A Quadratic Deformation Model for Facial Expression Recognition

Mohammad Obaid, Mukundan, Roland Goecke, Billinghurst, Seichter

    Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

    1 Citation (Scopus)
    31 Downloads (Pure)


    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 publicationProceedings of the 2009 Digital Image Computing: Techniques and Applications
    EditorsHao Shi, Yanchun Zhang, Murk J Bottema, Brian C Lovell, Anthony J Maeder
    Place of PublicationAustralia
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Number of pages7
    ISBN (Print)9781424452972
    Publication statusPublished - 2009
    Event2009 Digital Image Computing: Techniques and Applications, DICTA 2009 - Melbourne, Australia
    Duration: 1 Dec 20093 Dec 2009


    Conference2009 Digital Image Computing: Techniques and Applications, DICTA 2009


    Dive into the research topics of 'A Quadratic Deformation Model for Facial Expression Recognition'. Together they form a unique fingerprint.

    Cite this