“An Improved Rendering Technique for Active-Appearance-Model-Based Automated Age Progression” by Patterson, Sethuram and Ricanek

  • ©Eric Patterson, Amrutha Sethuram, and Karl Ricanek



Entry Number: 20


    An Improved Rendering Technique for Active-Appearance-Model-Based Automated Age Progression



    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.


    1. Patterson, E., Sethuram, A., Ricanek K., and Bingham, F. Improvements in Active-Appearance-Model-Based Synthetic Age Progression for Adult Aging. Proceedings of the IEEE Conference on Biometrics: Theory, Applications, and Systems, Washington, D.C., 2009.
    2. Lanitis, A., Taylor, C. J., and Cootes, T. F. Toward Automatic Simulation of Aging Effects on Face Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(4), 2002.
    3. Matthews, I. and Baker, S. Active Appearance Models Revisited. International Journal of Computer Vision, Vol. 60, 2004, pp. 135–164.


    This work was partially funded by research contract from the Army Research Laboratory and Federal Bureau of Investigation’s CJIS division.


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