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Abstract. In this paper a completely automatic face recognition system is presented. The system is inspired by the elastic bunch graph method, but the fiducial point localization is completely different and does not require any operator intervention. Each fiducial point is characterized applying a bank of filters which extracts the peculiar texture around it (jet). The performances of the steerable Gaussian first derivatives basis filters are compared to the ones of the Gabor wavelet transform, showing similar results when images of faces in approximately the same pose are compared.

In this paper a completely automatic face recognition system is presented. It consists of two main modules: in the first, the facial fiducial points are localized, and in the second the face is characterized applying a bank of Gabor filters in correspondence to the found fiducial points. This method is an evolution of the one we have presented in [2]: the fiducial point estimation is more efficient and self-correcting, and the face characterization modified.

Abstract. In this paper a fully automatic face verification system is presented. A face is characterized by a vector (jet) of coefficients determined applying a bank of Gabor filters in correspondence to 19 facial fiducial points automatically localized. The identity claimed by a subject is accepted or rejected depending on a similarity measure computed among the jet characterizing the subject, and the ones corresponding to the subjects in the gallery. The performance of the system has been quantified according to the Lausanne evaluation protocol for authentication.

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