Evaluation of Epipole Estimation Methods with/without Rank-2 Constraint across Algebraic/Geometric Error Functions

@article{Migita2007EvaluationOE,
  title={Evaluation of Epipole Estimation Methods with/without Rank-2 Constraint across Algebraic/Geometric Error Functions},
  author={Tsuyoshi Migita and Takeshi Shakunaga},
  journal={2007 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2007},
  pages={1-7}
}
The best method for estimating the fundamental matrix and/or the epipole over a given set of point correspondences between two images is a nonlinear minimization, which searches a rank-2 fundamental matrix that minimizes the geometric error cost function. When convenience is preferred to accuracy, we often use a linear approximation method, which searches a rank-3 matrix that minimizes the algebraic error. Although it has been reported that the algebraic error causes very poor results, it is… CONTINUE READING