• DocumentCode
    3282664
  • Title

    Drowsy driver detection system using eye blink patterns

  • Author

    Danisman, Taner ; Bilasco, Ian Marius ; Djeraba, Chabane ; Ihaddadene, Nacim

  • Author_Institution
    LIFL, Univ. Lille 1, Lille, France
  • fYear
    2010
  • fDate
    3-5 Oct. 2010
  • Firstpage
    230
  • Lastpage
    233
  • Abstract
    This paper presents an automatic drowsy driver monitoring and accident prevention system that is based on monitoring the changes in the eye blink duration. Our proposed method detects visual changes in eye locations using the proposed horizontal symmetry feature of the eyes. Our new method detects eye blinks via a standard webcam in real-time at 110fps for a 320×240 resolution. Experimental results in the JZU eye-blink database showed that the proposed system detects eye blinks with a 94% accuracy with a 1% false positive rate.
  • Keywords
    accident prevention; cameras; driver information systems; feature extraction; road safety; accident prevention system; automatic drowsy driver monitoring; drowsy driver detection system; eye blink pattern; webcam; Accuracy; Cameras; Computer vision; Databases; Driver circuits; Face; Real time systems; Eye blink detection; drowsiness detection; eye symmetry;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine and Web Intelligence (ICMWI), 2010 International Conference on
  • Conference_Location
    Algiers
  • Print_ISBN
    978-1-4244-8608-3
  • Type

    conf

  • DOI
    10.1109/ICMWI.2010.5648121
  • Filename
    5648121