Damer, Naser ; Boller, Viola ; Wainakh, Yaza ; Boutros, Fadi ; Terhörst, Philipp ; Braun, Andreas ; Kuijper, Arjan (2019)
Detecting Face Morphing Attacks by Analyzing the Directed Distances of Facial Landmarks Shifts.
40th German Conference, GCPR. Stuttgart, Germany (09.10.2018-12.10.2018)
doi: 10.1007/978-3-030-12939-2_36
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Face morphing attacks create face images that are verifiable to multiple identities. Associating such images to identity documents lead to building faulty identity links, causing attacks on operations like border crossing. Most of previously proposed morphing attack detection approaches directly classified features extracted from the investigated image. We discuss the operational opportunity of having a live face probe to support the morphing detection decision and propose a detection approach that take advantage of that. Our proposed solution considers the facial landmarks shifting patterns between reference and probe images. This is represented by the directed distances to avoid confusion with shifts caused by other variations. We validated our approach using a publicly available database, built on 549 identities. Our proposed detection concept is tested with three landmark detectors and proved to outperform the baseline concept based on handcrafted and transferable CNN features.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2019 |
Autor(en): | Damer, Naser ; Boller, Viola ; Wainakh, Yaza ; Boutros, Fadi ; Terhörst, Philipp ; Braun, Andreas ; Kuijper, Arjan |
Art des Eintrags: | Bibliographie |
Titel: | Detecting Face Morphing Attacks by Analyzing the Directed Distances of Facial Landmarks Shifts |
Sprache: | Englisch |
Publikationsjahr: | 2019 |
Ort: | Cham |
Verlag: | Springer |
Buchtitel: | Pattern Recognition |
Reihe: | Lecture Notes in Computer Science (LNCS) |
Band einer Reihe: | 11269 |
Veranstaltungstitel: | 40th German Conference, GCPR |
Veranstaltungsort: | Stuttgart, Germany |
Veranstaltungsdatum: | 09.10.2018-12.10.2018 |
DOI: | 10.1007/978-3-030-12939-2_36 |
URL / URN: | https://doi.org/10.1007/978-3-030-12939-2_36 |
Kurzbeschreibung (Abstract): | Face morphing attacks create face images that are verifiable to multiple identities. Associating such images to identity documents lead to building faulty identity links, causing attacks on operations like border crossing. Most of previously proposed morphing attack detection approaches directly classified features extracted from the investigated image. We discuss the operational opportunity of having a live face probe to support the morphing detection decision and propose a detection approach that take advantage of that. Our proposed solution considers the facial landmarks shifting patterns between reference and probe images. This is represented by the directed distances to avoid confusion with shifts caused by other variations. We validated our approach using a publicly available database, built on 549 identities. Our proposed detection concept is tested with three landmark detectors and proved to outperform the baseline concept based on handcrafted and transferable CNN features. |
Freie Schlagworte: | Biometrics, Face recognition, Spoofing attacks |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
Hinterlegungsdatum: | 26 Jun 2019 08:54 |
Letzte Änderung: | 26 Jun 2019 08:54 |
PPN: | |
Export: | |
Suche nach Titel in: | TUfind oder in Google |
Frage zum Eintrag |
Optionen (nur für Redakteure)
Redaktionelle Details anzeigen |