We present a novel approach for RANSAC-based computation of the fundamental matrix based on epipolar homography decomposition. We analyze the geometrical meaning of the decomposition-based representation and show that it directly induces a consecutive sampling strategy of two independent sets of correspondences. We show that our method guarantees a minimal number of evaluated hypotheses with respect to current minimal approaches, on the condition that there are four correspondences on an image line. We validate our approach on real-world image pairs, providing fast and accurate results.
@article{arxiv.2006.05926,
title = {Separable Four Points Fundamental Matrix},
author = {Gil Ben-Artzi},
journal= {arXiv preprint arXiv:2006.05926},
year = {2020}
}