Advanced Face Presentation Attack Detection on Light Field Database

Abstract

In the last years several works have been focused on the impact of new sensors on face recognition. A particular interest has been addressed to technologies able to detect the depth of the scene as light field cameras. Together with person identification algorithms, new anti-spoofing methods customized for specific devices have to be investigated. In this paper, a new algorithm for presentation attack detection on light field face database is proposed. While distance between subject and camera is not a relevant information for standard 2D spoofing attacks, it could be important when using 3D cameras. We prove through three experiments that the proposed method based on depth map elaboration outperforms the existent algorithms in presentation attack detection on light field images.