• DocumentCode
    2437627
  • Title

    Information theory and face detection

  • Author

    Lew, Michael S. ; Huijsmans, Nies

  • Author_Institution
    Dept. of Comput. Sci., Leiden Univ., Netherlands
  • Volume
    3
  • fYear
    1996
  • fDate
    25-29 Aug 1996
  • Firstpage
    601
  • Abstract
    Face detection in complex environments is an unsolved problem which has fundamental importance to face recognition, model based video coding, content based image retrieval, and human computer interaction. In this paper we model the face detection problem using information theory, and formulate information based measures for detecting faces by maximizing the feature class separation. The underlying principle is that search through an image can be viewed as a reduction of uncertainty in the classification of the image. The face detection algorithm is empirically compared using multiple test sets, which include four face databases from three universities
  • Keywords
    Markov processes; face recognition; feature extraction; image classification; image matching; information theory; maximum likelihood estimation; Markov random fields; face databases; face detection; face recognition; feature class separation; image classification; information theory; maximum likelihood estimation; template matching; Content based retrieval; Face detection; Face recognition; Human computer interaction; Image databases; Image retrieval; Information theory; Spatial databases; Testing; Video coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1996., Proceedings of the 13th International Conference on
  • Conference_Location
    Vienna
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-7282-X
  • Type

    conf

  • DOI
    10.1109/ICPR.1996.547017
  • Filename
    547017