Toward Automatic Simulation of Aging Effects on Face Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
An approach of cluster validity on Gabor wavelet based adaptive face recognition
International Journal of Knowledge-based and Intelligent Engineering Systems - Extended papers selected from KES-2006
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Improvements in active appearance model based synthetic age progression for adult aging
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Use of cluster validity in designing adaptive gabor wavelet based face recognition
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
Modelling the time-variant covariates for gait recognition
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
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A large number of high performance 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 present experimental results to prove that the performance of automatic face recognition systems depends on the age difference of subjects between the training and test images. We also 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.