A new matrix-inversion-free solver reconstructs hidden-variable determinant polynomials for minimal problems using IFFT interpolation from samples and recovers solutions via rank-1 submatrices and Cramer's rule.
Usac: A universal framework for random sample consensus.IEEE transactions on pattern analysis and machine intelligence, 35(8):2022–2038
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Solving Minimal Problems Without Matrix Inversion Using FFT-Based Interpolation
A new matrix-inversion-free solver reconstructs hidden-variable determinant polynomials for minimal problems using IFFT interpolation from samples and recovers solutions via rank-1 submatrices and Cramer's rule.