Lightweight Structured Line Map Based Visual Localization
文献类型：期刊论文
| 作者 | Liu, Hongmin3,6; Cao, Chengyang3,6; Ye, Hanqiao1,2,4,7; Cui, Hainan1,2,4,7 ; Gao, Wei1,2,4,7; Wang, Xing5; Shen, Shuhan1,2,4,7
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| 刊名 | IEEE ROBOTICS AND AUTOMATION LETTERS
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| 出版日期 | 2024-06-01 |
| 卷号 | 9期号:6页码:5182-5189 |
| 关键词 | Visual localization line segments lightweight structured line map pose estimation |
| ISSN号 | 2377-3766 |
| DOI | 10.1109/LRA.2024.3387137 |
| 通讯作者 | Shen, Shuhan(shshen@nlpr.ia.ac.cn) |
| 英文摘要 | Visual localization, also known as camera pose estimation, is a crucial component of many applications, such as robotics, autonomous driving, and augmented reality. Traditional visual localization algorithms typically run on point cloud maps generated by algorithms such as Structure-from-Motion (SfM) or Simultaneous Localization and Mapping (SLAM). However, point features are sensitive to weak textures and illumination changes. In addition, the generated 3D point cloud maps often contain millions of points, which puts higher demands on device storage and computing resources. To address these challenges, we propose a visual localization algorithm based on lightweight structured line maps. Instead of extracting and matching point features in the images, we select line segments that represent structured scene information as image features. These line segments are then used to construct a lightweight line map containing rich structured scene information. The camera pose is then estimated through a series of steps that include line extraction, matching, initial pose estimation, and pose refinement. Experimental results on benchmark datasets show that our method achieves competitive localization accuracy compared to current state-of-the-art visual localization methods, while significantly reducing the memory footprint of the 3D map. |
| WOS关键词 | POSE ESTIMATION ; CORRESPONDENCES ; EFFICIENT |
| 资助项目 | National Natural Science Foundation of China |
| WOS研究方向 | Robotics |
| 语种 | 英语 |
| WOS记录号 | WOS:001209593700010 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.ia.ac.cn/handle/173211/57050]  |
| 专题 | 精密感知与控制研究中心_精密感知与控制 |
| 通讯作者 | Shen, Shuhan |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Univ Sci & Technol Beijing, Inst Artificial Intelligence, Beijing 100083, Peoples R China 4.CASIA SenseTime Res Grp, Beijing 100190, Peoples R China 5.Beijing Electromech Engn Res Inst, Sci & Technol Complex Syst Control & Intelligent A, Beijing 100074, Peoples R China 6.Univ Sci & Technol Beijing, Sch Intelligence Sci & Technol, Beijing 100083, Peoples R China 7.Luoyang Inst Robot & Intelligent Equipment, Luoyang 471003, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Hongmin,Cao, Chengyang,Ye, Hanqiao,et al. Lightweight Structured Line Map Based Visual Localization[J]. IEEE ROBOTICS AND AUTOMATION LETTERS,2024,9(6):5182-5189. |
| APA | Liu, Hongmin.,Cao, Chengyang.,Ye, Hanqiao.,Cui, Hainan.,Gao, Wei.,...&Shen, Shuhan.(2024).Lightweight Structured Line Map Based Visual Localization.IEEE ROBOTICS AND AUTOMATION LETTERS,9(6),5182-5189. |
| MLA | Liu, Hongmin,et al."Lightweight Structured Line Map Based Visual Localization".IEEE ROBOTICS AND AUTOMATION LETTERS 9.6(2024):5182-5189. |
入库方式： OAI收割
来源：自动化研究所
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