Toward Automatic Simulation of Aging Effects on Face Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active Appearance Models Revisited
International Journal of Computer Vision
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
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Age progression is the process of creating images that suggest how a person may appear in a certain amount of time based on the effects of the aging process. Traditionally these images have been created manually by forensic artists who use both art and science to guide how representations appear, whether drawn or photo-manipulated. Automated age-progression seeks to use algorithmic methods to create accurate images of how the individual in a photo could appear after aging effects. It is still a fairly young area of research, but one promising technique suggested so far has been to use parametrically driven face models such as Active Appearance Models to modify the face appearance in an image based on a data-driven model of face aging. These can be successful but tend to suffer from reconstructed texture artifacts.