我们使用光线的基础功能(RBF ) 重建从 3D 的光滑的表面散布了数据。一个对象的表面含蓄地被定义为适合到给定的表面数据的 RBF 的零个集合。我们与光线的基础功能在表面重建的方法上建议改进。散布数据的一个稀少的近似集合被减少插入内推的数字构造表面上的点。我们在场为发现离开表面正常的一个适应方法指。方程的顺序逐渐地作为离开表面限制还原剂的数字极大地减少。试验性的结果被提供说明建议方法是柔韧的并且可以拉美丽的图形。
We use Radial Basis Functions (RBFs) to reconstruct smooth surfaces from 3D scattered data. An object's surface is defined implicitly as the zero set of an RBF fitted to the given surface data. We propose improvements on the methods of surface reconstruction with radial basis functions. A sparse approximation set of scattered data is constructed by reducing the number of interpolating points on the surface. We present an adaptive method for finding the off-surface normal points. The order of the equation decreases greatly as the number of the off-surface constraints reduces gradually. Experimental results are provided to illustrate that the proposed method is robust and may draw beautiful graphics.