High Accuracy Computation of Rank-Constrained Fundamental Matrix

@inproceedings{Sugaya2007HighAC,
  title={High Accuracy Computation of Rank-Constrained Fundamental Matrix},
  author={Yasuyuki Sugaya and Kenichi Kanatani},
  booktitle={BMVC},
  year={2007}
}
A new method is presented for computing the fundamental matrix from point correspondences: its singular value decomposition (SVD) is optimized by the Levenberg-Marquard (LM) method. The search is initialized by optimal correction of unconstrained ML. There is no need for tentative 3-D reconstruction. The accuracy achieves the theoretical bound (the KCR lower bound).