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Face Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Features
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Datum
2020
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Gesellschaft für Informatik e.V.
Zusammenfassung
The security of the commonly used face recognition algorithms is often doubted, as they
appear vulnerable to so-called presentation attacks. While there are a number of detection methods
that are using different light spectra to detect these attacks this is the first work to explore skin properties
using the ultraviolet spectrum. Our multi-sensor approach consists of learning features that
appear in the comparison of two images, one in the visible and one in the ultraviolet spectrum. We
use brightness and keypoints as features for training, experimenting with different learning strategies.
We present the results of our evaluation on our novel Face UV PAD database. The results of
our method are evaluated in an leave-one-out comparison, where we achieved an APCER/BPCER
of 0%/0.2%. The results obtained indicate that UV images in presentation attack detection include
useful information that are not easy to overcome.