• DocumentCode
    3348680
  • Title

    Face detection using support vector domain description in color images

  • Author

    Seo, Jin ; Ko, Hanseok

  • Author_Institution
    Dept. of Electron. & Comput. Eng., Korea Univ., Seoul, South Korea
  • Volume
    5
  • fYear
    2004
  • fDate
    17-21 May 2004
  • Abstract
    We present a system for face detection in color images using the support vector domain description (SVDD). Conventional face detection algorithms require a training procedure using both face and non-face images. In the SVDD, however, we employ only face images for training. We can detect faces in color images from the radius and center pairs of SVDD. We also use entropic threshold for extracting the facial feature and sliding window for improved performance while saving processing time. Experimental results indicate the effectiveness and efficiency of the proposed algorithm compared to the conventional PCA (principal component analysis) based methods.
  • Keywords
    entropy; face recognition; feature extraction; image colour analysis; learning (artificial intelligence); object detection; PCA; color images; entropic threshold; face detection; facial feature extraction; principal component analysis; sliding window; support vector domain description; training procedure; Algorithm design and analysis; Color; Face detection; Facial features; Lagrangian functions; Neural networks; Principal component analysis; Support vector machine classification; Support vector machines; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-8484-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.2004.1327214
  • Filename
    1327214