Face anti-spoofing to 3D masks by combining texture and geometry features

Abstract

Anti-spoofing has become more important in face recognition systems. This paper proposes a novel approach to resist 3D face mask attacks, which jointly uses texture and shape features. Different from existing methods where depth information by extra equipments is required, we reconstruct geometry cues from RGB images through 3D Morphable Model. The hand-crafted features as well as the deep ones are then extracted to comprehensively represent texture and shape differences between real and fake faces and finally fused for decision making. The experiments are carried out on the 3D-MAD dataset and the competitive results indicate the effectiveness.