• DocumentCode
    2863577
  • Title

    Shrinking: another method for surface reconstruction

  • Author

    Lee, In-Kwon ; Kim, Ku-Jin

  • Author_Institution
    Dept. of Comput. Sci., Yonsei Univ., South Korea
  • fYear
    2004
  • fDate
    2004
  • Firstpage
    259
  • Lastpage
    266
  • Abstract
    We present a method to reconstruct a pipe or a canal surface from a point cloud (a set of unorganized points). A pipe surface is defined by a spine curve and a constant radius of a swept sphere, while a variable radius may be used to define a canal surface. In this paper, by using the shrinking and moving least-squares methods, we reduce a point cloud to a thin curve-like point set which will be approximated to the spine curve of a pipe or canal surface. The distance between a point in the thin point cloud and a corresponding point in the original point set represents the radius of the pipe or canal surface.
  • Keywords
    computational geometry; image reconstruction; least squares approximations; surface fitting; canal surface; constant radius; moving least-squares method; pipe surface; point cloud; point set; shrinking; spine curve; surface reconstruction; swept sphere radius; unorganized points; variable radius; Clouds; Computer science; Irrigation; Optimization methods; Rough surfaces; Shape; Solid modeling; Surface fitting; Surface reconstruction; Surface roughness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geometric Modeling and Processing, 2004. Proceedings
  • Print_ISBN
    0-7695-2078-2
  • Type

    conf

  • DOI
    10.1109/GMAP.2004.1290047
  • Filename
    1290047