• DocumentCode
    672595
  • Title

    Mouth covered detection for yawn

  • Author

    Ibrahim, M.M. ; Soroghan, John S. ; Petropoulakis, Lykourgos

  • Author_Institution
    Electron. & Electr. Eng. Dept., Univ. of Strathclyde, Glasgow, UK
  • fYear
    2013
  • fDate
    8-10 Oct. 2013
  • Firstpage
    89
  • Lastpage
    94
  • Abstract
    Yawn is one of the common fatigue sign phenomena. The common technique to detect yawn is based upon the measurement of mouth opening. However, the spontaneous human action to cover the mouth during yawn can prevent such measurements. This paper presents a new technique to detect the covered mouth by employing the Local Binary Pattern (LBP) features. Subsequently, the facial distortions during the yawn process are identified by measuring the changes of wrinkles using Sobel edges detector. In this research the Strathclyde Facial Fatigue (SFF) database that contains genuine fatigue signs is used for training, testing and evaluation of the developed algorithms. This database was created from sleep deprivation experiments that involved twenty participants.
  • Keywords
    edge detection; face recognition; sleep; LBP features; SFF database; Sobel edge detector; Strathclyde Facial Fatigue database; facial distortions; fatigue sign phenomena; fatigue signs; local binary pattern features; mouth covered detection; mouth opening measurement; sleep deprivation experiments; spontaneous human action; wrinkles; yawn detection; Artificial neural networks; Distortion measurement; Yawn; database; destortion detection; fatigue; mouth covered;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal and Image Processing Applications (ICSIPA), 2013 IEEE International Conference on
  • Conference_Location
    Melaka
  • Print_ISBN
    978-1-4799-0267-5
  • Type

    conf

  • DOI
    10.1109/ICSIPA.2013.6707983
  • Filename
    6707983