• DocumentCode
    3491522
  • Title

    Real time face recognition system using autoassociative neural network models

  • Author

    Palanivel, S. ; Venkatesh, B.S. ; Yegnanarayana, B.

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Indian Inst. of Technol. Madras, Chennai, India
  • Volume
    2
  • fYear
    2003
  • fDate
    6-10 April 2003
  • Abstract
    This paper proposes a novel method for video-based real time face recognition. The proposed method uses motion information to detect the face region, and the region is processed in YCrCb color space to determine the location of the eyes. The system extracts only the gray level features relative to the location of the eyes. autoassociative neural network (AANN) model is used to capture the distribution of the extracted gray level features. Experimental results show that the proposed system gives an average recognition rate of 99% in real time for 25 subjects. The performance of the proposed method is invariant to size, tilt of the face and is also not sensitive to natural lighting conditions.
  • Keywords
    face recognition; image colour analysis; neural nets; real-time systems; video signal processing; AANN model; autoassociative neural network models; automatic human faces recognition; average recognition rate; color space; eyes location; gray level features extraction; natural lighting conditions; video-based real time face recognition; Data mining; Eyes; Face detection; Face recognition; Head; Neural networks; Pixel; Real time systems; Skin; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7663-3
  • Type

    conf

  • DOI
    10.1109/ICASSP.2003.1202496
  • Filename
    1202496