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To Detect or not to Detect: The Right Faces to Morph

Damer, Naser ; Saladie, Alexandra Mosegui ; Zienert, Steffen ; Wainakh, Yaza ; Terhörst, Philipp ; Kirchbuchner, Florian ; Kuijper, Arjan (2019)
To Detect or not to Detect: The Right Faces to Morph.
12th IAPR International Conference On Biometrics (ICB 2019). Crete, Greece (04.06.2019-07.06.2019)
doi: 10.1109/ICB45273.2019.8987316
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Recent works have studied the face morphing attack detection performance generalization over variations in morphing approaches, image re-digitization, and image source variations. However, these works assumed a constant approach for selecting the images to be morphed (pairing) across their training and testing data. A realistic variation in the pairing protocol in the training data can result in challenges and opportunities for a stable attack detector. This work extensively study this issue by building a novel database with three different pairing protocols and two different morphing approaches. We study the detection generalization over these variations for single image and differential attack detection, along with handcrafted and CNNbased features. Our observations included that training an attack detection solution on attacks created from dissimilar face images, in contrary to the common practice, can result in an overall more generalized detection performance. Moreover, we found that differential attack detection is very sensitive to variations in morphing and pairing protocols.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2019
Autor(en): Damer, Naser ; Saladie, Alexandra Mosegui ; Zienert, Steffen ; Wainakh, Yaza ; Terhörst, Philipp ; Kirchbuchner, Florian ; Kuijper, Arjan
Art des Eintrags: Bibliographie
Titel: To Detect or not to Detect: The Right Faces to Morph
Sprache: Englisch
Publikationsjahr: 2019
Veranstaltungstitel: 12th IAPR International Conference On Biometrics (ICB 2019)
Veranstaltungsort: Crete, Greece
Veranstaltungsdatum: 04.06.2019-07.06.2019
DOI: 10.1109/ICB45273.2019.8987316
URL / URN: https://doi.org/10.1109/ICB45273.2019.8987316
Kurzbeschreibung (Abstract):

Recent works have studied the face morphing attack detection performance generalization over variations in morphing approaches, image re-digitization, and image source variations. However, these works assumed a constant approach for selecting the images to be morphed (pairing) across their training and testing data. A realistic variation in the pairing protocol in the training data can result in challenges and opportunities for a stable attack detector. This work extensively study this issue by building a novel database with three different pairing protocols and two different morphing approaches. We study the detection generalization over these variations for single image and differential attack detection, along with handcrafted and CNNbased features. Our observations included that training an attack detection solution on attacks created from dissimilar face images, in contrary to the common practice, can result in an overall more generalized detection performance. Moreover, we found that differential attack detection is very sensitive to variations in morphing and pairing protocols.

Freie Schlagworte: Biometrics Spoofing attacks Face recognition
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing
Hinterlegungsdatum: 14 Apr 2020 07:35
Letzte Änderung: 27 Feb 2023 11:25
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