Automatic Pain Intensity Estimation using Heteroscedastic Conditional Ordinal Random Fields

Ognjen Rudovic, Vladimir Pavlovic, Maja Pantic

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    46 Citations (Scopus)
    39 Downloads (Pure)


    Automatic pain intensity estimation from facial images is challenging mainly because of high variability in subject-specific pain expressiveness. This heterogeneity in the subjects causes their facial appearance to vary significantly when experiencing the same pain level. The standard classification methods (e.g., SVMs) do not provide a principled way of accounting for this heterogeneity. To this end, we propose the heteroscedastic Conditional Ordinal Random Field (CORF) model for automatic estimation of pain intensity. This model generalizes the CORF framework for modeling sequences of ordinal variables, by adapting it for heteroscedasticity. This is attained by allowing the variance in the ordinal probit model in the CORF to change depending on the input features, resulting in the model able to adapt to the pain expressiveness level specific to each subject. Our experimental results on the UNBC Shoulder Pain Database show that modeling heterogeneity in the subjects with the framework of CORFs improves the pain intensity estimation attained by the standard CORF model, and the other commonly used classification models.
    Original languageEnglish
    Title of host publicationAdvances in Visual Computing
    Subtitle of host publication9th International Symposium, ISVC 2013, Rethymnon, Crete, Greece, July 29-31, 2013. Proceedings
    EditorsSabine Coquillart, Xun Luo, Min Chen, David Gotz
    Place of PublicationBerlin
    Number of pages10
    ISBN (Print)978-3-642-41938-6
    Publication statusPublished - Jul 2013
    Event9th International Symposium on Visual Computing, ISVC 2013 - Rethymnon, Crete, Greece
    Duration: 29 Jul 201331 Jul 2013
    Conference number: 9

    Publication series

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


    Conference9th International Symposium on Visual Computing, ISVC 2013
    Abbreviated titleISVC
    CityRethymnon, Crete


    • EWI-24340
    • METIS-302660
    • IR-89371
    • HMI-HF: Human Factors

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