Robust estimation of rigid body 3-D motion parameters from point correspondences

The estimation of a rigid body 3-D motion parameters fi om perspective views is typically very sensitive to noise and also to the presence of outliers in the measurements. In this paper we present a robust :3-D motion estimation approach based on a previously proposed method using SVD analysis of the measurements matrix. On the introduction of noise and outliers the performance of the old method was seen to deteriorate rapidly. Here the problem is attacked by; splitting the measurement. set in smaller subsets and combining the properties of the resulting submatrices with the propel ties of the desired solution vector in order to obtain our estimate. The method is very; robust and it has been succesfully tested in both artificial datasets and real images with up to 50 % presence of outliers. In addition. the method is fast, and more importantly, the estimate quality is independent, of the percentage of outliers.