# Six-Point Method for Multi-Camera Systems with Reduced Solution Space

arXiv: https://arxiv.org/abs/2402.18066 · HTML: https://mlsanity.com/paper/2402.18066/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 71 references that are in the map.
- First posted on arXiv 28 Feb 2024.

## Builds on (most cited first, 12 of 12)

- [nuScenes: A multimodal dataset for autonomous driving](https://mlsanity.com/paper/1903.11027/) (2019)
- [A Pose-only Solution to Visual Reconstruction and Navigation](https://mlsanity.com/paper/2103.01530/) (2021)
- [An Efficient Solution to Non-Minimal Case Essential Matrix Estimation](https://mlsanity.com/paper/1903.09067/) (2019)
- [Making Affine Correspondences Work in Camera Geometry Computation](https://mlsanity.com/paper/2007.10032/) (2020)
- [Affine Correspondences between Multi-Camera Systems for Relative Pose Estimation](https://mlsanity.com/paper/2306.12996/) (2023)
- [Equivalent Constraints for Two-View Geometry: Pose Solution/Pure Rotation Identification and 3D Reconstruction](https://mlsanity.com/paper/1810.05863/) (2018)
- [Relative Pose from Deep Learned Depth and a Single Affine Correspondence](https://mlsanity.com/paper/2007.10082/) (2020)
- [Optimizing Elimination Templates by Greedy Parameter Search](https://mlsanity.com/paper/2203.14901/) (2022)
- [Quaternion Based Camera Pose Estimation From Matched Feature Points](https://mlsanity.com/paper/1704.02672/) (2017)
- [Resultant Based Incremental Recovery of Camera Pose from Pairwise Matches](https://mlsanity.com/paper/1901.09364/) (2019)
- [Robust Self-calibration of Focal Lengths from the Fundamental Matrix](https://mlsanity.com/paper/2311.16304/) (2023)
- [From Correspondences to Pose: Non-minimal Certifiably Optimal Relative Pose without Disambiguation](https://mlsanity.com/paper/2312.05995/) (2023)

## Built on by (most cited first, 7 of 7)

- [Full-DoF Egomotion Estimation for Event Cameras Using Geometric Solvers](https://mlsanity.com/paper/2503.03307/) (2025)
- [Perceptual Region-Driven Infrared-Visible Co-Fusion for Extreme Scene Enhancement](https://mlsanity.com/paper/2512.06400/) (2025)
- [Fusion-Restoration Image Processing Algorithm to Improve the High-Temperature Deformation Measurement](https://mlsanity.com/paper/2601.12682/) (2026)
- [High Dynamic Range Imaging Based on an Asymmetric Event-SVE Camera System](https://mlsanity.com/paper/2603.00467/) (2026)
- [An Opticalmechanics Framework for Dynamic Estimation of Multibody Systems](https://mlsanity.com/paper/2606.09383/) (2026)
- [Efficient Minimal Solvers for Visual-Inertial Relative Pose Estimation in Multi-Camera Systems](https://mlsanity.com/paper/2606.09477/) (2026)
- [Efficient Minimal Solvers for Relative Pose Estimation in Autonomous Driving Applications](https://mlsanity.com/paper/2606.09569/) (2026)

## Abstract (arXiv)

Relative pose estimation using point correspondences (PC) is a widely used technique. A minimal configuration of six PCs is required for two views of generalized cameras. In this paper, we present several minimal solvers that use six PCs to compute the 6DOF relative pose of multi-camera systems, including a minimal solver for the generalized camera and two minimal solvers for the practical configuration of two-camera rigs. The equation construction is based on the decoupling of rotation and translation. Rotation is represented by Cayley or quaternion parametrization, and translation can be eliminated by using the hidden variable technique. Ray bundle constraints are found and proven when a subset of PCs relate the same cameras across two views. This is the key to reducing the number of solutions and generating numerically stable solvers. Moreover, all configurations of six-point problems for multi-camera systems are enumerated. Extensive experiments demonstrate the superior accuracy and efficiency of our solvers compared to state-of-the-art six-point methods. The code is available at https://github.com/jizhaox/relpose-6pt