A Study of Face Recognition Performance Under Aging
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Abstract
In the face recognition technology into important identity applications, it is imperative that the ef-fects of facial aging on face recognition performance are thoroughly understood. As face recognition systems evolve and improve, they should be periodically re-evaluated on large-scale face datasets. In our study, we evaluate the performance of two state-of-the-art commer-cial off the shelf (COTS) face recognition systems on two large-scale longitudinal datasets of mugshots of repeat of-fenders. We fit multi-level statistical models to genuine comparison scores (simi-larity between images of the same face) from the two COTS face matchers.
References
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