中文摘要：

对三维点云进行隐式曲面重建是解决虚拟现实等方面所存在问题的关键.本文提出了一种基于椭球约束的径向基函数隐式曲面建模的算法,该方法在仅有点云信息的前提下仍能够非常精确地拟合点云数据.当点云稀疏时拟合后的模型可以非常好地保证模型的主要特征,但对于拟合大规模数据点集时,模型会出现冗余现象,保特征效果不理想且效率低下.需将点云进行适当分割,然后并行拟合被分割点云并将它们进行光滑拼接处理.实验效果表明该算法保特征效果非常好且效率明显提高.

英文摘要：

Implicit surface fitting to a set of scattered points plays an important role in solving many problems occurring in virtual reality and so on. This paper presents an implicit surface fitting algorithm using radial basis functions with an ellipsoid constraint. This method can fit the data accurately by use of information of point clouds. The fitted shape can still capture the main features of the object when the data sets are sparse. The fitted surface may contain many redundant components and not represent the actual shape properly with longer time when fitting large data set. Large-scale scattered data is needed to be subdivided adaptively, these subdivided data fit simultaneously and these simpler implicit surfaces blended smoothly. The experimental results show that the algorithm is good in preserving feature and can improve the efficiency obviously.