An Improved Robust Method for Iterating Least-Squares Plane Fitting

Abstract:

The iterating eigenvalue least-squares is not robust,so an improved statistic analysis method is introduced for fitting a plane to point clouds containing a great amount of outliers.The method is robust iterating least-squares (RILS).Firstly,some plane models are fitted to the local neighborhoods around sample points by moving least-squares (MLS),and then a good model is selected from those models by least median of squares (LMS)and refined to appropriate the whole point set through eliminating those outliers by iterating eigenvalue least-squares.Different from other backward ways,this method is robust,which retains the accuracy of the original method,and furthermore accelerates the convergence of iteration.