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@TECHREPORT{George_Idiap-RR-02-2022,
         author = {George, Anjith and Geissbuhler, David and Marcel, S{\'{e}}bastien},
       projects = {Idiap, ODIN/BATL},
          month = {2},
          title = {A Comprehensive Evaluation on Multi-channel Biometric Face Presentation Attack Detection},
           type = {Idiap-RR},
         number = {Idiap-RR-02-2022},
           year = {2022},
    institution = {Idiap},
       abstract = {The vulnerability against presentation attacks is
a crucial problem undermining the wide-deployment of face
recognition systems. Though presentation attack detection (PAD)
systems try to address this problem, the lack of generalization
and robustness continues to be a major concern. Several works
have shown that using multi-channel PAD systems could alleviate
this vulnerability and result in more robust systems. However,
there is a wide selection of channels available for a PAD system
such as RGB, Near Infrared, Shortwave Infrared, Depth, and
Thermal sensors. Having a lot of sensors increases the cost of
the system, and therefore an understanding of the performance
of different sensors against a wide variety of attacks is necessary
while selecting the modalities. In this work, we perform a
comprehensive study to understand the effectiveness of various
imaging modalities for PAD. The studies are performed on a
multi-channel PAD dataset, collected with 14 different sensing
modalities considering a wide range of 2D, 3D, and partial
attacks. We used the multi-channel convolutional network-based
architecture, which uses pixel-wise binary supervision. The model
has been evaluated with different combinations of channels, and
different image qualities on a variety of challenging known and
unknown attack protocols. The results reveal interesting trends
and can act as pointers for sensor selection for safety-critical
presentation attack detection systems. The source codes and
protocols to reproduce the results are made available publicly
making it possible to extend this work to other architectures.},
            pdf = {https://publications.idiap.ch/attachments/reports/2021/George_Idiap-RR-02-2022.pdf}
}