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Toward to Reduction of Bias for Gender and Ethnicity from Face Images using Automated Skin Tone Classification

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dc.contributor.authorMolina, David
dc.contributor.authorCausa, Leonardo
dc.contributor.authorTapia, Juan
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.accessioned2020-09-16T08:25:47Z
dc.date.available2020-09-16T08:25:47Z
dc.date.issued2020
dc.description.abstractThis paper proposes and analyzes a new approach for reducing the bias in gender caused by skin tone from faces based on transfer learning with fine-tuning. The categorization of the ethnicity was developed based on an objective method instead of a subjective Fitzpatrick scale. A Kmeans method was used to categorize the color faces using clusters of RGB pixel values. Also, a new database was collected from the internet and will be available upon request. Our method outperforms the state of the art and reduces the gender classification bias using the skin-type categorization. The best results were achieved with VGGNET architecture with 96.71% accuracy and 3.29% error rate.en
dc.identifier.isbn978-3-88579-700-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34339
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.subjectGender classification
dc.subjectBias
dc.subjectSkin-Detection
dc.titleToward to Reduction of Bias for Gender and Ethnicity from Face Images using Automated Skin Tone Classificationen
dc.typeText/Conference Paper
gi.citation.endPage289
gi.citation.publisherPlaceBonn
gi.citation.startPage281
gi.conference.date16.-18. September 2020
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleFurther Conference Contributions

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P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group