Abstract
One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We review some of the representative face aging modeling techniques, especially the 3D aging modeling technique. The 3D aging modeling technique adapts view invariant 3D face models to the given 2D face aging database. The evaluation results of the 3D aging modeling technique on three different databases (FG-NET, MORPH and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine showed its effectiveness in handling the aging effect.
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Park, U., Jain, A.K. (2011). Face Aging Modeling. In: Li, S., Jain, A. (eds) Handbook of Face Recognition. Springer, London. https://doi.org/10.1007/978-0-85729-932-1_10
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DOI: https://doi.org/10.1007/978-0-85729-932-1_10
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