:8页码:1809-1822
关键词Feature correspondence graph matching continuous method continuation method combinatorial optimization
ISSN号0162-8828
DOI10.1109/TPAMI.2019.2903483
通讯作者Liu, Zhi-Yong(zhiyong.liu@ia.ac.cn)
英文摘要Feature correspondence lays the foundation for many computer vision and image processing tasks, which can be well formulated and solved by graph matching. Because of the high complexity, approximate methods are necessary for graph matching, and the continuous relaxation provides an efficient approximate scheme. But there are still many problems to be settled, such as the highly nonconvex objective function, the ignorance of the combinatorial nature of graph matching in the optimization process, and few attention to the outlier problem. Focusing on these problems, this paper introduces a continuation method directly targeting at the combinatorial optimization problem associated with graph matching. Specifically, first a regularization function incorporating the original objective function and the discrete constraints is proposed. Then a continuation method based on Gaussian smoothing is applied to it, in which the closed forms of relevant functions with respect to the outlier distribution are deduced. Experiments on both synthetic data and real world images validate the effectiveness of the proposed method.
WOS关键词OPTIMIZATION
资助项目National Natural Science Foundation (NSFC) of China[61633009] ; National Natural Science Foundation (NSFC) of China[61503383] ; National Natural Science Foundation (NSFC) of China[U1613213] ; National Natural Science Foundation (NSFC) of China[61627808] ; National Natural Science Foundation (NSFC) of China[91648205] ; National Natural Science Foundation (NSFC) of China[U1509212] ; National Key R\&D Program of China[2016YFC0300801] ; National Key R\&D Program of China[2017YFB1300202] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDB32000000]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000545415400001
出版者IEEE COMPUTER SOC
资助机构National Natural Science Foundation (NSFC) of China ; National Key R\&D Program of China ; Strategic Priority Research Program of Chinese Academy of Sciences
源URL[http://ir.ia.ac.cn/handle/173211/40004]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组
通讯作者Liu, Zhi-Yong
作者单位1.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Xu,Liu, Zhi-Yong,Qiao, Hong. A Continuation Method for Graph Matching Based Feature Correspondence[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2020,42(8):1809-1822.
APA Yang, Xu,Liu, Zhi-Yong,&Qiao, Hong.(2020).A Continuation Method for Graph Matching Based Feature Correspondence.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,42(8),1809-1822.
MLA Yang, Xu,et al."A Continuation Method for Graph Matching Based Feature Correspondence".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 42.8(2020):1809-1822.

入库方式： OAI收割

来源：自动化研究所

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