Surface reconstruction based on radial basis functions network

Authors:
Han-bo Liu;Xin Wang;Xiao-jun Wu;Wen-yi Qiang
Affiliations:
Department of Control and Mechatronics Engineering, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, P.R. China;Department of Mechanical Engineering and Automation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, P.R. China;Department of Control and Mechatronics Engineering, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, P.R. China;Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, P.R. China
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Year:
2006

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Abstract

A new method for arbitrary 3d-object reconstruction in unknown environment is proposed in this paper. The implicit surface is reconstructed based on radial basis functions network from range scattered data. For the property of locality of radial basis function, the method is fast and robust with respect to large data. Furthermore, an adapted K-Means algorithm is used to reduce RBF centers for reconstruction. Experiment results show that the presented approach is helpful in speed improvement and is a good solution for large data reconstruction.