• DocumentCode
    3315363
  • Title

    Variational problems and PDEs on implicit surfaces

  • Author

    Bertalmìo, Marcelo ; Sapiro, Guillermo ; Cheng, Li-Tien ; Osher, Stanley

  • Author_Institution
    Minnesota Univ., MN, USA
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    186
  • Lastpage
    193
  • Abstract
    A novel framework for solving variational problems and partial differential equations for scalar and vector-valued data defined on surfaces is introduced. The key idea is to implicitly represent the surface as the level set of a higher dimensional function, and solve the surface equations in a fixed Cartesian coordinate system using this new embedding function. The equations are then both intrinsic to the surface and defined in the embedding space. This approach thereby eliminates the need for performing complicated and inaccurate computations on triangulated surfaces, as is commonly done in the literature. We describe the framework and present examples in computer graphics and image processing applications, including texture synthesis, flow field visualization, as well as image and vector field intrinsic regularization for data defined on 3D surfaces
  • Keywords
    computational geometry; computer graphics; differential geometry; image representation; image sequences; image texture; partial differential equations; variational techniques; vectors; 3D surfaces; PDE; computer graphics; embedding function; fixed Cartesian coordinate system; flow field visualization; image processing; implicit surfaces; level set; partial differential equations; scalar-valued data; surface equations; surface representation; texture synthesis; variational problems; vector field intrinsic regularization; vector-valued data; Application software; Computer graphics; Data visualization; Differential equations; Embedded computing; Image processing; Laplace equations; Partial differential equations; Physics; Surface texture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Variational and Level Set Methods in Computer Vision, 2001. Proceedings. IEEE Workshop on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7695-1278-X
  • Type

    conf

  • DOI
    10.1109/VLSM.2001.938899
  • Filename
    938899