• DocumentCode
    3251985
  • Title

    Modeling human visual object recognition

  • Author

    Edelman, Shimon ; Bulthoff, Heinrich H.

  • Author_Institution
    Dept. of Appl. Math. & Comput. Sci., Weizmann Inst. of Sci., Rehovot, Israel
  • Volume
    4
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    37
  • Abstract
    The topics discussed here are network models of object recognition; a computational theory of recognition; psychophysical support for a view-interpolation model: and an open issue, features of recognition. The authors survey a successful replication of central characteristics of performance in 3-D object recognition by a computational model based on interpolation among a number of stored views of each object. Network models of 3-D object recognition based on interpolation among specific stored views behave in several respects similarly to human observers in a number of recognition tasks. Even closer replication of human performance in recognition should be expected, once the issue of the features used to represent object views is resolved
  • Keywords
    brain models; image recognition; neural nets; visual perception; 3-D object recognition; object recognition; psychophysical support; view-interpolation model; visual object recognition; Biology computing; Computer networks; Computer science; Humans; Image recognition; Image resolution; Interpolation; Mathematical model; Mathematics; Object recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.227292
  • Filename
    227292