Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection

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

	Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection
	Qian, Deheng1 ; Chen, Tianshi 2; Qiao, Hong1,3 ; Tang, Tang 1
刊名	NEUROCOMPUTING
	2016-07-12
卷号	197 页码:171-183
关键词	Point matching Order relation Projection Graph matching Dynamic programming
英文摘要	Point matching aims at finding the optimal matching between two sets of feature points. It is widely accomplished by graph matching methods which match nodes of graphs via minimizing energy functions. However, the obtained correspondences between feature points vary in their matching qualities. In this paper, we propose an innovative matching algorithm which iteratively improves the matching found by such methods. The intuition is that we may improve a given matching by identifying "reliable" correspondences, and re-matching the rest feature points without reliable correspondences. A critical issue here is how to identify reliable correspondences, which is addressed with two novel mechanisms, Multi-direction Geometric Serialization (MGS) and Reliable Correspondence Selection (RCS). Specifically, MGS provides representations of the spatial relations among feature points. With these representations, RCS determines whether a correspondence is reliable according to a reliability metric. By recursively applying MGS and RCS, and re-matching feature points without reliable correspondences, a new (intermediate) matching can be obtained. In this manner, our algorithm starts with a matching provided by a classical method, iteratively generates a number of intermediate matchings, and chooses the best one as the final matching. Experiments demonstrate that our algorithm significantly improves the matching precisions of classical graph matching methods. (C) 2016 Published by Elsevier B.V.
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]	REGISTRATION ; RECOGNITION ; ALGORITHM
收录类别	SCI
语种	英语
WOS记录号	WOS:000376694700015
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/11611]
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
作者单位	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Comp, State Key Lab Comp Architecture, Beijing 100190, Peoples R China 3.Chinese Acad Sci, CEBSIT, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Qian, Deheng,Chen, Tianshi,Qiao, Hong,et al. Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection[J]. NEUROCOMPUTING,2016,197:171-183.
APA	Qian, Deheng,Chen, Tianshi,Qiao, Hong,&Tang, Tang.(2016).Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection.NEUROCOMPUTING,197,171-183.
MLA	Qian, Deheng,et al."Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection".NEUROCOMPUTING 197(2016):171-183.