Iterative Point Matching via multi-direction geometric serialization and reliable correspondence selection | |
Qian, Deheng1; Chen, Tianshi2; Qiao, Hong1,3; Tang, Tang1 | |
刊名 | NEUROCOMPUTING
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2016-07-12 | |
卷号 | 197页码:171-183 |
关键词 | Point matching Order relation Projection Graph matching Dynamic programming |
ISSN号 | 0925-2312 |
DOI | 10.1016/j.neucom.2016.02.066 |
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. |
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 |
语种 | 英语 |
出版者 | ELSEVIER SCIENCE BV |
WOS记录号 | WOS:000376694700015 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/8407] ![]() |
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. |
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