• DocumentCode
    2242932
  • Title

    Visual/Acoustic Emotion Recognition

  • Author

    Chen, Cheng-Yao ; Huang, Yue-Kai ; Cook, Perry

  • Author_Institution
    Dept. of Electr. Eng., Princeton Univ., NJ
  • fYear
    2005
  • fDate
    6-6 July 2005
  • Firstpage
    1468
  • Lastpage
    1471
  • Abstract
    To recognize and understand a person´s emotion has been known as one of the most important issue in human-computer interaction. In this paper, we present a multimodal system that supports emotion recognition from both visual and acoustic feature analysis. Our main achievement is that with this bimodal method, we can effectively extend the recognized emotion categories compared to when only visual or acoustic feature analysis works alone. We also show that by carefully cooperating bimodal features, the recognition precision of each emotion category will exceed the limit set up by the single modality, both visual and acoustic. Moreover, we believe our system is closer to real human perception and experience and hence will make emotion recognition closer to practical application in the future
  • Keywords
    acoustic signal processing; emotion recognition; feature extraction; human computer interaction; visual perception; acoustic emotion recognition; bimodal feature analysis; human perception; human-computer interaction; multimodal system; visual emotion recognition; Algorithm design and analysis; Computer science; Emotion recognition; Face recognition; Facial features; Feedback; Humans; Performance analysis; Robustness; Timing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2005. ICME 2005. IEEE International Conference on
  • Conference_Location
    Amsterdam
  • Print_ISBN
    0-7803-9331-7
  • Type

    conf

  • DOI
    10.1109/ICME.2005.1521709
  • Filename
    1521709