Essential Matrix Estimation

Version 1.1 (96,5 ko) par Manolis Lourakis
Compute the essential matrix from a set of corresponding image projections
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Mise à jour 31 jan. 2020

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This code uses a five point algorithm in a RANSAC framework to compute a robust initial estimate of the essential matrix.
That estimate is subsequently refined by parameterizing the essential matrix with six parameters (3 for the Rodrigues vector and 3 for the translation vector) and minimizing the cumulative symmetric distance from epipolar lines for RANSAC inliers with the Levenberg–Marquardt algorithm.
NOTE: The code requires several functions by others, see README.txt for further instructions.

See also https://en.wikipedia.org/wiki/Essential_matrix

Citation pour cette source

Manolis Lourakis (2025). Essential Matrix Estimation (https://fr.mathworks.com/matlabcentral/fileexchange/67580-essential-matrix-estimation), MATLAB Central File Exchange. Extrait(e) le .

Compatibilité avec les versions de MATLAB
Créé avec R2012b
Compatible avec toutes les versions
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E_estim

Version Publié le Notes de version
1.1

Minor changes to ransacfitessmatrix.m

Included 3rd party scripts
1.0.0.0

Updated description
Updated description
Updated description
Updated description
Updated dependencies