Robust face recognition using automatic age normalization

A large number of automatic face recognition systems have been reported in the literature. Many of them are robust to within class appearance variation of subjects such as variation in expression, lighting and pose. However, most of the face identification systems developed, are sensitive to changes in the age of individuals. In this paper we demonstrate that automatic age simulation techniques can be used for designing face recognition systems, robust to ageing variation. In this context, the perceived age of the subjects in the training and test images is modified before the training and classification procedures, so that ageing variation is eliminated. Experimental results demonstrate that the performance of our face recognition system can be improved significantly, when this approach is adopted.