Incremental Rotation Averaging

doi:10.1007/s11263-020-01427-7

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 机器人视觉团队

	Incremental Rotation Averaging
	Gao, Xiang 2; Zhu, Lingjie 3,4; Xie, Zexiao 2; Liu, Hongmin 1; Shen, Shuhan 3,4
刊名	INTERNATIONAL JOURNAL OF COMPUTER VISION
	2021-01-16
页码	15
关键词	Rotation averaging Incremental estimation Accuracy and robustness
ISSN号	0920-5691
DOI	10.1007/s11263-020-01427-7
通讯作者	Liu, Hongmin(hmliu_82@163.com) ; Shen, Shuhan(shshen@nlpr.ia.ac.cn)
英文摘要	In this paper, we present a simple yet effective rotation averaging pipeline, termed Incremental Rotation Averaging (IRA), which is inspired by the well-developed incremental Structure from Motion (SfM) techniques. Unlike the traditional rotation averaging methods which estimate all the absolute rotations simultaneously and focus on designing either robust loss function or outlier filtering strategy, here the absolute rotations are estimated in an incremental way. Similar to the incremental SfM, our IRA is robust to relative rotation outliers and could achieve accurate rotation averaging results. In addition, we propose several key techniques, such as initial triplet and Next-Best-View selection, Weighted Local/Global Optimization, and Re-Rotation Averaging, to push the rotation averaging results one step further. Ablation studies and comparison experiments on the 1DSfM, Campus, and San Francisco datasets demonstrate the effectiveness of our IRA and its advantages over the state-of-the-art rotation averaging methods in accuracy and robustness.
资助项目	National Key Research and Development Program of China[2020YFB1313002] ; National Science Foundation of China[62003319] ; National Science Foundation of China[62076026] ; National Science Foundation of China[61873265] ; Shandong Provincial Natural Science Foundation[ZR2020QF075] ; China Postdoctoral Science Foundation[2020M682239] ; National Laboratory of Pattern Recognition[202000010]
WOS研究方向	Computer Science
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000608098500001
资助机构	National Key Research and Development Program of China ; National Science Foundation of China ; Shandong Provincial Natural Science Foundation ; China Postdoctoral Science Foundation ; National Laboratory of Pattern Recognition
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/42593]
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	Liu, Hongmin; Shen, Shuhan
作者单位	1.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China 2.Ocean Univ China, Coll Engn, Qingdao 266100, 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
推荐引用方式 GB/T 7714	Gao, Xiang,Zhu, Lingjie,Xie, Zexiao,et al. Incremental Rotation Averaging[J]. INTERNATIONAL JOURNAL OF COMPUTER VISION,2021:15.
APA	Gao, Xiang,Zhu, Lingjie,Xie, Zexiao,Liu, Hongmin,&Shen, Shuhan.(2021).Incremental Rotation Averaging.INTERNATIONAL JOURNAL OF COMPUTER VISION,15.
MLA	Gao, Xiang,et al."Incremental Rotation Averaging".INTERNATIONAL JOURNAL OF COMPUTER VISION (2021):15.