Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game
文献类型：期刊论文
| 作者 | Zai, Dawei2; Li, Jonathan2,3; Guo, Yulan1,4; Cheng, Ming2; Huang, Pengdi2; Cao, Xiaofei2; Wang, Cheng2 |
| 刊名 | ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
 |
| 出版日期 | 2017-12-01 |
| 卷号 | 134页码:15-29 |
| 关键词 | Terrestrial laser scanning (TLS) Registration Covariance matrix descriptor 3D representation Game theory |
| ISSN号 | 0924-2716 |
| DOI | 10.1016/j.isprsjprs.2017.10.001 |
| 英文摘要 | It is challenging to automatically register TLS point clouds with noise, outliers and varying overlap. In this paper, we propose a new method for pairwise registration of TLS point clouds. We first generate covariance matrix descriptors with an adaptive neighborhood size from point clouds to find candidate correspondences, we then construct a non-cooperative game to isolate mutual compatible correspondences, which are considered as true positives. The method was tested on three models acquired by two different TLS systems. Experimental results demonstrate that our proposed adaptive covariance (ACOV) descriptor is invariant to rigid transformation and robust to noise and varying resolutions. The average registration errors achieved on three models are 0.46 cm, 0.32 cm and 1.73 cm, respectively. The computational times cost on these models are about 288 s, 184 s and 903 s, respectively. Besides, our registration framework using ACOV descriptors and a game theoretic method is superior to the state-of-the-art methods in terms of both registration error and computational time. The experiment on a large outdoor scene further demonstrates the feasibility and effectiveness of our proposed pairwise registration framework. (C) 2017 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved. |
| 资助项目 | National Natural Science Foundation of China[41471379] ; National Natural Science Foundation of China[61471371] ; National Natural Science Foundation of China[61602499] ; Fujian Collaborative Innovation Center for Big Data Applications in Governments ; National Postdoctoral Program for Innovative Talents[BX201600172] |
| WOS研究方向 | Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000418220800002 |
| 出版者 | ELSEVIER SCIENCE BV |
| 源URL | [http://119.78.100.204/handle/2XEOYT63/5563]  |
| 专题 | 中国科学院计算技术研究所期刊论文_英文 |
| 通讯作者 | Li, Jonathan |
| 作者单位 | 1.Natl Univ Def Technol, Coll Elect Sci & Engn, Changsha, Hunan, Peoples R China 2.Xiamen Univ, Sch Informat Sci & Engn, Fujian Key Lab Sensing & Comp Smart City, Xiamen, Peoples R China 3.Univ Waterloo, Dept Geog & Environm Management, Waterloo, ON, Canada 4.Chinese Acad Sci, Inst Comp Technol, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zai, Dawei,Li, Jonathan,Guo, Yulan,et al. Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2017,134:15-29. |
| APA | Zai, Dawei.,Li, Jonathan.,Guo, Yulan.,Cheng, Ming.,Huang, Pengdi.,...&Wang, Cheng.(2017).Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,134,15-29. |
| MLA | Zai, Dawei,et al."Pairwise registration of TLS point clouds using covariance descriptors and a non-cooperative game".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 134(2017):15-29. |
入库方式： OAI收割
来源：计算技术研究所
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