Being biological tissues in nature, all biometric traits undergo aging. Aging has profound effects on facial biometrics as it causes change in shape and texture. However, aging remain an under-studied problem in comparison to facial variations due to pose, illumination and expression changes.
A commonly adopted solution in the state-of-the-art is the virtual template synthesis for aging and de-aging transformations involving complex 3D modelling techniques. These methods are also prone to estimation errors in the synthesis. Another viable solution is to continuously adapt the template to the temporal
variation (aging) of the query data. Though efficacy of template update procedures has been proven for expression, lightning and pose variations, the use of template update for facial aging has not received much attention so far. This paper investigates the use of template update procedures for temporal variance
due to the facial aging process. Experimental evaluations on FGNET and MORPH aging database using commercial VeriLook face recognition engine demonstrate that continuous template updating is an effective and simple way to adapt to variations due to the aging process.
