• DocumentCode
    2643218
  • Title

    Geometric and photometric constraints for surface recovery

  • Author

    Lu, Jiping ; Little, Jim

  • Author_Institution
    Dept. of Comput. Sci., British Columbia Univ., Vancouver, BC, Canada
  • fYear
    1996
  • fDate
    18-20 Jun 1996
  • Firstpage
    694
  • Lastpage
    700
  • Abstract
    In this paper we present a novel approach to surface recovery from an image sequence of a rotating object. In this approach, the object is illuminated under a collinear light source (where the light source lies on or near the optical axis) and rotated on a controlled turntable. A wire-frame of 3D curves on the object surface is extracted by using shading and occluding contours in the image sequence. Then the whole object surface is recovered by interpolating the surface between curves on the wire-frame. The interpolation can be done by using geometric or photometric constraints. The photometric method uses shading information and is more powerful than geometric methods. The experimental results on real image sequence of matte and specular surfaces show that the technique is feasible and promising
  • Keywords
    computer vision; image sequences; interpolation; 3D curves; collinear light source; controlled turntable; geometric constraints; image sequence; interpolation; object surface; occluding contours; optical axis; photometric constraints; photometric method; rotating object; shading; shading information; surface recovery; Cameras; Computational intelligence; Data mining; Image sequences; Laboratories; Light sources; Photometry; Reflectivity; Shape; Stereo vision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1996. Proceedings CVPR '96, 1996 IEEE Computer Society Conference on
  • Conference_Location
    San Francisco, CA
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-7259-5
  • Type

    conf

  • DOI
    10.1109/CVPR.1996.517148
  • Filename
    517148