View-graph construction framework for robust and efficient structure-from-motion

doi:10.1016/j.patcog.2020.107712

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

	View-graph construction framework for robust and efficient structure-from-motion
	Cui, Hainan 2; Shi, Tianxin 2; Zhang, Jun 1; Xu, Pengfei 1; Meng, Yiping 1; Shen, Shuhan 2,3
刊名	PATTERN RECOGNITION
	2021-06-01
卷号	114 页码:9
关键词	Structure-from-motion View-graph construction Epipolar geometry computation
ISSN号	0031-3203
DOI	10.1016/j.patcog.2020.107712
通讯作者	Cui, Hainan(hncui@nlpr.ia.ac.cn)
英文摘要	A view-graph is vital for both the accuracy and robustness of structure-from-motion (SfM). Conventional matrix decomposition techniques treat all edges of view-graph equally; hence, many edge outliers are produced in matching pairs with fewer feature matches. To address this problem, we propose an incremental framework for view-graph construction, where the robustness of matched pairs that have a larger number of feature matches is propagated to their connected images. Given pairwise feature matches, a verified maximum spanning tree (VMST) is first constructed; for each edge in the VMST, we perform a local reconstruction and register its visible cameras. Based on the local reconstruction, pairwise relative geometries are computed and some new epipolar edges are produced. In this way, these newly computed edges inherit the robustness and accuracy of VMST, and by embedding them into VMST, our view-graph is constructed. We feed our view-graph into a standard SfM pipeline and compare this newly formed system with many of state-of-the-art SfM methods. The experimental results demonstrate that our view graph provides a better foundation for conventional SfM systems, and enables them to reconstruct both general and ambiguous images. ? 2020 Elsevier Ltd. All rights reserved.
资助项目	National Natural Science Foundation of China[61703397] ; National Natural Science Foundation of China[U1805264] ; Didi GAIA Foundation
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	ELSEVIER SCI LTD
WOS记录号	WOS:000625557800001
资助机构	National Natural Science Foundation of China ; Didi GAIA Foundation
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/43347]
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	Cui, Hainan
作者单位	1.Didi Chuxing, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Automat, NLPR, Beijing, Peoples R China 3.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Cui, Hainan,Shi, Tianxin,Zhang, Jun,et al. View-graph construction framework for robust and efficient structure-from-motion[J]. PATTERN RECOGNITION,2021,114:9.
APA	Cui, Hainan,Shi, Tianxin,Zhang, Jun,Xu, Pengfei,Meng, Yiping,&Shen, Shuhan.(2021).View-graph construction framework for robust and efficient structure-from-motion.PATTERN RECOGNITION,114,9.
MLA	Cui, Hainan,et al."View-graph construction framework for robust and efficient structure-from-motion".PATTERN RECOGNITION 114(2021):9.