• DocumentCode
    482199
  • Title

    3D Mesh Skeleton Extraction Based on Feature Points

  • Author

    Gong, Faming ; Kang, Cui

  • Author_Institution
    Coll. of Comput. & Commun. Eng., China Univ. of Pet. (East China), Dongying
  • Volume
    1
  • fYear
    2009
  • fDate
    22-24 Jan. 2009
  • Firstpage
    326
  • Lastpage
    329
  • Abstract
    A novel efficient skeleton extraction algorithm is proposed, which is based on feature points extraction and Reeb graph theories. Because of the topological facility of feature points, a model can be divided into several branches according to them. One feature point can present one branch. So we just extract the other point of the branch - that could be skeleton point, connect these points with their corresponding feature points, then we can get all branch skeletons. Finally, connecting branch skeletons through connecting skeleton points according the topological relationship of each skeleton point preserving, then 3D modelpsilas skeleton can be extracted.Without pre-processing stages and without input parameters, this algorithm can automatically extract the skeleton of 3D models. Theoretical analyses and experimental results show that our method has a lower computing complexity, and meets the requirement of extracting nice-looking and affine-invariant skeletons efficiently.
  • Keywords
    computational complexity; feature extraction; 3D mesh skeleton extraction; Reeb graph theories; affine-invariant skeletons; computing complexity; feature points extraction; Computer graphics; Educational institutions; Extremities; Feature extraction; Geophysics computing; Graph theory; Joining processes; Petroleum; Shape; Skeleton; skeleton; skeleton extraction; skeleton point;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Engineering and Technology, 2009. ICCET '09. International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-3334-6
  • Type

    conf

  • DOI
    10.1109/ICCET.2009.71
  • Filename
    4769481