Robust Software for Computing Camera Motion Parameters
We revisit the method of Tsai, Huang, and Zhu for the computation of camera motion parameters in computer vision. We elucidate some spectral properties of the homography matrices that arise, which are rank-one perturbations of rotation matrices. We show how to correct for noise by finding the rank-one perturbation of a rotation closest to a given matrix. We illustrate some of the inaccuracies and computational failures that can arise when using the formulas given by Tsai, and we propose new formulas that avoid these pitfalls. A computational experiment shows that the new methods are indeed quite robust.
homography camera pose singular value decomposition