LS-RBF network based 3D surface reconstruction method

Authors:
P. Z. Wen;X. J. Wu;Y. Zhu;X. W. Peng
Affiliations:
Guilin University of Electronic Technology, Guilin, China;Harbin Institute of Technology, Shenzhen Graduate School, Shenzhen, China;Guilin University of Electronic Technology, Guilin, China;Guilin University of Electronic Technology, Guilin, China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

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.