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An end-to-end face authentication system integrating both 2D color images and depth data is presented in this paper, based on a low-cost sensor capable of real-time acquisition of 3D images and associated color images. Depth data is used for robust face detection, localization and 3D pose estimation, as well as for compensating pose and illumination variations of facial images prior to classification. The proposed algorithms were implemented in a pilot security system for access control in real settings. Experimental results show that when normalized images, depicting upright orientation and frontal lighting, are used for authentication, significantly lower error rates are achieved. Moreover, the combination of color and depth data results in increased authentication accuracy, compared to the use of each modality alone.