Title
Age classification from facial images
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
ISSN
1077-3142
Recommended Citation
"Age classification from facial images" (1999). Faculty Bibliography 1990s. 2706.
https://stars.library.ucf.edu/facultybib1990/2706
Comments
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