Abstract：The commonly applied methods of the point-cloud-plane fitting ignored the effects of model error. This paper introduced the penalized least squares to calculate the plane fitting parameters. In the process of calculating, the penalized least squares considers the parameter and the Semi-Parameters at the same time. The fitting precision is greatly improved. We test the results of three different methods (the least squares, eigen-value and penalized least squares methods) on inclined plane, horizontal plane and vertical plane. In comparison, with the rest of methods, the penalized least squares is best.
MENG Qingnian,ZHENG Dehua,XU Yezhang. The Research about the Point-Cloud-Plane Fitting Based on
Penalized Least Squares[J]. jgg, 2015, 35(3): 420-423.
