ARTICLE deFreitasPereira_EURASIPJIVP_2014/IDIAP Face liveness detection using dynamic texture de Freitas Pereira, Tiago Komulainen, Jukka Anjos, André De Martino, José Mario Hadid, Abdenour Pietikainen, Matti Marcel, Sébastien Anti-spoofing Counter-Measures Face Recognition temporal pattern extraction Texture Analysis EXTERNAL http://publications.idiap.ch/attachments/papers/2014/deFreitasPereira_EURASIPJIVP_2014.pdf PUBLIC EURASIP Journal on Image and Video Processing 2 2014 https://pypi.python.org/pypi/antispoofing.lbptop URL 10.1186/1687-5281-2014-2 doi User authentication is an important step to protect information, and in this context, face biometrics is potentially advantageous. Face biometrics is natural, intuitive, easy to use, and less human-invasive. Unfortunately, recent work has revealed that face biometrics is vulnerable to spoofing attacks using cheap low-tech equipment. This paper introduces a novel and appealing approach to detect face spoofing using the spatiotemporal (dynamic texture) extensions of the highly popular local binary pattern operator. The key idea of the approach is to learn and detect the structure and the dynamics of the facial micro-textures that characterise real faces but not fake ones. We evaluated the approach with two publicly available databases (Replay-Attack Database and CASIA Face Anti-Spoofing Database). The results show that our approach performs better than state-of-the-art techniques following the provided evaluation protocols of each database.