A fast method for implicit surface reconstruction based on radial basis functions network from 3D scattered points.
A method for arbitrary surface reconstruction from 3D large scattered points is proposed in this paper. According to the properties of 3D points, e.g. the non-uniform distribution and unknown topology, an implicit surface model is adopted based on radial basis functions network. And because of the property of locality of radial basis function, the method is fast and robust in surface reconstruction. Furthermore, an adapted K-Means algorithm is used to reduce reconstruction centers. For features completeness, two effective methods are introduced to extract the feature points before the adapted K-Means algorithm. Experiment results show that the presented approach is a good solution for reconstruction from 3D large scattered points.
Liu
Hanbo
H
Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen Guangdong, 518055, P.R. China. liu_hanbo@hit.edu.cn
Wang
Xin
X
Qiang
Wenyi
W
D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D006801:Humans; D021621:Imaging, Three-Dimensional; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted