• DocumentCode
    2476255
  • Title

    A hybrid technique for facial feature point detection

  • Author

    Gargesha, M. ; Panchanathan, S.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Arizona State Univ., Tempe, AZ, USA
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    134
  • Lastpage
    138
  • Abstract
    Existing techniques for facial feature point detection from color images include template matching, facial geometry and symmetry analysis, mathematical morphology, luminance and chrominance analysis, and PCA. However, these techniques are plagued by poor performance in the presence of scale variations. In this paper, a hybrid technique is proposed that employs a combination of the above approaches along with curvature analysis of the intensity surface of the face image in order to provide a superior performance with reduced computational complexity, even in the presence of scale variations
  • Keywords
    face recognition; feature extraction; image colour analysis; image matching; mathematical morphology; principal component analysis; PCA; chrominance analysis; color images; computational complexity reduction; curvature analysis; face image; facial feature point detection; facial geometry; hybrid technique; intensity surface; luminance analysis; mathematical morphology; performance; symmetry analysis; template matching; Computational complexity; Eyes; Face detection; Facial features; Image analysis; Image color analysis; Image edge detection; Nose; Performance analysis; Principal component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Analysis and Interpretation, 2002. Proceedings. Fifth IEEE Southwest Symposium on
  • Conference_Location
    Sante Fe, NM
  • Print_ISBN
    0-7695-1537-1
  • Type

    conf

  • DOI
    10.1109/IAI.2002.999905
  • Filename
    999905