• DocumentCode
    2308504
  • Title

    Ordinal and metric structure of smooth surfaces from parallax

  • Author

    Baratoff, Gregory

  • Author_Institution
    Comput. Vision Lab., Maryland Univ., College Park, MD, USA
  • Volume
    1
  • fYear
    1996
  • fDate
    25-29 Aug 1996
  • Firstpage
    275
  • Abstract
    The work presented in this paper is a first attempt at evaluating an ordinal representation for the local shape of smooth surface patches. To this end we investigate the reliability of estimating the tilt and slant components of the local surface orientation from binocular parallax. This is of interest because parallax is a commonly used cue, but has not been evaluated as to its susceptibility to image measurement errors. Our theoretical sensitivity analysis shows that the tilt is less sensitive than the slant to errors in the estimation of the viewing geometry, but that image measurement errors affect both slant and tilt seriously. In view of these results, it can not be claimed that the tilt is more reliably estimated from parallax than the slant. Despite the discovered sensitivity to image measurement errors, the tilt remains a very useful piece of information, in that it still specifies partial ordinal relations even when substantially degraded. We present a simple and efficient method to keep track of such partial information during all ongoing computation
  • Keywords
    computational geometry; error analysis; feature extraction; image reconstruction; image representation; sensitivity analysis; binocular parallax; image measurement errors; local shape; metric structure; ordinal representation; ordinal structure; partial information; sensitivity analysis; slant component; smooth surface patches; tilt component; viewing geometry; Automation; Computer vision; Contracts; Degradation; Educational institutions; Geometry; Image analysis; Laboratories; Shape; Surface topography;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1996., Proceedings of the 13th International Conference on
  • Conference_Location
    Vienna
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-7282-X
  • Type

    conf

  • DOI
    10.1109/ICPR.1996.546033
  • Filename
    546033