Neural networks based recognition of 3D freeform surface from 2D Sketch

Sun, Guangmin, Qin, Sheng-feng and Wright, David (2005) Neural networks based recognition of 3D freeform surface from 2D Sketch. In: Proceedings of EUROCON 2005 - The International Conference on Computer as a Tool. IEEE, Piscataway, NJ, pp. 1378-1381. ISBN 142440049X

Full text not available from this repository. (Request a copy)

Abstract

In this paper, the back propagation (BP) network and radial basis function (RBF) neural network are employed to recognize and reconstruct 3D freeform surface from 2D freehand sketch. Some tests and comparison experiments have been made to evaluate the performance for the reconstruction of freeform surfaces of both networks using simulation data. The experimental results show that both BP and RBF based freeform surface reconstruction methods are feasible; and the RBF network performed better. The RBF average point error between the reconstructed 3D surface data and the desired 3D surface data is less than 0.05 over all our 75 test sample data

Item Type:	Book Section
Uncontrolled Keywords:	artificial intelligence, freeform surface recognition, neural networks, sketch design
Subjects:	G900 Others in Mathematical and Computing Sciences W200 Design studies
Depositing User:	Ay Okpokam
Date Deposited:	22 Dec 2015 11:55
Last Modified:	12 Oct 2019 19:34
URI:	http://nrl.northumbria.ac.uk/id/eprint/25195

Downloads