Performance evaluation of face classification systems

Abstract

In this paper face classification systems based on 3D images are compared in terms of classification and metrological performance in presence of image uncertainty. In previous papers the authors proposed a new approach to classification and recognition problems. It is based on the evaluation of the image uncertainty and on the exploitation of such information to provide the confidence level of classification results. Such approach is here adopted for comparing several 3D architectures, different for camera specifications and geometrical positioning, with the aims of quantifying their performance from a metrological point of view and of identifying the configuration able to optimize the result reliability.