• DocumentCode
    2585710
  • Title

    Learning 3D object recognition strategies

  • Author

    Draper, Bruce A. ; Riseman, Edward M.

  • Author_Institution
    Dept. of Comput. & Inf. Sci., Massachusetts Univ., Amherst, MA, USA
  • fYear
    1990
  • fDate
    4-7 Dec 1990
  • Firstpage
    320
  • Lastpage
    324
  • Abstract
    The problem of automatically learning knowledge-directed control strategies is considered. In particular, the authors address the problem of learning object-specific recognition strategies from object descriptions and sets of interpreted training images. A separate recognition strategy is developed for every object in the domain. The goal of each recognition strategy is to identify any and all instances of the object in an image, and give the 3-D position (relative to the camera) of each instance. The goal of the learning process is to build a strategy that minimizes the expected cost of recognition, subject to accuracy constraints imposed by the user
  • Keywords
    computer vision; computerised pattern recognition; computerised picture processing; knowledge based systems; learning systems; 3-D position; 3D object recognition strategies; accuracy constraints; automatic learning; camera; interpreted training images; knowledge-directed control strategies; object descriptions; Automatic control; Cameras; Computer vision; Contracts; Costs; Decision trees; Image recognition; Information science; Object recognition; Shape;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision, 1990. Proceedings, Third International Conference on
  • Conference_Location
    Osaka
  • Print_ISBN
    0-8186-2057-9
  • Type

    conf

  • DOI
    10.1109/ICCV.1990.139541
  • Filename
    139541