• DocumentCode
    2861810
  • Title

    Automatic Eye Detection and Its Validation

  • Author

    Wang, Peng ; Green, Matthew B. ; Ji, Qiang ; Wayman, James

  • Author_Institution
    Rensselaer Polytechnic Institute
  • fYear
    2005
  • fDate
    25-25 June 2005
  • Firstpage
    164
  • Lastpage
    164
  • Abstract
    The accuracy of face alignment affects the performance of a face recognition system. Since face alignment is usually conducted using eye positions, an accurate eye localization algorithm is therefore essential for accurate face recognition. In this paper, we first study the impact of eye locations on face recognition accuracy, and then introduce an automatic technique for eye detection. The performance of our automatic eye detection technique is subsequently validated using FRGC 1.0 database. The validation shows that our eye detector has an overall 94.5% eye detection rate, with the detected eyes very close to the manually provided eye positions. In addition, the face recognition performance based on the automatic eye detection is shown to be comparable to that of using manually given eye positions.
  • Keywords
    Computer errors; Databases; Detectors; Eyes; Face detection; Face recognition; Pixel; Principal component analysis; Robustness; Systems engineering and theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition - Workshops, 2005. CVPR Workshops. IEEE Computer Society Conference on
  • Conference_Location
    San Diego, CA, USA
  • ISSN
    1063-6919
  • Print_ISBN
    0-7695-2372-2
  • Type

    conf

  • DOI
    10.1109/CVPR.2005.570
  • Filename
    1565482