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Impact of Doppelgängers on Face Recognition: Database and Evaluation

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dc.contributor.authorRathgeb, Christian
dc.contributor.authorDrozdowski, Pawel
dc.contributor.authorObel, Marcel
dc.contributor.authorDörsch, André
dc.contributor.authorStockhardt, Fabian
dc.contributor.authorHaryanto, Nathania E.
dc.contributor.authorBernardo, Kevin
dc.contributor.authorBusch, Christoph
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDamer, Naser
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorGomez-Barrero, Marta
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorSequeira, Ana
dc.contributor.editorUhl, Andreas
dc.date.accessioned2021-10-04T08:43:46Z
dc.date.available2021-10-04T08:43:46Z
dc.date.issued2021
dc.description.abstractLook-alikes, a.k.a. doppelgängers, increase the probability of false matches in a facial recognition system, in contrast to random face image pairs selected for non-mated comparison trials. In order to analyse and improve the robustness of automated face recognition, datasets of doppelgänger face image pairs are needed. In this work, we present a new face database consisting of 400 pairs of doppelgänger images. Subsequently, two state-of-the-art face recognition systems are evaluated on said database and other public datasets, including the Disguised Faces in The Wild (DFW) database. It is found that the collected image pairs yield very high similarity scores resulting in a significant increase of false match rates. To facilitate reproducible research and future experiments in this field, the dataset is made available.en
dc.identifier.isbn978-3-88579-709-8
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37454
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-315
dc.subjectbiometrics
dc.subjectface recognition
dc.subjectdoppelgänger
dc.subjectlook-alike
dc.subjectdatabase
dc.titleImpact of Doppelgängers on Face Recognition: Database and Evaluationen
dc.typeText/Conference Paper
gi.citation.endPage20
gi.citation.publisherPlaceBonn
gi.citation.startPage11
gi.conference.date15.-17. September 2021
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleRegular Research Papers

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P315 - BIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group