• DocumentCode
    3206436
  • Title

    Autonomous fixation

  • Author

    Taalebinezhaad, M. Ali

  • Author_Institution
    Artificial Intelligence Lab., MIT, Cambridge, MA, USA
  • fYear
    1992
  • fDate
    15-18 Jun 1992
  • Firstpage
    744
  • Lastpage
    747
  • Abstract
    The author previously introduced a direct method, called fixation, for the recovery of shape and motion in the general case that uses neither feature correspondence nor optical flow. Instead, it directly uses the spatio-temporal gradients of image brightness. The experimental results of applying some of the author´s fixation algorithms to a sequence of real images, where the motion is a combination of translation and rotation, are reported. Techniques for autonomous choice of parameters that result in good estimates for important motion parameters are described
  • Keywords
    image sequences; motion estimation; fixation algorithms; image brightness; motion; motion parameters; real images; shape; spatio-temporal gradients; Artificial intelligence; Brightness; Computer vision; Equations; Image motion analysis; Laboratories; Motion estimation; Optical computing; Shape; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
  • Conference_Location
    Champaign, IL
  • ISSN
    1063-6919
  • Print_ISBN
    0-8186-2855-3
  • Type

    conf

  • DOI
    10.1109/CVPR.1992.223184
  • Filename
    223184