Siegmund, Dirk ; Kerckhoff, Florian ; Yeste Magdaleno, Javier ; Jansen, Nils ; Kirchbuchner, Florian ; Kuijper, Arjan (2020)
Face Presentation Attack Detection in Ultraviolet Spectrum
via Local and Global Features.
19th International Conference of the Biometrics Special Interest Group. virtual Conference (16.09.2020-18.09.2020)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2020 |
| Autor(en): | Siegmund, Dirk ; Kerckhoff, Florian ; Yeste Magdaleno, Javier ; Jansen, Nils ; Kirchbuchner, Florian ; Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Face Presentation Attack Detection in Ultraviolet Spectrum via Local and Global Features |
| Sprache: | Englisch |
| Publikationsjahr: | 2020 |
| Verlag: | Gesellschaft für Informatik |
| Buchtitel: | BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group |
| Veranstaltungstitel: | 19th International Conference of the Biometrics Special Interest Group |
| Veranstaltungsort: | virtual Conference |
| Veranstaltungsdatum: | 16.09.2020-18.09.2020 |
| URL / URN: | https://dl.gi.de/handle/20.500.12116/34329 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | 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. |
| Freie Schlagworte: | Biometric identification systems, Spoofing attacks, Biometrics, Security technologies |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
| Hinterlegungsdatum: | 09 Apr 2021 10:03 |
| Letzte Änderung: | 09 Apr 2021 10:03 |
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