An Exploration of Freeform Surface Reconstruction by RBF Neural Network

A novel method for surface reconstruction by artificial neural network is introduced， and an effective radial basis function(RBF) network model as well as its learning algorithm is presented.A program of surface reconstruction from dense scattered points by neural network is illustrated and some key techniques are analyzed in detail.The simulation experiments demonstrate that the fitting precision for surface patches by a two layer RBF network is much better than a BP network，and its training speed is also much faster.This approach is valuable for practical applications.