• DocumentCode
    2528503
  • Title

    Principal Component Analysis-based Mesh Decomposition

  • Author

    Chang, Jung-Shiong ; Shih, A.C.-C. ; Liao, Hong-Yuan Mark ; Fang, Wen-Hsien

  • Author_Institution
    Nat. Taiwan Univ. of Sci. & Technol., Taipei
  • fYear
    2007
  • fDate
    1-3 Oct. 2007
  • Firstpage
    292
  • Lastpage
    295
  • Abstract
    In this paper, we propose an automatic mesh decomposition technique based on principal component analysis (PCA) and Boolean operations. First, we calculate the normalized protrusion degree of each dual vertex on the smoothed 3-D mesh. The protrusion degree of a vertex and the vertex´s 3-D coordinates form a 4-D feature vector, which we use to represent the polygon mesh. Since a 3-D object is composed of a large number of polygon meshes, we apply PCA to the set of 4-D feature vectors. We take the axes corresponding to the top three principal components as the three axes of a new coordinate system and project the set of 4-D vectors onto the system. Surprisingly, the projected data along the first axis reveals the salient structures of the 3-D object. Therefore, using the first component axis as the search basis, we can identify all the salient parts of an arbitrary 3-D object.
  • Keywords
    Boolean algebra; computational geometry; mesh generation; principal component analysis; vertex functions; Boolean operations; mesh decomposition; polygon mesh; principal component analysis; protrusion degree; vertex; Convergence; Displacement control; Filters; Information analysis; Information science; Laplace equations; Principal component analysis; Smoothing methods; PCA; mesh decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Signal Processing, 2007. MMSP 2007. IEEE 9th Workshop on
  • Conference_Location
    Crete
  • Print_ISBN
    978-1-4244-1274-7
  • Type

    conf

  • DOI
    10.1109/MMSP.2007.4412875
  • Filename
    4412875