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Surface Reconstruction Based on Radial Basis Functions Network

  • Han-bo Liu
  • Xin Wang
  • Xiao-jun Wu
  • Wen-yi Qiang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3973)

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.

Keywords

Radial Basis Function Radial Basis Function Network Move Little Square Implicit Surface Scattered Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Han-bo Liu
    • 1
  • Xin Wang
    • 2
  • Xiao-jun Wu
    • 1
  • Wen-yi Qiang
    • 3
  1. 1.Department of Control and Mechatronics EngineeringHarbin Institute of Technology Shenzhen Graduate SchoolShenzhenP.R. China
  2. 2.Department of Mechanical Engineering and AutomationHarbin Institute of Technology Shenzhen Graduate SchoolShenzhenP.R. China
  3. 3.Department of Control Science and EngineeringHarbin Institute of TechnologyHarbinP.R. China

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