Age classification from facial images

    Authors

    Y. H. Kwon;N. D. Lobo

    Comments

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    Abbreviated Journal Title

    Comput. Vis. Image Underst.

    Keywords

    TEMPLATES; FACES; Computer Science, Artificial Intelligence; Engineering, Electrical &; Electronic

    Abstract

    This paper presents a theory and practical computations for visual age classification from facial images. Currently, the theory has only been implemented to classify input images into one of three age-groups: babies, young adults, and senior adults. The computations are based on cranio-facial development theory and skin wrinkle analysis. In the implementation, primary features of the face are found first, followed by secondary feature analysis. The primary features are the eyes, nose, mouth, chin, virtual-top of the head and the sides of the face. From these features, ratios that distinguish babies from young adults and seniors are computed. In secondary feature analysis, a wrinkle geography map is used to guide the detection and measurement of wrinkles. The wrinkle index computed is sufficient to distinguish seniors from young adults and babies. A combination rule for the ratios and the wrinkle index thus permits categorization of a face into one of three classes. Results using real images are presented. This is the first work involving age classification, and the first work that successfully extracts and uses natural wrinkles. It is also a successful demonstration that facial features are sufficient for a classification task, a finding that is important to the debate about what are appropriate representations for facial analysis. (C) 1999 Academic Press.

    Journal Title

    Computer Vision and Image Understanding

    Volume

    74

    Issue/Number

    1

    Publication Date

    1-1-1999

    Document Type

    Article

    Language

    English

    First Page

    1

    Last Page

    21

    WOS Identifier

    WOS:000079611200001

    ISSN

    1077-3142

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