Parameterization of unorganized cylindrical point clouds for least squares B-spline surface fitting

Abstract

In this study, a method for parameterizing unorganized cylindrical point clouds is suggested. The proposed method creates an initial base surface onto which points are projected to estimate parameter values for each point. To produce an initial base surface, we suggest the concept of a virtual turntable and apply multilevel B-splines. Grid points are projected to the point cloud to increase the accuracy of the initial base surface. During the projection process, a modified weight factor is introduced. Lastly, global B-spline surface interpolation is executed to generate an initial base surface, which undergoes a process of refinement and relaxation. Parameter values are then obtained by projecting the point cloud onto the surface orthogonally. Experiments show that the proposed method successfully estimates parameters and solves the problems of self-loop and crossover. Furthermore, the results of experiment show that the proposed weight factor is more effective than the existing weight factor for point directed projection.