CVAug 2, 2025

P3P Made Easy

arXiv:2508.01312v31 citationsh-index: 8
Originality Incremental advance
AI Analysis

This work provides a simpler and efficient solution for computer vision practitioners dealing with camera pose estimation, though it is incremental as it builds on existing theoretical foundations.

The paper tackled the classical Perspective-Three-Point (P3P) problem for camera pose recovery by revisiting an overlooked algebraic formulation, resulting in a compact solver that achieves accuracy and runtime comparable to state-of-the-art methods.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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