Face Spoofing Video Detection Using Spatio-Temporal Statistical Binary Pattern
Ying Zhang, Rohit Kumar Dubey, Guang Hua, Vrizlynn L. L. Thing · 2018
Face has been used as a popular biometric trait to identify a person. However, attacking such face recognition system is not challenging today by using for example a fake face photo or video in front of a camera. In this paper, we present a novel feature, namely, SBP-TOP, to effectively identify such spoofings. SBP-TOP presents the texture information for the face region from both spatial and temporal perspectives. We have tested the proposed feature on two well-known face spoofing datasets: new Michigan State University mobile face spoofing database (MSU MFSD) and CASIA Face Anti-Spoofing Database (CASIA). The results indicate an accuracy over 95% on both datasets and there is an improvement over the state-of-the-art feature by around 10% and 3.2%, respectively.