Personalised modelling of facial action unit intensity

Shuang Yang, Ognjen Rudovic, Vladimir Pavlovic, Maja Pantic

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

    15 Citations (Scopus)
    11 Downloads (Pure)


    Facial expressions depend greatly on facial morphology and expressiveness of the observed person. Recent studies have shown great improvement of the personalized over non-personalized models in variety of facial expression related tasks, such as face and emotion recognition. However, in the context of facial action unit (AU) intensity estimation, personalized modeling has been scarcely investigated. In this paper, we propose a two-step approach for personalized modeling of facial AU intensity from spontaneously displayed facial expressions. In the first step, we perform facial feature decomposition using the proposed matrix decomposition algorithm that separates the person’s identity from facial expression. These two are then jointly modeled using the framework of Conditional Ordinal Random Fields, resulting in a personalized model for intensity estimation of AUs. Our experimental results show that the proposed personalized model largely outperforms non-personalized models for intensity estimation of AUs.
    Original languageEnglish
    Title of host publicationAdvances in Visual Computing
    Subtitle of host publication10th International Symposium, ISVC 2014, Las Vegas, NV, USA, December 8-10, 2014, Proceedings
    EditorsGeorge Bebis, Richard Boyle, Bahram Parvin, Darko Koracin
    Place of PublicationCham
    Number of pages13
    VolumePart II
    ISBN (Electronic)978-3-319-14364-4
    ISBN (Print)978-3-319-14363-7
    Publication statusPublished - Dec 2014
    Event10th International Symposium on Visual Computing, ISVC 2014 - Las Vegas, United States
    Duration: 8 Dec 201410 Dec 2014
    Conference number: 10

    Publication series

    NameLecture Notes in Computer Science
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference10th International Symposium on Visual Computing, ISVC 2014
    Abbreviated titleISVC
    Country/TerritoryUnited States
    CityLas Vegas


    • HMI-HF: Human Factors
    • EWI-25809
    • EC Grant Agreement nr.: FP7/611153
    • EC Grant Agreement nr.: FP7/2007-2013
    • METIS-309928
    • IR-94676


    Dive into the research topics of 'Personalised modelling of facial action unit intensity'. Together they form a unique fingerprint.

    Cite this