| Scale invariant image matching using triplewise constraint and weighted voting | |
Pang, Yanwei2; Shang, Mianyou2; Yuan, Yuan1 ; Pan, Jing3
| |
| 作者部门 | 光学影像分析与学习中心 |
| 2012-04-15 | |
| 发表期刊 | NEUROCOMPUTING
 |
| ISSN | 0925-2312 |
| 卷号 | 83页码:64-71 |
| 产权排序 | 2 |
| 摘要 | Due to limited computational resource, image matching on mobile phone places great demand on efficiency and scale invariant. Though spectral matching (SM) with pairwisely geometric constraints is widely used in matching, it is not efficient and scale invariant for applications in mobile phones. The main factor that limits its efficiency is that it requires to eign-decomposition of a large affinity matrix when the number of candidate correspondences is large. It lacks scale invariance because the pairwise constraints cannot hold when large scale variation occurs. In this paper, we attempt to tackle these problems. In the proposed method, each candidate correspondence is considered as a voter and a candidate as well. As a voter it gives voting scores to other candidates and also votes itself. Based on the voting scores, the optimal correspondences are computed by simple addition operations and ranking operations, which results in high efficiency. To make the proposed method scale invariant, we propose a novel triple-wisely geometric constraint formed by three potential correspondences with one being the candidate and the other two being voters. The three correspondences constitute a pair of triangles. The similarity of the two triangles is the core of the triple-wisely constraint, which is robust to scale variation. The information of triple-wise constraints are encoded in a 3-dimensional matrix from which the optimal correspondence can be obtained by simple summation and ranking operations. Experimental results on real-data show the effectiveness and efficiency of the proposed method. (C) 2012 Elsevier B.V. All rights reserved. |
| 文章类型 | Article |
| 关键词 | Image Matching Spectral Technique Correspondence Establishment Weighted Voting |
| 学科领域 | Computer Science |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1016/j.neucom.2011.11.008 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | RELEVANCE FEEDBACK ; SUBSPACE |
| 语种 | 英语 |
| WOS研究方向 | Computer Science |
| WOS类目 | Computer Science, Artificial Intelligence |
| WOS记录号 | WOS:000301613800008 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/20261 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China 2.Tianjin Univ, Sch Elect Informat Engn, Tianjin 300072, Peoples R China 3.Tianjin Univ Educ & Technol, Sch Elect Engn, Tianjin 300222, Peoples R China |
| 推荐引用方式 GB/T 7714 | Pang, Yanwei,Shang, Mianyou,Yuan, Yuan,et al. Scale invariant image matching using triplewise constraint and weighted voting[J]. NEUROCOMPUTING,2012,83:64-71. |
| APA | Pang, Yanwei,Shang, Mianyou,Yuan, Yuan,&Pan, Jing.(2012).Scale invariant image matching using triplewise constraint and weighted voting.NEUROCOMPUTING,83,64-71. |
| MLA | Pang, Yanwei,et al."Scale invariant image matching using triplewise constraint and weighted voting".NEUROCOMPUTING 83(2012):64-71. |
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| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Scale invariant imag（938KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY | 请求全文 | |
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