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Revisiting the P3P Problem

Ding, Yaqing LU ; Yang, Jian ; Larsson, Viktor LU ; Olsson, Carl LU and Åström, Kalle LU orcid (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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Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
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}},
}