Face liveness detection using dynamic texture

• Published in: EURASIP journal on image and video processing 2014-01, Vol.2014 (1), p.1-15, Article 2
• Main Authors: Freitas Pereira, Tiago de, Komulainen, Jukka, Anjos, André, De Martino, José Mario, Hadid, Abdenour, Pietikäinen, Matti, Marcel, Sébastien
• Format: Article
• Language: English
• Subjects: Authentication; Biometrics; Dynamics; Engineering; Facial; Image Processing and Computer Vision; Local binary patterns (LBP)-based image and video analysis; Pattern Recognition; Signal,Image and Speech Processing; Spoofing; State of the art; Surface layer; Texture
• ISSN: 1687-5281; 1687-5176; 1687-5281
• DOI: 10.1186/1687-5281-2014-2

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.