A comparison of weighted LS methods with LS methods in 3-D motion estimation from stereo image sequences

Estimating 3-D motion parameters from three-dimensional point correspondences is considered. A minimum errors-in-variables formulation of the motion estimation problem is developed to obtain stable and accurate solutions and is connected with the ordinary least squares formulation of the problem. When covariance matrices of 3-D points are known, a closed-form matrix-weighted solution is derived for estimating the motion parameters in the presence of independent and identically distributed (i.i.d.) Gaussian noise. In a general case, a closed-form approximate solution is presented. The experimental results demonstrate that the authors´ solutions are accurate and reliable in the presence of noise with different deviations