Binary pattern analysis for 3D facial action unit detection

Georgia Sandbach, Stefanos Zafeiriou, Maja Pantic

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    35 Citations (Scopus)
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    In this paper we propose new binary pattern features for use in the problem of 3D facial action unit (AU) detection. Two representations of 3D facial geometries are employed, the depth map and the Azimuthal Projection Distance Image (APDI). To these the traditional Local Binary Pattern is applied, along with Local Phase Quantisation, Gabor filters and Monogenic filters, followed by the binary pattern feature extraction method. Feature vectors are formed for each feature type through concatenation of histograms formed from the resulting binary numbers. Feature selection is then performed using a two-stage GentleBoost approach. Finally, we apply Support Vector Machines as classifiers for detection of each AU. This system is tested in two ways. First we perform 10-fold cross-validation on the Bosphorus database, and then we perform cross-database testing by training on this database and then testing on apex frames from the D3DFACS database, achieving promising results in both.
    Original languageUndefined
    Title of host publicationProceedings of the British Machine Vision Conference, BMVC 2012
    Place of PublicationUK
    PublisherBMVA Press
    Number of pages12
    ISBN (Print)1-901725-46-4
    Publication statusPublished - 3 Sep 2012
    EventBritish Machine Vision Conference, BMVC 2012 - Surrey, United Kingdom
    Duration: 3 Sep 20127 Sep 2012

    Publication series

    PublisherBMVA Press


    ConferenceBritish Machine Vision Conference, BMVC 2012
    Abbreviated titleBMVC
    Country/TerritoryUnited Kingdom
    Internet address


    • EWI-22975
    • METIS-296263
    • IR-84317

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