# Efficient Solution of Point-Line Absolute Pose

arXiv: https://arxiv.org/abs/2404.16552 · HTML: https://mlsanity.com/paper/2404.16552/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 32 references that are in the map.
- First posted on arXiv 25 Apr 2024.

## Builds on (most cited first, 6 of 6)

- [GlueStick: Robust Image Matching by Sticking Points and Lines Together](https://mlsanity.com/paper/2304.02008/) (2023)
- [DeepLSD: Line Segment Detection and Refinement with Deep Image Gradients](https://mlsanity.com/paper/2212.07766/) (2022)
- [3D Line Mapping Revisited](https://mlsanity.com/paper/2303.17504/) (2023)
- [3D Visual Perception for Self-Driving Cars using a Multi-Camera System: Calibration, Mapping, Localization, and Obstacle Detection](https://mlsanity.com/paper/1708.09839/) (2017)
- [CvxPnPL: A Unified Convex Solution to the Absolute Pose Estimation Problem from Point and Line Correspondences](https://mlsanity.com/paper/1907.10545/) (2019)
- [Galois/monodromy groups for decomposing minimal problems in 3D reconstruction](https://mlsanity.com/paper/2105.04460/) (2021)

## Built on by (most cited first, 1 of 1)

- [PlanaReLoc: Camera Relocalization in 3D Planar Primitives via Region-Based Structure Matching](https://mlsanity.com/paper/2603.20818/) (2026)

## Abstract (arXiv)

We revisit certain problems of pose estimation based on 3D--2D correspondences between features which may be points or lines. Specifically, we address the two previously-studied minimal problems of estimating camera extrinsics from p ∈  1, 2  point--point correspondences and l=3-p line--line correspondences. To the best of our knowledge, all of the previously-known practical solutions to these problems required computing the roots of degree ≥ 4 (univariate) polynomials when p=2, or degree ≥ 8 polynomials when p=1. We describe and implement two elementary solutions which reduce the degrees of the needed polynomials from 4 to 2 and from 8 to 4, respectively. We show experimentally that the resulting solvers are numerically stable and fast: when compared to the previous state-of-the art, we may obtain nearly an order of magnitude speedup. The code is available at urlhttps://github.com/petrhruby97/efficientabsolute