Efficient and robust large-scale structure-from-motion via track selection and camera prioritization
文献类型：期刊论文
| 作者 | Cui, Hainan1 ; Shen, Shuhan1,2; Gao, Wei1,2; Liu, Hongmin4; Wang, Zhiheng3
|
| 刊名 | ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
 |
| 出版日期 | 2019-10-01 |
| 卷号 | 156页码:202-214 |
| ISSN号 | 0924-2716 |
| 关键词 | Image-based modeling Structure-from-motion Track selection Rotation averaging Camera prioritization |
| DOI | 10.1016/j.isprsjprs.2019.08.005 |
| 通讯作者 | Cui, Hainan(hncui@nlpr.ia.ac.cn) ; Liu, Hongmin(hmliu_82@163.com) |
| 英文摘要 | Incremental Structure-from-Motion (SfM) techniques have exhibited superior practicability in many recent studies; however, efficiency and robustness remain key challenges for these techniques. In this work, we propose a new incremental SfM method that overcomes these problems in a united framework that contains two iteration loops. The inner loop is a track selection loop, where a well-conditioned subset of the feature tracks is iteratively selected to accelerate the time-consuming bundle adjustment. The outer loop is a camera registration loop, where the a priori camera rotations are estimated via rotation averaging on multiple orthogonal maximum spanning trees (OMSTs) of the view-graph and used as weak supervision for the registration. The calibrated camera poses that agree with the a priori camera rotations are preferentially registered, and after all the consistent cameras have been calibrated, the remaining cameras are incrementally registered. The results of extensive experiments demonstrate that our system can reconstruct both general and ambiguous image datasets, and our system outperforms many state-of-the-art SfM systems in terms of efficiency and robustness. |
| 资助项目 | National Key R&D Program of China[2016YFB0502002] ; Natural Science Foundation of China[61703397] ; Natural Science Foundation of China[61632003] ; Henan Science and Technology Innovation Outstanding Youth Program[184100510009] ; Henan University Scientific and Technological Innovation Team Support Program[19IRTSTHN012] |
| WOS研究方向 | Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:000487765800015 |
| 资助机构 | National Key R&D Program of China ; Natural Science Foundation of China ; Henan Science and Technology Innovation Outstanding Youth Program ; Henan University Scientific and Technological Innovation Team Support Program |
| 源URL | [http://ir.ia.ac.cn/handle/173211/26076]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_机器人视觉团队 |
| 通讯作者 | Cui, Hainan; Liu, Hongmin |
| 作者单位 | 1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Henan Polytech Univ, Jiaozuo 454000, Henan, Peoples R China 4.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cui, Hainan,Shen, Shuhan,Gao, Wei,et al. Efficient and robust large-scale structure-from-motion via track selection and camera prioritization[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2019,156:202-214. |
| APA | Cui, Hainan,Shen, Shuhan,Gao, Wei,Liu, Hongmin,&Wang, Zhiheng.(2019).Efficient and robust large-scale structure-from-motion via track selection and camera prioritization.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,156,202-214. |
| MLA | Cui, Hainan,et al."Efficient and robust large-scale structure-from-motion via track selection and camera prioritization".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 156(2019):202-214. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。