Facial action detection using block-based pyramid appearance descriptors

Bihan Jiang, Michel F. Valstar, Maja Pantic

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

    5 Citations (Scopus)
    60 Downloads (Pure)

    Abstract

    Facial expression is one of the most important non-verbal behavioural cues in social signals. Constructing an effective face representation from images is an essential step for successful facial behaviour analysis. Most existing face descriptors operate on the same scale, and do not leverage coarse v.s. fine methods such as image pyramids. In this work, we propose the sparse appearance descriptors Block-based Pyramid Local Binary Pattern (B-PLBP) and Block-based Pyramid Local Phase Quantisation (B-PLPQ). The effectiveness of our proposed descriptors is evaluated by a real-time facial action recognition system. The performance of B-PLBP and B-PLPQ is also compared with Block-based Local Binary Patterns (BLBP) and Block-based Local Phase Quantisation (B-LPQ) . The system proposed here enables detection a much larger range of facial behaviour by detecting 22 facial muscle actions (Action Units, AUs), which can be practically applied for social behaviour analysis and synthesis. Results show that our proposed descriptor B-PLPQ outperforms all other tested methods for the problem of FACS Action Unit analysis and that systems which utilise a pyramid representation outperform those that use basic appearance descriptors.
    Original languageUndefined
    Title of host publicationProceedings of the IEEE International Conference on Social Computing, SocialCom 2012
    Place of PublicationUSA
    PublisherIEEE Computer Society
    Pages429-434
    Number of pages6
    ISBN (Print)978-1-4673-5638-1
    DOIs
    Publication statusPublished - 3 Sep 2012
    EventASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012 - Amsterdam, Netherlands
    Duration: 3 Sep 20125 Sep 2012

    Publication series

    Name
    PublisherIEEE Computer Society

    Conference

    ConferenceASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012
    Abbreviated titleSocialCom/PASSAT
    CountryNetherlands
    CityAmsterdam
    Period3/09/125/09/12

    Keywords

    • EWI-22977
    • METIS-296264
    • IR-84564
    • HMI-MI: MULTIMODAL INTERACTIONS

    Cite this

    Jiang, B., Valstar, M. F., & Pantic, M. (2012). Facial action detection using block-based pyramid appearance descriptors. In Proceedings of the IEEE International Conference on Social Computing, SocialCom 2012 (pp. 429-434). USA: IEEE Computer Society. https://doi.org/10.1109/SocialCom-PASSAT.2012.69