Recent advances in face biometrics with Gabor wavelets: A review

In this paper we focus on the great outburst of Gabor-based methods for face biometrics occurred in the last few years. Analytical approaches rely on the representation of a face with the Gabor responses computed on specific landmarks, while holistic methods take into account the face as a whole. We explore the role played by Gabor wavelets in international competitions, such as FERET or BANCA, where Gabor algorithms ranked first above other methods. By means of the analysis of five quantifiable factors, we present a ranking of methods as a function of their goodness. An enhanced version of AdaBoost, a complex-valued Gabor representation and a Gabor adaptive downsampling method are the three algorithms that lead the ranking. We also show there is a global trend toward face recognition methods, as well as toward Gabor holistic algorithms, due to their higher success rates.

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