Camera Resection from Known Line Pencils and a Radially Distorted Scanline
Abstract
We present a marker-based geometric estimation framework for the absolute pose of a camera by analyzing the 1D observations in a single radially distorted pixel scanline.We leverage a pair of known co-planar pencils of lines, along with lens distortion parameters, to propose an ensemble of solvers exploring the space of estimation strategies applicable to our setup.First, we present a minimal algebraic solver requiring only six measurements and yielding eight solutions, which relies on the intersection of two conics defined by one of the pencils of lines.Then, we present a unique closed-form geometric solver from seven measurements.Finally, we present an homography-based formulation amenable to linear least-squares from eight or more measurements.Our geometric framework constitutes a theoretical analysis on the minimum geometric context necessary to solve in closed form for the absolute pose of a single camera from a single radially distorted scanline.
Cite
Text
Dibene and Dunn. "Camera Resection from Known Line Pencils and a Radially Distorted Scanline." Conference on Computer Vision and Pattern Recognition, 2025. doi:10.1109/CVPR52734.2025.01477Markdown
[Dibene and Dunn. "Camera Resection from Known Line Pencils and a Radially Distorted Scanline." Conference on Computer Vision and Pattern Recognition, 2025.](https://mlanthology.org/cvpr/2025/dibene2025cvpr-camera/) doi:10.1109/CVPR52734.2025.01477BibTeX
@inproceedings{dibene2025cvpr-camera,
title = {{Camera Resection from Known Line Pencils and a Radially Distorted Scanline}},
author = {Dibene, Juan C. and Dunn, Enrique},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2025},
pages = {15843-15851},
doi = {10.1109/CVPR52734.2025.01477},
url = {https://mlanthology.org/cvpr/2025/dibene2025cvpr-camera/}
}