• DocumentCode
    384334
  • Title

    Interactive visual pattern recognition

  • Author

    Nagy, George ; Zou, Jie

  • Author_Institution
    Dept. of Electr. Comput. & Syst. Eng., Rensselaer Polytech. Inst., Troy, NY, USA
  • Volume
    2
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    478
  • Abstract
    Computer Assisted Visual Interactive Recognition (CAVIAR) draws on sequential pattern recognition, image database, expert systems, pen computing, and digital camera technology. It is designed to recognize wildflowers and other families of similar objects more accurately than machine vision and faster than most laypersons. The novelty of the approach is that human perceptual ability is exploited through interaction with the image of the unknown object. The computer remembers the characteristics of all previously seen classes, suggests possible operator actions, and displays confidence scores based on already detected features. In one application, consisting of 80 test images of wildflowers, 10 laypersons averaged 80% recognition accuracy at 12 seconds per flower.
  • Keywords
    computer vision; expert systems; pattern recognition; visual databases; computer assisted visual interactive recognition; digital camera technology; expert systems; human perceptual ability; image database; interactive visual pattern recognition; machine vision; pen computing; sequential pattern recognition; Application software; Computer displays; Computer vision; Digital cameras; Expert systems; Humans; Image databases; Image recognition; Machine vision; Pattern recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2002. Proceedings. 16th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-1695-X
  • Type

    conf

  • DOI
    10.1109/ICPR.2002.1048342
  • Filename
    1048342