Automatic, Dimensional and Continuous Emotion Recognition

Hatice Gunes, J. Vallverdú (Editor), Maja Pantic

    Research output: Contribution to journalArticleAcademicpeer-review

    Abstract

    Recognition and analysis of human emotions have attracted a lot of interest in the past two decades and have been researched extensively in neuroscience, psychology, cognitive sciences, and computer sciences. Most of the past research in machine analysis of human emotion has focused on recognition of prototypic expressions of six basic emotions based on data that has been posed on demand and acquired in laboratory settings. More recently, there has been a shift toward recognition of affective displays recorded in naturalistic settings as driven by real world applications. This shift in affective computing research is aimed toward subtle, continuous, and context-specific interpretations of affective displays recorded in real-world settings and toward combining multiple modalities for analysis and recognition of human emotion. Accordingly, this article explores recent advances in dimensional and continuous affect modelling, sensing, and automatic recognition from visual, audio, tactile, and brain-wave modalities.
    Original languageUndefined
    Pages (from-to)68-99
    Number of pages32
    JournalInternational journal of synthetic emotions
    Volume1
    Issue number1
    DOIs
    Publication statusPublished - Jan 2010

    Keywords

    • EC Grant Agreement nr.: FP7/211486
    • EWI-19464
    • HMI-MI: MULTIMODAL INTERACTIONS
    • Bodily Expression
    • Multi-modal Fusion
    • Continuous Emotion Recognition
    • Facial Expression
    • Emotional Acoustic and Bio-signals
    • METIS-277514
    • IR-75888
    • Dimensional Emotion Modelling

    Cite this

    Gunes, Hatice ; Vallverdú, J. (Editor) ; Pantic, Maja. / Automatic, Dimensional and Continuous Emotion Recognition. In: International journal of synthetic emotions. 2010 ; Vol. 1, No. 1. pp. 68-99.
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    title = "Automatic, Dimensional and Continuous Emotion Recognition",
    abstract = "Recognition and analysis of human emotions have attracted a lot of interest in the past two decades and have been researched extensively in neuroscience, psychology, cognitive sciences, and computer sciences. Most of the past research in machine analysis of human emotion has focused on recognition of prototypic expressions of six basic emotions based on data that has been posed on demand and acquired in laboratory settings. More recently, there has been a shift toward recognition of affective displays recorded in naturalistic settings as driven by real world applications. This shift in affective computing research is aimed toward subtle, continuous, and context-specific interpretations of affective displays recorded in real-world settings and toward combining multiple modalities for analysis and recognition of human emotion. Accordingly, this article explores recent advances in dimensional and continuous affect modelling, sensing, and automatic recognition from visual, audio, tactile, and brain-wave modalities.",
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    Automatic, Dimensional and Continuous Emotion Recognition. / Gunes, Hatice; Vallverdú, J. (Editor); Pantic, Maja.

    In: International journal of synthetic emotions, Vol. 1, No. 1, 01.2010, p. 68-99.

    Research output: Contribution to journalArticleAcademicpeer-review

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    AB - Recognition and analysis of human emotions have attracted a lot of interest in the past two decades and have been researched extensively in neuroscience, psychology, cognitive sciences, and computer sciences. Most of the past research in machine analysis of human emotion has focused on recognition of prototypic expressions of six basic emotions based on data that has been posed on demand and acquired in laboratory settings. More recently, there has been a shift toward recognition of affective displays recorded in naturalistic settings as driven by real world applications. This shift in affective computing research is aimed toward subtle, continuous, and context-specific interpretations of affective displays recorded in real-world settings and toward combining multiple modalities for analysis and recognition of human emotion. Accordingly, this article explores recent advances in dimensional and continuous affect modelling, sensing, and automatic recognition from visual, audio, tactile, and brain-wave modalities.

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    KW - Emotional Acoustic and Bio-signals

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    KW - IR-75888

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