Face Liveness Detection From a Single Image via Diffusion Speed Model
Abstract— Face Liveness Detection From a Single Image via Diffusion Speed Model. Spooﬁng using photographs or videos is one of the most common methods of attacking face recognition and veriﬁcation systems. In this paper, we propose a real-time and nonintrusive method based on the diffusion speed of a single image to address this problem. In particular, inspired by the observation that the difference in surface properties between a live face and a fake one is efﬁciently revealed in the diffusion speed, we exploit anti spooﬁng features by utilizing the total variation ﬂow scheme. More speciﬁcally, we propose deﬁning the local patterns of the diffusion speed, the so-called local speed patterns, as our features, which are input into the linear < Final Year Projects 2016 > SVM classiﬁer to determine whether the given face is fake or not.