• DocumentCode
    2533753
  • Title

    Photometric computation of the sign of Gaussian curvature using a curve-orientation invariant

  • Author

    Angelopoulou, Elli ; Wolff, Lawrence B.

  • Author_Institution
    Comput. Vision Lab., Johns Hopkins Univ., Baltimore, MD, USA
  • fYear
    1997
  • fDate
    17-19 Jun 1997
  • Firstpage
    432
  • Lastpage
    437
  • Abstract
    The authors compute the sign of Gaussian curvature using a purely geometric definition. Consider a point p on a smooth surface S and a closed curve γ on S which encloses p. The image of γ on the unit normal Gaussian sphere is a new curve β. The Gaussian curvature at p is defined as the ratio of the area enclosed by γ over the area enclosed by β as γ contracts to p. The sign of Gaussian curvature at p is determined by the relative orientations of the closed curves γ and β. They directly compare the relative orientation of two such curves from intensity data. They employ three unknown illumination conditions to create a photometric scatter plot. This plot is in one-to-one correspondence with the subset of the unit Gaussian sphere containing the mutually illuminated surface normals. This permits direct computation of the sign of Gaussian curvature without the recovery of surface normals. Their method is albedo invariant. They assume diffuse reflectance, but the nature of the diffuse reflectance can be general and unknown. Simulations, as well as empirical results, demonstrate the accuracy of the technique
  • Keywords
    computational geometry; computer vision; feature extraction; image classification; image segmentation; object recognition; photometry; reflectivity; simulation; Gaussian curvature sign; albedo invariant method; closed curve; curve-orientation invariant; diffuse reflectance; intensity data; mutually illuminated surface normals; photometric computation; photometric scatter plot; purely geometric definition; relative closed curve orientation; simulation; smooth surface; unit Gaussian sphere; unit normal Gaussian sphere; unknown illumination conditions; Computer science; Computer vision; Contracts; Gaussian processes; Laboratories; Lighting; Photometry; Reflectivity; Scattering; Surface fitting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1997. Proceedings., 1997 IEEE Computer Society Conference on
  • Conference_Location
    San Juan
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-7822-4
  • Type

    conf

  • DOI
    10.1109/CVPR.1997.609361
  • Filename
    609361