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Surface Reconstruction from LiDAR Data with Extended Snake Theory

  • Yi-Hsing Tseng
  • Kai-Pei Tang
  • Fu-Chen Chou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4679)

Abstract

Surface reconstruction from implicit data of sub-randomly distributed 3D points is the key work of extracting explicit information from LiDAR data. This paper proposes an approach of extended snake theory to surface reconstruction from LiDAR data. The proposed algorithm approximates a surface with connected planar patches. Growing from an initial seed point, a surface is reconstructed by attaching new adjacent planar patches based on the concept of minimizing the deformable energy. A least-squares solution is sought to keep a local balance of the internal and external forces, which are inertial forces maintaining the flatness of a surface and pulls of observed LiDAR points bending the growing surface toward observations. Experiments with some test data acquired with a ground-based LiDAR demonstrate the feasibility of the proposed algorithm. The effects of parameter settings on the delivered results are also investigated.

Keywords

Snake theory surface reconstruction LiDAR laser scanning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Yi-Hsing Tseng
    • 1
  • Kai-Pei Tang
    • 1
  • Fu-Chen Chou
    • 1
  1. 1.Department of Geomatics, National Cheng Kung University, No.1 University Road, TainanTaiwan

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