One-Snapshot Face Anti-spoofing Using a Light Field Camera

Abstract

Face recognition is an increasingly popular technology for user authentication. However, face recognition is susceptible to spoofing attacks. Therefore, a reliable way to detect malicious attacks is crucial to the robustness of the face recognition system. This paper describes a new approach to utilizing light field camera for defending spoofing face attacks, like (warped) printed 2D facial photos and high-definition tablet images. The light field camera is a sensor that can record the directions as well as the colors of incident rays. Needing only one snapshot, multiple refocused images can be generated. In the proposed method, three kinds of features extracted from a pair of refocused images are extracted to discriminate fake faces and real faces. To verify the performance, we build a light field photograph databases and conduct experiments. Experimental results reveal that the employed features can achieve remarkable anti-spoofing accuracy under different types of spoofing attacks.