%Aigaion2 BibTeX export from Idiap Publications
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@INPROCEEDINGS{Chingovska_IEEEBIOSIG2012_2012,
         author = {Chingovska, Ivana and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
       projects = {Idiap, TABULA RASA},
          month = sep,
          title = {On the Effectiveness of Local Binary Patterns in Face Anti-spoofing},
      booktitle = {Proceedings of the 11th International Conference of the Biometrics Special Interes Group},
           year = {2012},
       crossref = {Chingovska_Idiap-RR-19-2012},
       abstract = {Spoofing attacks are one of the security traits that
biometric recognition systems are proven to be vulnerable to.
When spoofed, a biometric recognition system is bypassed by
presenting a copy of the biometric evidence of a valid user. Among
all biometric modalities, spoofing a face recognition system is
particularly easy to perform: all that is needed is a simple
photograph of the user.
In this paper, we address the problem of detecting face spoofing
attacks. In particular, we inspect the potential of texture features
based on Local Binary Patterns (LBP) and their variations on
three types of attacks: printed photographs, and photos and
videos displayed on electronic screens of different sizes. For
this purpose, we introduce REPLAY-ATTACK, a novel publicly
available face spoofing database which contains all the mentioned
types of attacks. We conclude that LBP, with 15\% Half Total
Error Rate, show moderate discriminability when confronted
with a wide set of attack types.},
            pdf = {https://publications.idiap.ch/attachments/papers/2012/Chingovska_IEEEBIOSIG2012_2012.pdf}
}



crossreferenced publications: 
@TECHREPORT{Chingovska_Idiap-RR-19-2012,
         author = {Chingovska, Ivana and Anjos, Andr{\'{e}} and Marcel, S{\'{e}}bastien},
       keywords = {Biometrics, Counter-Measures, Local Binary Patterns, Spoofing Attacks},
       projects = {TABULA RASA},
          month = {7},
          title = {On the Effectiveness of Local Binary Patterns in Face Anti-spoofing},
           type = {Idiap-RR},
        journal = {IEEE BIOSIG 2012},
         number = {Idiap-RR-19-2012},
           year = {2012},
    institution = {Idiap},
       abstract = {Spoofing attacks are one of the security traits that biometric recognition systems are proven to be vulnerable to. When spoofed, a biometric recognition system is bypassed by presenting a copy of the biometric evidence of a valid user. Among all biometric modalities, spoofing a face recognition system is particularly easy to perform: all that is needed is a simple photograph of the user.

In this paper, we address the problem of detecting face spoofing attacks. In particular, we inspect the potential of texture features based on Local Binary Patterns (LBP) and their variations on three types of attacks: printed photographs, and photos and videos displayed on electronic screens of different sizes. For this purpose, we introduce REPLAY-ATTACK, a novel publicly available face spoofing database which contains all the mentioned types of attacks. We conclude that LBP, with  ~15\% Half Total Error Rate, show moderate discriminability when confronted with a wide set of attack types.},
            pdf = {https://publications.idiap.ch/attachments/reports/2012/Chingovska_Idiap-RR-19-2012.pdf}
}