CVPR 20260 citations

Homaloidal parametrization for detecting critical two-view configurations

Rakshith Madhavan, Matteo Forlivesi, Marina Bertolini, Cristina Turrini, Federica Arrigoni, Luca Magri

Abstract

We consider the problem of identifying degenerate configurations while estimating the fundamental matrix from (at least) 8 point correspondences. It is known that such configurations correspond to an ill-posed estimation of the fundamental matrix, so it is important to identify them in practice. So far, a practical degeneracy test is only available for the cases of planar scenes and pure rotation, while the case of the general critical surface (e.g., a hyperboloid/cone/cylinder containing 3D points and camera centres) is less studied, and the only available method is highly unstable, involving a pre-computed fundamental matrix. In this paper, we propose a novel degeneracy test for detecting points on the critical surface. By exploiting the geometry of the so-called "homaloidal net of conics", we are able to design a simple and very practical test that requires the linear estimation of a quadratic transformation from image correspondences. Our test does not require a fundamental matrix in advance and turns out to be more stable than its closest competitor, as shown in our experiments on both synthetic and real-world degenerate configurations.

BibTeX
@inproceedings{cvpr2026_homaloidalparame,
  title = {Homaloidal parametrization for detecting critical two-view configurations},
  author = {Rakshith Madhavan and Matteo Forlivesi and Marina Bertolini and Cristina Turrini and Federica Arrigoni and Luca Magri},
  booktitle = {CVPR 2026},
  year = {2026}
}
Homaloidal parametrization for detecting critical two-view configurations · CVPR 2026