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The 3D face recognition aims to reduce the flaws that present the bi-dimensional based methods. This kind of recognizing method has the advantage to be invariant to illumination changes because the faces are represented as a points cloud or a 3D mesh where the most remarkable is the geometry. In this research work we present a recognizing system that uses a set of 3D shape descriptors that were selected from a relevance analysis by using the Fisher coefficients in different regions of face which are part of an anthropometric face model. A set of experiments for face, expression, and gender recognition and were performed using the relevance analysis proposed. The obtained results show that the relevance analysis offers an increasing of the performance in face recognition system.

Reconocimiento de rostros y gestos faciales mediante un análisis de relevancia con imágenes 3D