Toward automatic simulation of aging effects on face images
Lanitis, A.
Taylor, C.J.
Cootes, T.F.
Dept. of Comput. Sci., Cyprus Coll., Nicosia;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Apr 2002
Volume: 24,
Issue: 4
On page(s): 442-455
ISSN: 0162-8828
References Cited: 28
CODEN: ITPIDJ
INSPEC Accession Number: 7234900
Digital Object Identifier: 10.1109/34.993553
Current Version Published: 2002-08-07
Abstract
The process of aging causes significant alterations in the facial
appearance of individuals. When compared with other sources of variation
in face images, appearance variation due to aging displays some unique
characteristics. Changes in facial appearance due to aging can even
affect discriminatory facial features, resulting in deterioration of the
ability of humans and machines to identify aged individuals. We describe
how the effects of aging on facial appearance can be explained using
learned age transformations and present experimental results to show
that reasonably accurate estimates of age can be made for unseen images.
We also show that we can improve our results by taking into account the
fact that different individuals age in different ways and by considering
the effect of lifestyle. Our proposed framework can be used for
simulating aging effects on new face images in order to predict how an
individual might look like in the future or how he/she used to look in
the past. The methodology presented has also been used for designing a
face recognition system, robust to aging variation. In this context, the
perceived age of the subjects in the training and test images is
normalized before the training and classification procedure so that
aging variation is eliminated. Experimental results demonstrate that,
when age normalization is used, the performance of our face recognition
system can be improved
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