Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection
Qian, Deheng1; Chen, Tianshi2; Qiao, Hong1,3; Tang, Tang1
发表期刊NEUROCOMPUTING
2016-07-12
卷号197页码:171-183
文章类型Article
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
WOS标题词Science & Technology ; Technology
DOI10.1016/j.neucom.2016.02.066
关键词[WOS]REGISTRATION ; RECOGNITION ; ALGORITHM
收录类别SCI
语种英语
项目资助者National Science Foundation of China(61210009 ; Strategic Priority Research Program of the CAS(XDB02080003) ; Beijing Natural Science Foundation(2141100002014002) ; 61503383)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000376694700015
引用统计
被引频次:1[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/173211/11611
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
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
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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.
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