This paper revisits the method of Tsai, Huang, and Zhu for the computation of camera motion parameters in computer vision. It elucidates some spectral properties of the homography matrices that arise, which are rank-one perturbations of rotation matrices. The paper shows how to correct for noise by finding the rank-one perturbation of a rotation closest to a give matrix. The paper illustrates some of the inaccuracies and computational failures that can arise when using the formulas given by Tsai, and it proposes new formulas that avoid these pitfalls. A computational experiment shows that the new methods are indeed quite robust.
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