Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter

Stefanos Zafeiriou, Maja Pantic

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

    6 Citations (Scopus)

    Abstract

    In this paper we explore the use of dense facial deformation in spontaneous smile/laughter as a biometric signature. The facial deformation is calculated between a neutral image (as neutral we define the least expressive image of the smile/laughter episode) and the apex of spontaneous smile/laughter (as apex we define the frame of the maximum facial change/deformation) and its complex representation is regarded. Subsequently, supervised and unsupervised complex dimensionality reduction techniques, namely the complex Principal Component Analysis (PCA) and the complex Linear Discriminant Analysis (LDA), are applied at the complex vector fields for feature extraction. We demonstrate the efficacy of facial deformation as a mean for person verification in a database of spontaneous smiles/laughters.
    Original languageUndefined
    Title of host publicationIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011)
    Place of PublicationUSA
    PublisherIEEE Computer Society
    Pages13-19
    Number of pages7
    ISBN (Print)978-1-4577-0529-8
    DOIs
    Publication statusPublished - Jun 2011

    Publication series

    Name
    PublisherIEEE Computer Society

    Keywords

    • METIS-285027
    • IR-79433
    • Face Recognition
    • Databases
    • Humans
    • EWI-21325
    • Principal component analysis
    • Speech
    • Training
    • EC Grant Agreement nr.: ERC/203143
    • HMI-MI: MULTIMODAL INTERACTIONS
    • Vectors

    Cite this

    Zafeiriou, S., & Pantic, M. (2011). Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011) (pp. 13-19). USA: IEEE Computer Society. https://doi.org/10.1109/CVPRW.2011.5981832
    Zafeiriou, Stefanos ; Pantic, Maja. / Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter. IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011). USA : IEEE Computer Society, 2011. pp. 13-19
    @inproceedings{f9fd96a9cd6940f28cbfb04fdc2ff504,
    title = "Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter",
    abstract = "In this paper we explore the use of dense facial deformation in spontaneous smile/laughter as a biometric signature. The facial deformation is calculated between a neutral image (as neutral we define the least expressive image of the smile/laughter episode) and the apex of spontaneous smile/laughter (as apex we define the frame of the maximum facial change/deformation) and its complex representation is regarded. Subsequently, supervised and unsupervised complex dimensionality reduction techniques, namely the complex Principal Component Analysis (PCA) and the complex Linear Discriminant Analysis (LDA), are applied at the complex vector fields for feature extraction. We demonstrate the efficacy of facial deformation as a mean for person verification in a database of spontaneous smiles/laughters.",
    keywords = "METIS-285027, IR-79433, Face Recognition, Databases, Humans, EWI-21325, Principal component analysis, Speech, Training, EC Grant Agreement nr.: ERC/203143, HMI-MI: MULTIMODAL INTERACTIONS, Vectors",
    author = "Stefanos Zafeiriou and Maja Pantic",
    note = "10.1109/CVPRW.2011.5981832",
    year = "2011",
    month = "6",
    doi = "10.1109/CVPRW.2011.5981832",
    language = "Undefined",
    isbn = "978-1-4577-0529-8",
    publisher = "IEEE Computer Society",
    pages = "13--19",
    booktitle = "IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011)",
    address = "United States",

    }

    Zafeiriou, S & Pantic, M 2011, Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter. in IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011). IEEE Computer Society, USA, pp. 13-19. https://doi.org/10.1109/CVPRW.2011.5981832

    Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter. / Zafeiriou, Stefanos; Pantic, Maja.

    IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011). USA : IEEE Computer Society, 2011. p. 13-19.

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

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    AU - Pantic, Maja

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    PY - 2011/6

    Y1 - 2011/6

    N2 - In this paper we explore the use of dense facial deformation in spontaneous smile/laughter as a biometric signature. The facial deformation is calculated between a neutral image (as neutral we define the least expressive image of the smile/laughter episode) and the apex of spontaneous smile/laughter (as apex we define the frame of the maximum facial change/deformation) and its complex representation is regarded. Subsequently, supervised and unsupervised complex dimensionality reduction techniques, namely the complex Principal Component Analysis (PCA) and the complex Linear Discriminant Analysis (LDA), are applied at the complex vector fields for feature extraction. We demonstrate the efficacy of facial deformation as a mean for person verification in a database of spontaneous smiles/laughters.

    AB - In this paper we explore the use of dense facial deformation in spontaneous smile/laughter as a biometric signature. The facial deformation is calculated between a neutral image (as neutral we define the least expressive image of the smile/laughter episode) and the apex of spontaneous smile/laughter (as apex we define the frame of the maximum facial change/deformation) and its complex representation is regarded. Subsequently, supervised and unsupervised complex dimensionality reduction techniques, namely the complex Principal Component Analysis (PCA) and the complex Linear Discriminant Analysis (LDA), are applied at the complex vector fields for feature extraction. We demonstrate the efficacy of facial deformation as a mean for person verification in a database of spontaneous smiles/laughters.

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    KW - IR-79433

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    KW - Databases

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    KW - EWI-21325

    KW - Principal component analysis

    KW - Speech

    KW - Training

    KW - EC Grant Agreement nr.: ERC/203143

    KW - HMI-MI: MULTIMODAL INTERACTIONS

    KW - Vectors

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    Zafeiriou S, Pantic M. Facial Behaviometrics: the Case of Facial Deformation in Spontenaous Smile/Laughter. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W 2011). USA: IEEE Computer Society. 2011. p. 13-19 https://doi.org/10.1109/CVPRW.2011.5981832