Graph matching based on fast normalized cut and multiplicative update mapping

doi:10.1016/j.patcog.2021.108228

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Graph matching based on fast normalized cut and multiplicative update mapping
	Yang, Jing 1,2; Yang, Xu2,4,5 ; Zhou, Zhang-Bing 1,3; Liu, Zhi-Yong2,4,5
发表期刊	PATTERN RECOGNITION
ISSN	0031-3203
	2022-02-01
卷号	122 页码:11
通讯作者	Yang, Xu(xu.yang@ia.ac.cn) ; Zhou, Zhang-Bing(zbzhou@cugb.edu.cn)
摘要	Point correspondence is a fundamental problem in pattern recognition and computer vision, which can be tackled by graph matching. Since graph matching is basically an NP-complete problem, some approximate methods are proposed to solve it. Continuous relaxation offers an effective approximate method for graph matching problem. However, the discrete constraint is not taken into consideration in the optimization step. In this paper, a fast normalized cut based graph matching method is proposed, where the discrete constraint is introduced into the optimization step. Specifically, first a semidefinite positive affinity matrix based form objective function is constructed by introducing a regularization term which is related to the discrete constraint. Then the fast normalized cut algorithm is utilized to find the continuous solution. Last, the discrete solution of graph matching is obtained by a multiplicative update algorithm. Experiments on both synthetic points and real-world images validate the effectiveness of the proposed method by comparing it with the state-of-the-art methods. 0 2021 Elsevier Ltd. All rights reserved.
关键词	Graph matching Fast normalized cut Discrete constraint Multiplicative update
DOI	10.1016/j.patcog.2021.108228
关键词[WOS]	ALGORITHM ; OPTIMIZATION
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China[2020AAA0108902] ; National Natural Science Foundation (NSFC) of China[61973301] ; National Natural Science Foundation (NSFC) of China[61972020] ; National Natural Science Foundation (NSFC) of China[61633009] ; Beijing Science and Technology Plan Project[Z201100008320029] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32050100]
项目资助者	National Key R&D Program of China ; National Natural Science Foundation (NSFC) of China ; Beijing Science and Technology Plan Project ; Strategic Priority Research Program of Chinese Academy of Science
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000697675100005
出版者	ELSEVIER SCI LTD
七大方向——子方向分类	模式识别基础
引用统计	被引频次：3[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/46044
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Yang, Xu; Zhou, Zhang-Bing
作者单位	1.China Univ Geosci Beijing, Sch Informat Engn, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.TELECOM SudParis, Comp Sci Dept, F-91011 Evry, France 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai 200031, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Yang, Jing,Yang, Xu,Zhou, Zhang-Bing,et al. Graph matching based on fast normalized cut and multiplicative update mapping[J]. PATTERN RECOGNITION,2022,122:11.
APA	Yang, Jing,Yang, Xu,Zhou, Zhang-Bing,&Liu, Zhi-Yong.(2022).Graph matching based on fast normalized cut and multiplicative update mapping.PATTERN RECOGNITION,122,11.
MLA	Yang, Jing,et al."Graph matching based on fast normalized cut and multiplicative update mapping".PATTERN RECOGNITION 122(2022):11.