Knowledge Commons of Institute of Automation,CAS
IRA plus plus : Distributed Incremental Rotation Averaging | |
Gao, Xiang1; Zhu, Lingjie2; Cui, Hainan3,4,5; Xie, Zexiao1; Shen, Shuhan3,4,5 | |
发表期刊 | IEEE Transactions on Circuits and Systems for Video Technology |
ISSN | 1051-8215 |
2022 | |
卷号 | 32期号:7页码:4885-4892 |
摘要 | By observing that the recently presented Incremental Rotation Averaging (IRA) suffers from drifting and efficiency problems in large-scale situations, it is upgraded in this work to possess stronger scalability in both accuracy and efficiency based on the thought of divide and conquer. This upgraded version is termed as IRA++. Specifically, the original Epipolar-geometry Graph (EG) is clustered into several sub-graphs and inner-rotation averaging is distributedly performed in each of them with IRA at first. Then, the relative rotation between each pair of inner-sub-EG coordinate systems is distributedly estimated by a voting-based single rotation averaging method. Subsequently, IRA-based inter-rotation averaging is performed to obtain the absolute rotation of each inner-sub-EG coordinate system. And finally, the absolute rotations of all the cameras in the original EG are globally aligned and optimized to get the final rotation averaging result. Comprehensive evaluations on the 1DSfM, Campus, and San Francisco datasets demonstrate the advantages of our proposed IRA++ over IRA and several other state-of-the-art rotation averaging methods in both efficiency and accuracy, especially the accuracy in noise-polluted and efficiency in large-scale situations. |
关键词 | Structure from motion Rotation averaging Divide and conquer |
DOI | 10.1109/TCSVT.2021.3118883 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Science Foundation of China[62003319] ; National Science Foundation of China[61873265] ; National Science Foundation of China[62076026] ; Shandong Provincial Natural Science Foundation[ZR2020QF075] ; China Postdoctoral Science Foundation[2020M682239] |
项目资助者 | National Science Foundation of China ; Shandong Provincial Natural Science Foundation ; China Postdoctoral Science Foundation |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Electrical & Electronic |
WOS记录号 | WOS:000819817700063 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
是否为代表性论文 | 是 |
七大方向——子方向分类 | 三维视觉 |
国重实验室规划方向分类 | 环境多维感知 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/49153 |
专题 | 多模态人工智能系统全国重点实验室_机器人视觉 中科院工业视觉智能装备工程实验室 |
通讯作者 | Shen, Shuhan |
作者单位 | 1.Ocean Univ China, Coll Engn, Qingdao 266100, Peoples R China 2.Alibaba AI Labs, Hangzhou 311121, Peoples R China 3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 5.CASIA SenseTime Res Grp, Beijing 100190, Peoples R China |
通讯作者单位 | 模式识别国家重点实验室; 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Gao, Xiang,Zhu, Lingjie,Cui, Hainan,et al. IRA plus plus : Distributed Incremental Rotation Averaging[J]. IEEE Transactions on Circuits and Systems for Video Technology,2022,32(7):4885-4892. |
APA | Gao, Xiang,Zhu, Lingjie,Cui, Hainan,Xie, Zexiao,&Shen, Shuhan.(2022).IRA plus plus : Distributed Incremental Rotation Averaging.IEEE Transactions on Circuits and Systems for Video Technology,32(7),4885-4892. |
MLA | Gao, Xiang,et al."IRA plus plus : Distributed Incremental Rotation Averaging".IEEE Transactions on Circuits and Systems for Video Technology 32.7(2022):4885-4892. |
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