3D Facial morphometrics for syndrome delineation

    Research output: ThesisDoctoral Thesis

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    Abstract

    The human face conveys a wealth of information about the identity, biological sex, age and ethnic background. It also reveals the affects of neurodevelopmental disorders. Thus, facial morphometrics can be used for detection of neurodevelopmental disorders and human identification. In this thesis, 30 facial features have been used for gender classification and scoring, face recognition and syndrome delineation. In particular, the thesis addresses the relative significance of facial landmarks in modelling the sexual dimorphism, automation of facial landmarking and establishing dense correspondence between 30 faces. It proposes algorithms to solve these challenges and applies them to Psychology and Biology.
    Original languageEnglish
    QualificationDoctor of Philosophy
    Awarding Institution
    • The University of Western Australia
    Award date15 Dec 2016
    Publication statusUnpublished - 2016

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    Forensic Anthropology
    Automation
    Sex Characteristics
    Psychology
    Neurodevelopmental Disorders
    Facial Recognition

    Cite this

    @phdthesis{2c21b147544e4574b2b639553a091403,
    title = "3D Facial morphometrics for syndrome delineation",
    abstract = "The human face conveys a wealth of information about the identity, biological sex, age and ethnic background. It also reveals the affects of neurodevelopmental disorders. Thus, facial morphometrics can be used for detection of neurodevelopmental disorders and human identification. In this thesis, 30 facial features have been used for gender classification and scoring, face recognition and syndrome delineation. In particular, the thesis addresses the relative significance of facial landmarks in modelling the sexual dimorphism, automation of facial landmarking and establishing dense correspondence between 30 faces. It proposes algorithms to solve these challenges and applies them to Psychology and Biology.",
    keywords = "3D face, Morphometrics, ASD, Syndrome, Dense correspondence, Gender classification, Sexual dimorphism, Machine learning",
    author = "Gilani, {Syed Zulqarnain Ahmad}",
    year = "2016",
    language = "English",
    school = "The University of Western Australia",

    }

    Gilani, SZA 2016, '3D Facial morphometrics for syndrome delineation', Doctor of Philosophy, The University of Western Australia.

    3D Facial morphometrics for syndrome delineation. / Gilani, Syed Zulqarnain Ahmad.

    2016.

    Research output: ThesisDoctoral Thesis

    TY - THES

    T1 - 3D Facial morphometrics for syndrome delineation

    AU - Gilani, Syed Zulqarnain Ahmad

    PY - 2016

    Y1 - 2016

    N2 - The human face conveys a wealth of information about the identity, biological sex, age and ethnic background. It also reveals the affects of neurodevelopmental disorders. Thus, facial morphometrics can be used for detection of neurodevelopmental disorders and human identification. In this thesis, 30 facial features have been used for gender classification and scoring, face recognition and syndrome delineation. In particular, the thesis addresses the relative significance of facial landmarks in modelling the sexual dimorphism, automation of facial landmarking and establishing dense correspondence between 30 faces. It proposes algorithms to solve these challenges and applies them to Psychology and Biology.

    AB - The human face conveys a wealth of information about the identity, biological sex, age and ethnic background. It also reveals the affects of neurodevelopmental disorders. Thus, facial morphometrics can be used for detection of neurodevelopmental disorders and human identification. In this thesis, 30 facial features have been used for gender classification and scoring, face recognition and syndrome delineation. In particular, the thesis addresses the relative significance of facial landmarks in modelling the sexual dimorphism, automation of facial landmarking and establishing dense correspondence between 30 faces. It proposes algorithms to solve these challenges and applies them to Psychology and Biology.

    KW - 3D face

    KW - Morphometrics

    KW - ASD

    KW - Syndrome

    KW - Dense correspondence

    KW - Gender classification

    KW - Sexual dimorphism

    KW - Machine learning

    M3 - Doctoral Thesis

    ER -