C.M. Hill, C.J. Solomon, and S.J. Gibson (UK)
Aging, PCA, subspace
The ability to accurately age a human face has a significant potential application in Forensic Science, in particular for attempts to locate and identify missing children. There may also be an application in the field of facial synthesis with an emphasis on facial composite construction [1]. With these uses in mind, a new technique for aging a face in an image has been developed. The technique uses Principal Components Analysis (PCA) on an equal number of male and female faces of different ages to produce sep arate models in shape and texture. The aging direction was identified for each gender subspace and in-sample male and female faces aged by 20 years according to their Euclidean distance from each aging axis. An out-of-sample male face was also aged. In addition, aging was computed for the male and female faces by producing a model trained only on the appropriate gender sample and using multiples of the aging axis in order to age the face.
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