• DocumentCode
    624638
  • Title

    The driver fatigue monitoring system based on face recognition technology

  • Author

    Xiao-qing Luo ; Rong Hu ; Tian-e Fan

  • Author_Institution
    Coll. of Sci. & Technol., Nanchang Univ., Nanchang, China
  • fYear
    2013
  • fDate
    9-11 June 2013
  • Firstpage
    384
  • Lastpage
    388
  • Abstract
    This paper uses different algorithms, which are called AdaBoost algorithm and the difference between infrared frames algorithm, to locate the precise position of the eyes in different light environment of driving. We identify the eye´s status by extracting the characteristic parameters of eyes and detect fatigue based on the method of PERCLOS. At the same time, tfurther test the driver´s fatigue, we use the Local Binary Patter (LBP) algorithm to detect the yawning as an aided detection. The results of the experiment show that algorithm ensures the accuracy of the system and it can achieve the requirement of non contact type, different lighting conditions and real-time detection.
  • Keywords
    driver information systems; face recognition; fatigue; learning (artificial intelligence); AdaBoost algorithm; PERCLOS method; driver fatigue monitoring system; eye detection; face recognition technology; fatigue detection; infrared frames algorithm; lighting conditions; local binary pattern algorithm; real-time detection; Eyelids; Face; Fatigue; Lighting; Monitoring; Mouth; Vehicles; AdaBoost; Driver fatigue; Eye detection; PERCLOS; Yawning detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Information Processing (ICICIP), 2013 Fourth International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-6248-1
  • Type

    conf

  • DOI
    10.1109/ICICIP.2013.6568102
  • Filename
    6568102