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Soft-Biometrics Estimation In the Era of Facial Masks

dc.contributor.authorAlonso-Fernandez, Fernando
dc.contributor.authorDiaz, Kevin Hernandez
dc.contributor.authorRamis, Silvia
dc.contributor.authorPerales, Francisco J.
dc.contributor.authorBigun, Josef
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.abstractWe analyze the use of images from face parts to estimate soft-biometrics indicators. Partial face occlusion is common in unconstrained scenarios, and it has become mainstream during the COVID-19 pandemic due to the use of masks. Here, we apply existing pre-trained CNN architectures, proposed in the context of the ImageNet Large Scale Visual Recognition Challenge, to the tasks of gender, age, and ethnicity estimation. Experiments are done with 12007 images from the Labeled Faces in the Wild (LFW) database. We show that such off-the-shelf features can effectively estimate soft-biometrics indicators using only the ocular region. For completeness, we also evaluate images showing only the mouth region. In overall terms, the network providing the best accuracy only suffers accuracy drops of 2-4% when using the ocular region, in comparison to using the entire face. Our approach is also shown to outperform in several tasks two commercial off-the-shelf systems (COTS) that employ the whole face, even if we only use the eye or mouth regions.en
dc.identifier.isbn978-3-88579-700-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34327
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.subjectSoft-Biometrics
dc.subjectPeriocular
dc.subjectGender
dc.subjectAge
dc.subjectEthnicity
dc.titleSoft-Biometrics Estimation In the Era of Facial Masksen
dc.typeText/Conference Paper
gi.citation.endPage19
gi.citation.publisherPlaceBonn
gi.citation.startPage11
gi.conference.date16.-18. September 2020
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleRegular Research Papers

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