• DocumentCode
    2004556
  • Title

    Recognizing facial expressions: Computational models and humans

  • Author

    Shenoy, Aruna ; Davey, Neil ; Frank, Raphael

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Univ. of Bedfordshire, Luton, UK
  • fYear
    2013
  • fDate
    9-11 Sept. 2013
  • Firstpage
    191
  • Lastpage
    198
  • Abstract
    This paper discusses various biologically plausible computational models that recognize human facial expression and analyze them. Identifying facial expressions is a non trivial task for a human and is a key part of social interactions. However, it is not as simple as that for a computational system. Here we analyze six different universally accepted facial expressions for analysis with the aid of six biologically plausible computational models. There have been a limited number of studies comparing the performance of human subjects with computational models for facial expression recognition. This paper does a genuine attempt in making this comparison.
  • Keywords
    emotion recognition; face recognition; biologically plausible computational models; facial expression identification; human facial expression analysis; human facial expression recognition; social interactions; Computational modeling; Correlation; Face; Filter banks; Gabor filters; Principal component analysis; Support vector machines; Curvilinear Component Analysis; Facial expression; Gabor filters; Principal component analysis; Support Vector machines; human subjects;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence (UKCI), 2013 13th UK Workshop on
  • Conference_Location
    Guildford
  • Print_ISBN
    978-1-4799-1566-8
  • Type

    conf

  • DOI
    10.1109/UKCI.2013.6651305
  • Filename
    6651305