• DocumentCode
    1632572
  • Title

    Infant hungry recognition based on neural network and AR model

  • Author

    Mansor, M.N. ; Rejab, M.N. ; Syam, S.H.-F. ; Syam, A.H.-F.

  • Author_Institution
    Sch. of Mechatron. Eng., Univ. Malaysia Perlis, Kangar, Malaysia
  • Volume
    2
  • fYear
    2012
  • Firstpage
    368
  • Lastpage
    370
  • Abstract
    To deal with nonverbal life was a difficult task. To study their behaviour without knowing what their needs is another crucial issue. A lot of researches have been rapidly investigated. Thus, in this paper we proudly proposed a system to determine the hungry infant based on their facial expression. A Haar Cascade face detection method was implemented. Autoregressive Model (AR) was employed for the coefficient extraction. Some other statistical methods were used as the feature extraction. Finally Neural network (NN) with 93.78% accuracy was accepted.
  • Keywords
    emotion recognition; face recognition; AR model; Haar Cascade face detection method; autoregressive model; facial expression; infant hungry recognition; neural network; nonverbal life; Educational institutions; Feature extraction; Mathematical model; Neural networks; Pediatrics; Training; Video recording; Autoregressive Model (AR); Detection of facial changes; NICU patient; Neural Network classifier;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4673-2465-6
  • Type

    conf

  • DOI
    10.1109/MSNA.2012.6324596
  • Filename
    6324596