Separable Four Points Fundamental Matrix

Gil Ben-Artzi
Ariel University, Israel

arXiv

Code




Highlights


Abstract

We present an approach for the computation of the fundamental matrix based on epipolar homography decomposition. We analyze the geometrical meaning of the decomposition-based representation and show that it guarantees a minimal number of RANSAC samples, on the condition that four correspondences are on an image line. Experiments on real-world image pairs show that our approach successfully recovers such four correspondences, provides accurate results and requires only a small number of RANSAC iterations.

RANSAC Iterations vs. Outlier Rate


                      Ideal Case: one solution per sample


              Practical Case: 2.43 solutions per sample,
                59 perprocessing iterations for our approach


Our Two-Steps Approach - How it works

A. Efficiently match a line segment with at least 4 points across images



B. Compute epipolar homography, sample 4 more points and compute F




Try our code!

Paper


Separable Four Points Fundamental Matrix, G. Ben-Artzi
arXiv



Acknowledgements

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