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.
How hard is 3-view triangulation really? InTenth IEEE In- ternational Conference on Computer Vision (ICCV’05) Vol- ume 1, pages 686–693
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.