• DocumentCode
    3023637
  • Title

    Authentic facial expression analysis

  • Author

    Sebe, Nicu ; Lew, Michael S. ; Cohen, Ira ; Sun, Yafei ; Gevers, Theo ; Huang, Thomas S.

  • Author_Institution
    Fac. of Sci., Amsterdam Univ., Netherlands
  • fYear
    2004
  • fDate
    17-19 May 2004
  • Firstpage
    517
  • Lastpage
    522
  • Abstract
    It is argued that for the computer to be able to interact with humans, it needs to havve the communication skills o humans. One of these skills is the ability to understand the emotional state of the person. The most expressive way humans display emotions is through facial expressions. In most facial expression systems and databases, the emotion data was collected by asking the subjects to perform a series of facial expressions. However, these directed or deliberate facial action tasks typically differ in appearance and timing from the authentic facial expressions induced through events in the normal environment of the subject. In this paper, we present our effort in creating an authentic facial expression database based on spontaneous emotions derived from the environment. Furthermore, we test and compare a wide range of classifiers from the machine learning literature that can be used for facial expression classification.
  • Keywords
    emotion recognition; image classification; learning (artificial intelligence); visual databases; authentic facial expression database; facial expression analysis; machine learning literature; Computer displays; Computer science; Face recognition; Feature extraction; Humans; Spatial databases; Sun; Testing; Timing; Tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on
  • Print_ISBN
    0-7695-2122-3
  • Type

    conf

  • DOI
    10.1109/AFGR.2004.1301585
  • Filename
    1301585