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Face Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Features

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dc.contributor.authorSiegmund, Dirk
dc.contributor.authorKerckhoff, Florian
dc.contributor.authorMagdaleno, Javier Yeste
dc.contributor.authorJansen, V
dc.contributor.authorKirchbuchner, Florian
dc.contributor.authorKuijper, Arjan
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorUhl, Andreas
dc.date.accessioned2020-09-16T08:25:45Z
dc.date.available2020-09-16T08:25:45Z
dc.date.issued2020
dc.description.abstractThe 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.en
dc.identifier.isbn978-3-88579-700-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34329
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-306
dc.subjectFace Presentation Attack Detection PAD
dc.subjectUltraviolet
dc.subjectMFP
dc.subjectBiometrics
dc.titleFace Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Featuresen
dc.typeText/Conference Paper
gi.citation.endPage214
gi.citation.publisherPlaceBonn
gi.citation.startPage207
gi.conference.date16.-18. September 2020
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleFurther Conference Contributions

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P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group