LS-RBF Network Based 3D Surface Reconstruction Method
We propose a new method for surface reconstruction from scattered point set based on least square radial basis function network in this paper. The RBF network is trained by fewer samples and we can get the weights of this network. Then an implicit continuous function is constructed to represent a 3D model. In this method, a binary tree is used to efficiently traversal the data set. Our scheme can overcome the numerical ill-conditioning of coefficient matrix and over-fitting problem. Some examples are presented to show the effectiveness of out algorithm in 2D and 3D cases. The numerical experiment shows high efficiency and satisfactory visual quality.
Neural network Radial basis function point filtering surface reconstruction
P.Z. Wen X.J. Wu Y. Zhu X.W. Peng
Guilin University of Electronic Technology, Guilin 541004, China Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
5785-5789
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）