COST-EFFECTIVE CAMERA LOCALIZATION AIDED BY PRIOR POINT CLOUDS MAPS FOR LEVEL 3 AUTONOMOUS DRIVING VEHICLES Article Swipe
Yee Leung
,
Xiujuan Zheng
,
Harvey Ho
,
Weisong Wen
,
Li‐Ta Hsu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.5194/isprs-archives-xlviii-1-w1-2023-227-2023
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.5194/isprs-archives-xlviii-1-w1-2023-227-2023
Precise and robust localization is critical for many navigation tasks, especially autonomous driving systems. The most popular localization approach is global navigation satellite systems (GNSS). However, it has several shortcomings such as multipath and nonline- of-sight reception. Vision-based localization is one of the approaches without using GNSS which is based on vision. This paper used visual localization with a prior 3D LiDAR map. Compared to common methods for visual localization using camera-acquired maps, this paper used the method that tracks the image feature and poses of a monocular camera to match with prior 3D LiDAR maps. This paper reconstructs the image feature to several sets of 3D points by a local bundle adjustment-based visual odometry system. Those 3D points matched with the prior 3D point cloud map to track the globe pose of the user. The visual localization approach has several advantages. (1) Since it only relies on matching geometry, it is robust to changes in ambient luminosity appearance. (2) Also, it uses the prior 3D map to provide viewpoint invariance. Moreover, the proposed method only requires users to use low-cost and lightweight camera sensors.
Related Topics
Concepts
Computer vision
Artificial intelligence
Computer science
Point cloud
Bundle adjustment
Visual odometry
GNSS applications
Simultaneous localization and mapping
Feature (linguistics)
Lidar
RANSAC
Monocular vision
Global Positioning System
Photogrammetry
Image (mathematics)
Remote sensing
Mobile robot
Geography
Robot
Telecommunications
Linguistics
Philosophy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.5194/isprs-archives-xlviii-1-w1-2023-227-2023
- https://isprs-archives.copernicus.org/articles/XLVIII-1-W1-2023/227/2023/isprs-archives-XLVIII-1-W1-2023-227-2023.pdf
- OA Status
- diamond
- Cited By
- 1
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4378194472
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4378194472Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.5194/isprs-archives-xlviii-1-w1-2023-227-2023Digital Object Identifier
- Title
-
COST-EFFECTIVE CAMERA LOCALIZATION AIDED BY PRIOR POINT CLOUDS MAPS FOR LEVEL 3 AUTONOMOUS DRIVING VEHICLESWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-05-25Full publication date if available
- Authors
-
Yee Leung, Xiujuan Zheng, Harvey Ho, Weisong Wen, Li‐Ta HsuList of authors in order
- Landing page
-
https://doi.org/10.5194/isprs-archives-xlviii-1-w1-2023-227-2023Publisher landing page
- PDF URL
-
https://isprs-archives.copernicus.org/articles/XLVIII-1-W1-2023/227/2023/isprs-archives-XLVIII-1-W1-2023-227-2023.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://isprs-archives.copernicus.org/articles/XLVIII-1-W1-2023/227/2023/isprs-archives-XLVIII-1-W1-2023-227-2023.pdfDirect OA link when available
- Concepts
-
Computer vision, Artificial intelligence, Computer science, Point cloud, Bundle adjustment, Visual odometry, GNSS applications, Simultaneous localization and mapping, Feature (linguistics), Lidar, RANSAC, Monocular vision, Global Positioning System, Photogrammetry, Image (mathematics), Remote sensing, Mobile robot, Geography, Robot, Telecommunications, Linguistics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1Per-year citation counts (last 5 years)
- References (count)
-
52Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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