• DocumentCode
    2786300
  • Title

    A new approach for extracting shape from texture

  • Author

    Cohen, Fernand S. ; Patel, Maqbool A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA
  • fYear
    1990
  • fDate
    5-7 Sep 1990
  • Firstpage
    204
  • Abstract
    A novel way of modeling images that result from the projective distortions of homogeneous textures laid on illuminated 3D surfaces, as they are seen by a camera is presented. A Gaussian Markov random field (GMRF) is used for modeling the homogeneous planar parent texture. The projective distortions of the parent texture is a 2D Gaussian random field described by a probability distribution which is an explicit function of the parameters of the GMRF homogeneous texture model, the surface shape, and the camera model (orthographic or pinhole). The basic modeling concepts are used in extracting shape information from texture. Shape parameter estimation is posed as a maximum-likelihood estimation (MLE) problem
  • Keywords
    Markov processes; computational geometry; parameter estimation; pattern recognition; probability; Gaussian Markov random field; camera model; homogeneous textures; illuminated 3D surfaces; image modelling; maximum-likelihood estimation; orthographic camera; parameter estimation; pinhole camera; probability distribution; rojective distortions; shape extraction; surface shape; Cameras; Data mining; Light sources; Markov random fields; Maximum likelihood estimation; Parameter estimation; Probability distribution; Reflectivity; Shape; Surface texture;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control, 1990. Proceedings., 5th IEEE International Symposium on
  • Conference_Location
    Philadelphia, PA
  • ISSN
    2158-9860
  • Print_ISBN
    0-8186-2108-7
  • Type

    conf

  • DOI
    10.1109/ISIC.1990.128459
  • Filename
    128459