Minimal solvers for relative pose with a single unknown radial distortion
Paper in proceeding, 2014

In this paper, we study the problems of estimating relative pose between two cameras in the presence of radial distortion. Specifically, we consider minimal problems where one of the cameras has no or known radial distortion. There are three useful cases for this setup with a single unknown distortion: (i) fundamental matrix estimation where the two cameras are uncalibrated, (ii) essential matrix estimation for a partially calibrated camera pair, (iii) essential matrix estimation for one calibrated camera and one camera with unknown focal length. We study the parameterization of these three problems and derive fast polynomial solvers based on Gröbner basis methods. We demonstrate the numerical stability of the solvers on synthetic data. The minimal solvers have also been applied to real imagery with convincing results.

minimal solver

radial distortion

Author

Y. Kuang

Lund University

J.E. Solem

Lund University

Fredrik Kahl

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

K. Aström

Lund University

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

10636919 (ISSN)

33-40
978-147995117-8 (ISBN)

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/CVPR.2014.12

ISBN

978-147995117-8

More information

Latest update

8/8/2023 6