Face anti-spoofing (presentation attack detection)

Without dedicated countermeasures, most of the existing facial biometric systems are vulnerable to spoofing (presentation attacks) because they try to maximize the discriminability between identities without regards to whether the presented trait originates from a living legitimate client or not. CMVS has been actively developing software-based methods for presentation attack detection (PAD). The proposed countermeasures to spoofing analyze the facial texture, motion and contextual information for describing the inherent disparities between genuine faces and fake ones. In 2013,   we received the IET Biometrics Premium Award 2013 for our paper published in IET Biometrics journal in 2012.


Selected References

Määttä J, Hadid A & Pietikäinen M (2011) Face spoofing detection from single images using micro-texture analysis. Proc. International Joint Conference on Biometrics (IJCB 2011), Washington, D.C., USA, 7 p.

Määttä J, Hadid A & Pietikäinen M (2012) Face spoofing detection from single images using texture and local shape analysis. IET Biometrics 1(1):3-10.

Komulainen J, Hadid A & Pietikäinen M (2013) Context based face anti-spoofing. Proc. the IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS), 8 p.

Pereira TdF, Komulainen J, Anjos A, De Martino JM, Hadid A, Pietikäinen M & Marcel S (2014) Face liveness detection using dynamic texture. EURASIP Journal on Image and Video Processing, 2014:2.

Boulkenafet Z, Komulainen J & Hadid A (2016) Face spoofing detection using colour texture analysis. IEEE Transactions on Information Forensics & Security 11(8): 1818-1830.

Li X, Komulainen J, Zhao G, Yuen PC & Pietikäinen M (2016) Generalized face anti-spoofing by detecting pulse from face videos. Proc. International Conference on Pattern Recognition (ICPR 2016), accepted.

Last updated: 22.8.2016