ARCS: Accurate Rotation and Correspondence Search

doi:10.1109/CVPR52688.2022.01087

KMS > 信息科学与技术学院 > PI研究组 > Manolis Tsakiris组

	ARCS: Accurate Rotation and Correspondence Search
	Peng, Liangzu 1; Tsakiris, Manolis C.2 ; Vidal, Rene 1
	2022
会议录名称	PROCEEDINGS OF THE IEEE COMPUTER SOCIETY CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION
ISSN	1063-6919
卷号	2022-June
页码	11143-11153
发表状态	已发表
DOI	10.1109/CVPR52688.2022.01087
摘要	This paper is about the old Wahba problem in its more general form, which we call 'simultaneous rotation and correspondence search'. In this generalization we need to find a rotation that best aligns two partially overlapping 3D point sets, of sizes m and n respectively with m\geq n. We first propose a solver, ARCS, that i) assumes noiseless point sets in general position, ii) requires only 2 inliers, iii) uses O(m\log m) time and O(m) space, and iv) can successfully solve the problem even with, e.g., m, napprox 106 in about 0.1 seconds. We next robustify ARCS to noise, for which we approximately solve consensus maximization problems using ideas from robust subspace learning and interval stabbing. Thirdly, we refine the approximately found consensus set by a Riemannian subgradient descent approach over the space of unit quaternions, which we show converges globally to an \varepsilon-stationary point in O(\varepsilon^{-4}) iterations, or locally to the ground-truth at a linear rate in the absence of noise. We combine these algorithms into ARCS+, to simultaneously search for rotations and correspondences. Experiments show that ARCS+ achieves state-of-the-art performance on large-scale datasets with more than 106 points with a 104 time-speedup over alternative methods. https://github.com/liangzu/ARCS © 2022 IEEE.
会议名称	2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2022
出版地	10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA
会议地点	New Orleans, LA, United states
会议日期	June 19, 2022 - June 24, 2022
URL	查看原文
收录类别	EI ; CPCI-S
语种	英语
资助项目	NSF["1704458","1934979"]
WOS研究方向	Computer Science ; Imaging Science & Photographic Technology
WOS类目	Computer Science, Artificial Intelligence ; Imaging Science & Photographic Technology
WOS记录号	WOS:000870759104023
出版者	IEEE Computer Society
EI入藏号	20224613120320
原始文献类型	Conference article (CA)
来源库	IEEE
引用统计	正在获取...
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/251424
专题	信息科学与技术学院_PI研究组_Manolis Tsakiris组
通讯作者	Peng, Liangzu
作者单位	1.Johns Hopkins Univ, Baltimore, MD 21218 USA 2.ShanghaiTech Univ, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Peng, Liangzu,Tsakiris, Manolis C.,Vidal, Rene. ARCS: Accurate Rotation and Correspondence Search[C]. 10662 LOS VAQUEROS CIRCLE, PO BOX 3014, LOS ALAMITOS, CA 90720-1264 USA:IEEE Computer Society,2022:11143-11153.