EPnP: An Accurate O(n) Solution to the PnP Problem
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The closed-form EPnP pose solver is suitable for both coplanar and non-coplanar 3D-2D key points and is state-of-the-art due to fast convergence to global minima and robustness against outliers.
“First, the closed-form EPnP [14] pose solver is used to estimate the initial guess and it is suitable for both coplanar and non-coplanar 3D-2D key points.This method is considered to be state-of-the-art due to fast convergence to global minima and robustness against outliers.”
From Transformer Network-Aided Relative Pose Estimation for Non-cooperative Spacecraft Using Vision Sensor (2024) · cites this paper as [14]
The Abstract describes EPnP as a closed-form, non-iterative solver for both planar and non-planar 3D-to-2D correspondences, and the Conclusion reports that it is fast and accurate. The paper does not attribute fast convergence to a global minimum to the closed-form solver; Related Work says an iterative comparator can converge to an inappropriate local minimum. In “Real Images,” erroneous correspondences are filtered with RANSAC, so that passage does not establish that EPnP itself is robust against outliers. (LLM, conf=0.90)
Experimental — accuracy not yet measuredGiven known 2D-3D keypoint correspondences, a Perspective-n-Point problem is solved to output the complete 6D pose.
“Then, given the known 2D3D keypoint correspondences, a Perspectiven -Point (P n P) problem is solved to output the complete 6D pose [42].”
From SPEED+: Next-Generation Dataset for Spacecraft Pose Estimation across Domain Gap (2022) · cites this paper as [42]
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- Authors
- Lepetit, V., Moreno-Noguer, F., & Fua, P.
- Affiliations
- École Polytechnique Fédérale de Lausanne (CH)
- Corresponding author
- Moreno-Noguer, Francesc
- Venue
- International Journal of Computer Vision
- Published
- 2008-07-19
- Volume
- 81
- Issue
- 2
- Pages
- 155-166
- ISSN
- 0920-5691 (ISSN-L)
- 1573-1405
- OpenAlex
- W1991544872
- Cited by
- 3,298
- References
- 33
- Citations by year
- 2026: 271 · 2025: 333 · 2024: 335 · 2023: 339 · 2022: 352 · 2021: 325 · 2020: 267 · 2019: 276 · 2018: 166 · 2017: 158 · 2016: 119 · 2015: 106 · 2014: 86 · 2013: 69 · 2012: 39
- FWCI
- 25.29
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- International Journal of Computer Vision (publishedVersion)
- UPCommons institutional repository (Universitat Politècnica de Catalunya) (submittedVersion, cc-by-nc-nd)
- reroDoc Digital Library (submittedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- RECERCAT (Consorci de Serveis Universitaris de Catalunya) (submittedVersion, other-oa)
- Funders
- National Science Foundation
- European Commission
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Optical measurement and interference techniques
- Physical Sciences › Engineering › Aerospace Engineering › Robotics and Sensor-Based Localization
- Keywords
- perspective-n-point, camera pose estimation, calibrated cameras, analytical solution, linear computational complexity, eigenvalue decomposition
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