Revisiting the P3P Problem
(2023) 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023 p.4872-4880- Abstract
One of the classical multi-view geometry problems is the so called P3P problem, where the absolute pose of a calibrated camera is determined from three 2D-to-3D correspondences. Since these solvers form a critical component of many vision systems (e.g. in localization and Structure-from-Motion), there have been significant effort in developing faster and more stable algorithms. While the current state-of-the-art solvers are both extremely fast and stable, there still exist configurations where they break down. In this paper we algebraically formulate the problem as finding the intersection of two conics. With this formulation we are able to analytically characterize the real roots of the polynomial system and employ a tailored solution... (More)
One of the classical multi-view geometry problems is the so called P3P problem, where the absolute pose of a calibrated camera is determined from three 2D-to-3D correspondences. Since these solvers form a critical component of many vision systems (e.g. in localization and Structure-from-Motion), there have been significant effort in developing faster and more stable algorithms. While the current state-of-the-art solvers are both extremely fast and stable, there still exist configurations where they break down. In this paper we algebraically formulate the problem as finding the intersection of two conics. With this formulation we are able to analytically characterize the real roots of the polynomial system and employ a tailored solution strategy for each problem instance. The result is a fast and stable solver, that is able to correctly solve cases where competing methods might fail. Our experimental evaluation shows that we outperform the current state-of-the-art methods both in terms of speed and success rate.
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- author
- Ding, Yaqing LU ; Yang, Jian ; Larsson, Viktor LU ; Olsson, Carl LU and Åström, Kalle LU
- organization
-
- Computer Vision and Machine Learning (research group)
- Mathematics (Faculty of Engineering)
- LTH Profile Area: AI and Digitalization
- Mathematical Imaging Group (research group)
- ELLIIT: the Linköping-Lund initiative on IT and mobile communication
- LU Profile Area: Nature-based future solutions
- LU Profile Area: Natural and Artificial Cognition
- LTH Profile Area: Engineering Health
- eSSENCE: The e-Science Collaboration
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- 3D from multi-view and sensors
- host publication
- Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
- pages
- 9 pages
- publisher
- IEEE Computer Society
- conference name
- 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023
- conference location
- Vancouver, Canada
- conference dates
- 2023-06-18 - 2023-06-22
- external identifiers
-
- scopus:85172406023
- ISBN
- 9798350301298
- DOI
- 10.1109/CVPR52729.2023.00472
- language
- English
- LU publication?
- yes
- id
- 5c3f8ae6-a3cf-47c9-90e3-87f20fd8c290
- date added to LUP
- 2024-01-15 11:45:17
- date last changed
- 2024-02-28 08:56:58
@inproceedings{5c3f8ae6-a3cf-47c9-90e3-87f20fd8c290, abstract = {{<p>One of the classical multi-view geometry problems is the so called P3P problem, where the absolute pose of a calibrated camera is determined from three 2D-to-3D correspondences. Since these solvers form a critical component of many vision systems (e.g. in localization and Structure-from-Motion), there have been significant effort in developing faster and more stable algorithms. While the current state-of-the-art solvers are both extremely fast and stable, there still exist configurations where they break down. In this paper we algebraically formulate the problem as finding the intersection of two conics. With this formulation we are able to analytically characterize the real roots of the polynomial system and employ a tailored solution strategy for each problem instance. The result is a fast and stable solver, that is able to correctly solve cases where competing methods might fail. Our experimental evaluation shows that we outperform the current state-of-the-art methods both in terms of speed and success rate.</p>}}, author = {{Ding, Yaqing and Yang, Jian and Larsson, Viktor and Olsson, Carl and Åström, Kalle}}, booktitle = {{Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition}}, isbn = {{9798350301298}}, keywords = {{3D from multi-view and sensors}}, language = {{eng}}, pages = {{4872--4880}}, publisher = {{IEEE Computer Society}}, title = {{Revisiting the P3P Problem}}, url = {{http://dx.doi.org/10.1109/CVPR52729.2023.00472}}, doi = {{10.1109/CVPR52729.2023.00472}}, year = {{2023}}, }