Aging face verification in score-age space using single reference image template

The influence of age progression on the performance of face verification systems is a challenging and largely open research problem. When only one reference and one test image per subject are available, in this paper we propose to manage the aging influence on the adult face verification system through a score-age stacking technique to find the global decision boundary which can change across the age progression. This allows for improved long-term class separation by introducing a parameterized decision boundary in the scores-age space using a biométrie template created by a single reference image. This new method, based on the concept of classifier stacking and age-dependent decision boundary, compares favorably with the conventional face verification approach, which uses age-independent decision threshold. Our experiments on the MORPH database show that the use of the proposed scheme allows for improving the verification performance of baseline system.