Function Approximation for Free-Form Surfaces

This paper presents a survey of techniques used for function approximation and free form surface reconstruction. A comparative study is performed between classical interpolation methods and two methods based on neural networks. We show that the neural networks approach provides good approximation and provides better results than classical techniques when used for reconstructing smoothly varying surfaces.