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IRA plus plus : Distributed Incremental Rotation Averaging

文献类型：期刊论文

作者Gao, Xiang5; Zhu, Lingjie4; Cui, Hainan1,2,3; Xie, Zexiao5; Shen, Shuhan1,2,3
刊名IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
出版日期2022-07-01
卷号32期号:7页码:4885-4892
ISSN号1051-8215
关键词Barium Optimization Cameras Rotation measurement Pipelines Estimation Scalability Structure from motion rotation averaging divide and conquer
DOI10.1109/TCSVT.2021.3118883
通讯作者Shen, Shuhan(shshen@nlpr.ia.ac.cn)
英文摘要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.
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]
WOS研究方向Engineering
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000819817700063
资助机构National Science Foundation of China ; Shandong Provincial Natural Science Foundation ; China Postdoctoral Science Foundation
源URL[http://ir.ia.ac.cn/handle/173211/49152]  
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
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.CASIA SenseTime Res Grp, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
4.Alibaba AI Labs, Hangzhou 311121, Peoples R China
5.Ocean Univ China, Coll Engn, Qingdao 266100, Peoples R China
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.

入库方式： OAI收割

来源：自动化研究所

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