Abstract

Fitting of data points by parametric curves and surfaces is demanded in many scientific fields. In this paper we review and analyze existing least squares orthogonal distance fitting techniques in a general numerical optimization framework. Two new geometric variant methods (GTDM and CDM) are proposed. The geometric meanings of existing and modified optimization methods are also revealed