MESH GENERATION FROM DENSE 3D SCATTERED DATA USING NEURAL NETWORK

• 来源期刊: 计算机辅助绘图.设计与制造(英文版)
• 学科: 工学
• 年，卷（期）: 2004,（1）
• 页码范围: 30-35
• 页数: 6页
• 分类号: TP183
• 语种: 中文

摘要

An improved self-organizing feature map (SOFM) neural network is presented to generate rectangular and hexagonal lattic with normal vector attached to each vertex. After the neural network was trained, the whole scattered data were divided into sub-regions where classified core were represented by the weight vectors of neurons at the output layer of neural network. The weight vectors of the neurons were used to approximate the dense 3-D scattered points, so the dense scattered points could be reduced to a reasonable scale, while the topological feature of the whole scattered points were remained.