Neural network-based fuzzy observer with application to facial analysis

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Human facial wrinkles can be effectively utilized for facial analysis. It is not an easy task, however, to extract features of wrinkledness directly from a camera image of a human face. For one thing, it is difficult to construct appropriate mathematical models for wrinkle features. In this work, a fuzzy observer is proposed as a means of providing linguistic descriptions about the image of a human face with wrinkles. In the proposed observer, some well-defined classical image features and numerical information are transformed into fuzzy numbers. A feedforward multilayered artificial neural network (ANN) is employed for parameter adjustment of the fuzzy observer based on the available crisp-input fuzzy-output sample sets. An experiment is performed to demonstrate that the facial wrinkles can be indirectly estimated by the proposed fuzzy observer. (C) 2000 Elsevier Science B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2000-02
Language
English
Article Type
Article
Citation

PATTERN RECOGNITION LETTERS, v.21, no.2, pp.93 - 105

ISSN
0167-8655
URI
http://hdl.handle.net/10203/78021
Appears in Collection
EE-Journal Papers(저널논문)
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