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Automatic face recognition with aging using the invariant features

In the field of automatic face recognition, transformations of facial features due to aging cause a problem. Due to small amounts of extracted features, the identity verification can be difficult. The feature-based methods that are present in the literature are still being developed, with unsatisfactory results caused by high rates of false matching. In this paper we present a new method of matching verification of SIFT extracted feature points, which uses both the positions and scales of feature points. By using this method and the SIFT descriptor, we develop an identity verification system robust to aged based facial features transformations. The application of our verification system in the FG-net database demonstrates our approach's performance. The experimental results show that if 16.66% false acceptance rate is admitted, 81.81% true matching rate is obtained.