Change detection and update of 3D sparse map by merging geometry and appearance

doi:10.1016/j.jag.2023.103306

CORC > 自动化研究所 > 中国科学院自动化研究所 > 中科院工业视觉智能装备工程实验室

	Change detection and update of 3D sparse map by merging geometry and appearance
	Ma, Wenjuan 2; Song, Zhuo 3; He, Ying 3; Shen, Shuhan 1,3
刊名	INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
	2023-05-01
卷号	119 页码:9
关键词	Change detection 3D map update 3D sparse map
ISSN号	1569-8432
DOI	10.1016/j.jag.2023.103306
通讯作者	Shen, Shuhan(shshen@nlpr.ia.ac.cn)
英文摘要	Large-scale 3D sparse maps generated by Structure-from-Motion (SfM) from images play an important role in many applications, including visual localization, augmented reality, etc. In these scenarios, the timeliness of the map i.e., detecting changes in the map and performing partial updates, is crucial. To solve this problem, in this paper we propose a novel method for 3D sparse map change detection and updating, to maintain the SfM map continuously over time. The core idea of this paper is to simultaneously detect the appearance and geometry changes of 3D map points, so as to find regions with significant changes, and update these regions locally without changing most of the stable map regions. In the proposed method, a local 3D map containing changing areas is computed from newly captured images by SfM and aligned to the old map according to the locations of new images in the new local map and their registration in the old map. Next, the overlapping map is partitioned into regular grids and the appearance uncertainty and geometry uncertainty are measured on each grid cell individually. Then the grid cells are labeled as changed or unchanged using Markov Random Field optimization by taking both cell uncertainty and consistency of adjacent cells into consideration. Finally, the visible old images of the point cloud in the changed cells are replaced with the corresponding visible new images, and the old map is updated by a local Bundle Adjustment. Experimental results on 3D maps reconstructed by aerial and ground images demonstrate the effectiveness and robustness of the proposed method.
资助项目	National Natural Science Foundation of China[62273345] ; Fundamental Research Funds of Zhejiang Sci-Tech University, China[2021Q028]
WOS关键词	ENERGY MINIMIZATION
WOS研究方向	Remote Sensing
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000982807500001
资助机构	National Natural Science Foundation of China ; Fundamental Research Funds of Zhejiang Sci-Tech University, China
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/53221]
专题	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.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China 2.Zhejiang Sci Tech Univ, Sch Comp Sci & Technol, Hangzhou, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Ma, Wenjuan,Song, Zhuo,He, Ying,et al. Change detection and update of 3D sparse map by merging geometry and appearance[J]. INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,2023,119:9.
APA	Ma, Wenjuan,Song, Zhuo,He, Ying,&Shen, Shuhan.(2023).Change detection and update of 3D sparse map by merging geometry and appearance.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,119,9.
MLA	Ma, Wenjuan,et al."Change detection and update of 3D sparse map by merging geometry and appearance".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 119(2023):9.