A quadratic deformation model for facial expression recognition

M. Obaid*, R. Mukundany, R. Goeckezx, M. Billinghurst, H. Seichter

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    1 Citation (Scopus)

    Abstract

    In this paper, we propose a novel approach for recognizing facial expressions based on using an Active Appearance Model facial feature tracking system with the quadratic deformation model representations of facial expressions. Thirty seven Facial Feature points are tracked based on the MPEG-4 Facial Animation Parameters layout. The proposed approach relies on the Euclidean distance measures between the tracked feature points and the reference deformed facial feature points of the six main expressions (smile, sad, fear, disgust, surprise, and anger). An evaluation of 30 model subjects, selected randomly from the Cohn-Kanade Database, was carried out. Results show that the main six facial expressions can successfully be recognized with an overall recognition accuracy of 89%. The proposed approach yields to promising recognition rates and can be used in real time applications.

    Original languageEnglish
    Title of host publicationDICTA 2009 - Digital Image Computing
    Subtitle of host publicationTechniques and Applications
    Pages264-270
    Number of pages7
    DOIs
    Publication statusPublished - 2009
    EventDigital Image Computing: Techniques and Applications, DICTA 2009 - Melbourne, VIC, Australia
    Duration: 1 Dec 20093 Dec 2009

    Publication series

    NameDICTA 2009 - Digital Image Computing: Techniques and Applications

    Conference

    ConferenceDigital Image Computing: Techniques and Applications, DICTA 2009
    Country/TerritoryAustralia
    CityMelbourne, VIC
    Period1/12/093/12/09

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