• DocumentCode
    3192512
  • Title

    Curvature consistency improves local shading analysis

  • Author

    Ferrie, F.P. ; Lagarde, J.

  • Author_Institution
    Comput. Vision & Robotics Lab., McGill Univ., Montreal, Que., Canada
  • Volume
    i
  • fYear
    1990
  • fDate
    16-21 Jun 1990
  • Firstpage
    70
  • Abstract
    The authors describe how a surface reconstruction algorithm based on minimizing the variation of surface curvature can be used to stabilize and correct the results of local shading analysis. The approach is viewpoint independent and applicable to any process that can provide estimates of local surface orientation. The assumptions used in formulating the minimization are derived from standard differential geometry. When applied as a second stage of processing after local shading analysis, the algorithm can recover a close approximation of the true surface orientation under realistic assumptions about image noise. Results are presented that show the performance of the algorithm on synthetic and real data. In particular, they demonstrate how this form of reconstruction can compensate for some of the shape distortion incurred in local shading analysis
  • Keywords
    computerised pattern recognition; computerised picture processing; curvature consistency; curvature variation minimization; differential geometry; local shading analysis; local surface orientation; surface curvature; surface reconstruction; Computer vision; Geometry; Image analysis; Image reconstruction; Intelligent robots; Minimization methods; Noise shaping; Robustness; Shape; Surface reconstruction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1990. Proceedings., 10th International Conference on
  • Conference_Location
    Atlantic City, NJ
  • Print_ISBN
    0-8186-2062-5
  • Type

    conf

  • DOI
    10.1109/ICPR.1990.118067
  • Filename
    118067