Surface reconstruction based on radial basis functions network

被引：0
|
作者：
Liu, Han-bo [1 ]
Wang, Xin
Wu, Xiao-jun
Qiang, Wen-yi
机构：
[1] Harbin Inst Technol, Shenzhen Grad Sch, Dept Control & Mechatron Engn, Shenzhen, Peoples R China
[2] Harbin Inst Technol, Shenzhen Grad Sch, Dept Mech Engn & Automat, Shenzhen, Peoples R China
[3] Harbin Inst Technol, Dept Control Sci & Engn, Harbin 150006, Peoples R China
来源：
ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS | 2006年 / 3973卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：1242 / 1247
页数：6
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