Change detection and update of 3D sparse map by merging geometry and appearance
文献类型：期刊论文
| 作者 | Ma, Wenjuan1; Song, Zhuo3; He, Ying3 ; Shen, Shuhan2,3
|
| 刊名 | INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
 |
| 出版日期 | 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. |
| WOS关键词 | ENERGY MINIMIZATION |
| 资助项目 | National Natural Science Foundation of China[62273345] ; Fundamental Research Funds of Zhejiang Sci-Tech University, China[2021Q028] |
| WOS研究方向 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000982807500001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Natural Science Foundation of China ; Fundamental Research Funds of Zhejiang Sci-Tech University, China |
| 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.Zhejiang Sci Tech Univ, Sch Comp Sci & Technol, Hangzhou, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, 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. |
入库方式： OAI收割
来源：自动化研究所
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