Tangent Sampson Error: Fast Approximate Two-View Reprojection Error for Central Camera Models

ICCV 2023 pp. 3370-3378

doi:10.1109/ICCV51070.2023.00312 /iccv/2023/terekhov2023iccv-tangent/

Abstract

In this paper we introduce the Tangent Sampson error, which is a generalization of the classical Sampson error in two-view geometry that allows for arbitrary central camera models. It only requires local gradients of the distortion map at the original correspondences (allowing for pre-computation) resulting in a negligible increase in computational cost when used in RANSAC or local refinement. The error effectively approximates the true-reprojection error for a large variety of cameras, including extremely wide field-of-view lenses that cannot be undistorted to a single pinhole image. We show experimentally that the new error outperforms competing approaches both when used for model scoring in RANSAC and for non-linear refinement of the relative camera pose.

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Text

Terekhov and Larsson. "Tangent Sampson Error: Fast Approximate Two-View Reprojection Error for Central Camera Models." International Conference on Computer Vision, 2023. doi:10.1109/ICCV51070.2023.00312

Markdown

[Terekhov and Larsson. "Tangent Sampson Error: Fast Approximate Two-View Reprojection Error for Central Camera Models." International Conference on Computer Vision, 2023.](https://mlanthology.org/iccv/2023/terekhov2023iccv-tangent/) doi:10.1109/ICCV51070.2023.00312

BibTeX

@inproceedings{terekhov2023iccv-tangent,
  title     = {{Tangent Sampson Error: Fast Approximate Two-View Reprojection Error for Central Camera Models}},
  author    = {Terekhov, Mikhail and Larsson, Viktor},
  booktitle = {International Conference on Computer Vision},
  year      = {2023},
  pages     = {3370-3378},
  doi       = {10.1109/ICCV51070.2023.00312},
  url       = {https://mlanthology.org/iccv/2023/terekhov2023iccv-tangent/}
}