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

doi:10.1016/j.neucom.2016.02.066

	Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection
	Qian, Deheng 1; Chen, Tianshi 2; Qiao, Hong 1,3; Tang, Tang 1
	2016-07-12
发表期刊	NEUROCOMPUTING
ISSN	0925-2312
卷号	197 页码:171-183
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.
关键词	Point matching Order relation Projection Graph matching Dynamic programming
DOI	10.1016/j.neucom.2016.02.066
收录类别	SCI
语种	英语
资助项目	National Science Foundation of China[61210009] ; National Science Foundation of China[61503383] ; Strategic Priority Research Program of the CAS[XDB02080003] ; Beijing Natural Science Foundation[2141100002014002]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000376694700015
出版者	ELSEVIER SCIENCE BV
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/8408
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Qiao, Hong
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.