Minimal Case Relative Pose Computation Using Ray-Point-Ray Features
文献类型：期刊论文
| 作者 | Zhao, Ji4; Kneip, Laurent1; He, Yijia3 ; Ma, Jiayi2
|
| 刊名 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
 |
| 出版日期 | 2020-05-01 |
| 卷号 | 42期号:5页码:1176-1190 |
| 关键词 | Three-dimensional displays Transmission line matrix methods Cameras Pose estimation Feature extraction Geometry Computer vision Structure-from-motion visual odometry minimal relative pose automatic solver generation Grobner bases ray-point-ray structures |
| ISSN号 | 0162-8828 |
| DOI | 10.1109/TPAMI.2019.2892372 |
| 通讯作者 | Kneip, Laurent(lkneip@shanghaitech.edu.cn) |
| 英文摘要 | Corners are popular features for relative pose computation with 2D-2D point correspondences. Stable corners may be formed by two 3D rays sharing a common starting point. We call such elements ray-point-ray (RPR) structures. Besides a local invariant keypoint given by the lines' intersection, their reprojection also defines a corner orientation and an inscribed angle in the image plane. The present paper investigates such RPR features, and aims at answering the fundamental question of what additional constraints can be formed from correspondences between RPR features in two views. In particular, we show that knowing the value of the inscribed angle between the two 3D rays poses additional constraints on the relative orientation. Using the latter enables the solution of the relative pose problem with as few as 3 correspondences across the two images. We provide a detailed analysis of all minimal cases distinguishing between 90-degree RPR-structures and structures with an arbitrary, known inscribed angle. We furthermore investigate the special cases of a known directional correspondence and planar motion, the latter being solvable with only a single RPR correspondence. We complete the exposition by outlining an image processing technique for robust RPR-feature extraction. Our results suggest high practicality in man-made environments, where 90-degree RPR-structures naturally occur. |
| WOS关键词 | CLOSED-FORM SOLUTION ; EGOMOTION ESTIMATION ; MOTION |
| 资助项目 | National Natural Science Foundation of China[61773295] ; ShanghaiTech University |
| WOS研究方向 | Computer Science ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000523685800012 |
| 出版者 | IEEE COMPUTER SOC |
| 资助机构 | National Natural Science Foundation of China ; ShanghaiTech University |
| 源URL | [http://ir.ia.ac.cn/handle/173211/38767]  |
| 专题 | 自动化研究所_智能制造技术与系统研究中心_智能机器人团队 |
| 通讯作者 | Kneip, Laurent |
| 作者单位 | 1.ShanghaiTech Univ, Shanghai 201210, Peoples R China 2.Wuhan Univ, Elect Informat Sch, Wuhan 430072, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 4.TuSimple, Beijing 100020, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhao, Ji,Kneip, Laurent,He, Yijia,et al. Minimal Case Relative Pose Computation Using Ray-Point-Ray Features[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2020,42(5):1176-1190. |
| APA | Zhao, Ji,Kneip, Laurent,He, Yijia,&Ma, Jiayi.(2020).Minimal Case Relative Pose Computation Using Ray-Point-Ray Features.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,42(5),1176-1190. |
| MLA | Zhao, Ji,et al."Minimal Case Relative Pose Computation Using Ray-Point-Ray Features".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 42.5(2020):1176-1190. |
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。