A Continuation Method for Graph Matching Based Feature Correspondence

doi:10.1109/TPAMI.2019.2903483

CORC > 自动化研究所 > 中国科学院自动化研究所 > 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

	A Continuation Method for Graph Matching Based Feature Correspondence
	Yang, Xu 3; Liu, Zhi-Yong 1,2,3; Qiao, Hong 1,2,3
刊名	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
	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
DOI	10.1109/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.
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关键词	OPTIMIZATION
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	IEEE COMPUTER SOC
WOS记录号	WOS:000545415400001
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
内容类型	期刊论文
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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, 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.