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Main Authors: Lee, Seong Hun, Vandewalle, Patrick, Civera, Javier
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2508.01312
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author Lee, Seong Hun
Vandewalle, Patrick
Civera, Javier
author_facet Lee, Seong Hun
Vandewalle, Patrick
Civera, Javier
contents We revisit the classical Perspective-Three-Point (P3P) problem, which aims to recover the absolute pose of a calibrated camera from three 2D-3D correspondences. It has long been known that P3P can be reduced to a quartic polynomial with analytically simple and computationally efficient coefficients. However, this elegant formulation has been largely overlooked in modern literature. Building on the theoretical foundation that traces back to Grunert's work in 1841, we propose a compact algebraic solver that achieves accuracy and runtime comparable to state-of-the-art methods. Our results show that this classical formulation remains highly competitive when implemented with modern insights, offering an excellent balance between simplicity, efficiency, and accuracy.
format Preprint
id arxiv_https___arxiv_org_abs_2508_01312
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle P3P Made Easy
Lee, Seong Hun
Vandewalle, Patrick
Civera, Javier
Computer Vision and Pattern Recognition
We revisit the classical Perspective-Three-Point (P3P) problem, which aims to recover the absolute pose of a calibrated camera from three 2D-3D correspondences. It has long been known that P3P can be reduced to a quartic polynomial with analytically simple and computationally efficient coefficients. However, this elegant formulation has been largely overlooked in modern literature. Building on the theoretical foundation that traces back to Grunert's work in 1841, we propose a compact algebraic solver that achieves accuracy and runtime comparable to state-of-the-art methods. Our results show that this classical formulation remains highly competitive when implemented with modern insights, offering an excellent balance between simplicity, efficiency, and accuracy.
title P3P Made Easy
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2508.01312