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Sub-hypergraph matching based on adjacency tensor

文献类型：期刊论文

作者Yang, Jing1,2; Yang, Xu2; Zhou, Zhang-Bing1,3; Liu, Zhi-Yong2,4,5
刊名COMPUTER VISION AND IMAGE UNDERSTANDING
出版日期2019-06-01
卷号183页码:1-10
关键词Hypergraph matching Subgraph matching High order structure Adjacency tensor
ISSN号1077-3142
DOI10.1016/j.cviu.2019.03.003
通讯作者Yang, Xu() ; Zhou, Zhang-Bing(zhangbing.zhou@gmail.com)
英文摘要Point correspondence problem is an important problem in pattern recognition and computer vision, which can be solved by graph matching. Recently, high order graph matching methods have attracted much attention due to their robustness to geometric transformations. Since high order graph matching usually suffers from high complexity, we previously proposed an adjacency tensor based algorithm, which effectively reduced the complexity of high order graph matching, especially high storage complexity. However, this method can only be applied to equal sized hypergraphs, and it cannot be directly extended to hypergraphs with outliers which are common in real world tasks. Aiming at this problem, in this paper we propose a third order subgraph matching method by extending our previous method to deal with partial point correspondence problem with outliers. Specifically, first a novel objective function focusing on the outlier problem is proposed, by encoding the attributes in a hypergraph with an adjacency tensor, and representing vertex assignments with a partial permutation matrix. Then the objective function is transformed and relaxed to a tractable matrix form and solved by a gradient based optimization algorithm. Consequently, the proposed algorithm can not only tackle the outlier vertices in the hypergraphs, but also involve the same low computational and storage complexities with our previous algorithm. Both synthetic data and real image comparisons with the state-of-the-art methods validate the effectiveness of the proposed method.
资助项目National Key R&D Program of China[2016YFC0300801] ; National Key R&D Program of China[2017YFB1300202] ; National Natural Science Foundation (NSFC) of China[61503383] ; National Natural Science Foundation (NSFC) of China[61633009] ; National Natural Science Foundation (NSFC) of China[U1613213] ; National Natural Science Foundation (NSFC) of China[61773047] ; National Natural Science Foundation (NSFC) of China[61772479] ; National Natural Science Foundation (NSFC) of China[61662021]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000469164200001
出版者ACADEMIC PRESS INC ELSEVIER SCIENCE
资助机构National Key R&D Program of China ; National Natural Science Foundation (NSFC) of China
源URL[http://ir.ia.ac.cn/handle/173211/24390]  
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
推荐引用方式
GB/T 7714		 Yang, Jing,Yang, Xu,Zhou, Zhang-Bing,et al. Sub-hypergraph matching based on adjacency tensor[J]. COMPUTER VISION AND IMAGE UNDERSTANDING,2019,183:1-10.
APA Yang, Jing,Yang, Xu,Zhou, Zhang-Bing,&Liu, Zhi-Yong.(2019).Sub-hypergraph matching based on adjacency tensor.COMPUTER VISION AND IMAGE UNDERSTANDING,183,1-10.
MLA Yang, Jing,et al."Sub-hypergraph matching based on adjacency tensor".COMPUTER VISION AND IMAGE UNDERSTANDING 183(2019):1-10.

入库方式： OAI收割

来源：自动化研究所

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