A new method for estimating 3D motion parameters from point correspondences is presented in this paper. The problem formulation leads to the solution of an overdetermined linear system of equations. The total least squares (TLS) method is found to be the most suitable one for estimating the solution since our model includes noise both in the observation data and in the system matrix. The translation parameters are obtained immediately from the above solution whereas the rotation parameters are estimated from the solution of another TLS problem. Tests of our method on artificial data and on real images show its robustness against Gaussian additive noise and against digitalization noise introduced by finite pixel resolution.
['Konstantinos I. Diamantaras', 'Theophilos Papadimitriou', 'Michael G. Strintzis', 'Manos Roumeliotis']
Total least squares 3-D motion estimation