中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Partial correspondence based on subgraph matching

文献类型:期刊论文

作者Yang, Xu; Qiao, Hong; Liu, Zhi-Yong; Zhi-Yong Liu
刊名NEUROCOMPUTING
出版日期2013-12-25
期号122页码:193-197
关键词Feature correspondence Structural model Subgraph matching GNCGCP
通讯作者Zhi-Yong Liu
英文摘要Exploiting both appearance similarity and geometric consistency is popular in addressing the feature correspondence problem. However, when there exist outliers the performance generally deteriorates greatly. In this paper, we propose a novel partial correspondence method to tackle the problem with outliers. Specifically, a novel pairwise term together with a neighborhood system is proposed, which, together with the other two pairwise terms and a unary term, formulates the correspondence to be solved as a subgraph matching problem. The problem is then approximated by the recently proposed Graduated Non-Convexity and Graduated Concavity Procedure (GNCGCP). The proposed algorithm obtains a state-of-the-art accuracy in the existence of outliers while keeping O(N-3) computational complexity and O(N-2) storage complexity. Simulations on both the synthetic and real-world images witness the effectiveness of the proposed method. (C) 2013 Elsevier B.V. All rights reserved.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Artificial Intelligence
研究领域[WOS]Computer Science
关键词[WOS]GRAPH ; RECOGNITION
收录类别SCI
语种英语
WOS记录号WOS:000325590200021
源URL[http://ir.ia.ac.cn/handle/173211/3040]  
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Zhi-Yong Liu
作者单位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,Qiao, Hong,Liu, Zhi-Yong,et al. Partial correspondence based on subgraph matching[J]. NEUROCOMPUTING,2013(122):193-197.
APA Yang, Xu,Qiao, Hong,Liu, Zhi-Yong,&Zhi-Yong Liu.(2013).Partial correspondence based on subgraph matching.NEUROCOMPUTING(122),193-197.
MLA Yang, Xu,et al."Partial correspondence based on subgraph matching".NEUROCOMPUTING .122(2013):193-197.

入库方式: OAI收割

来源:自动化研究所

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