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Unconstrained face mask and face-hand interaction datasets: building a computer vision system to help prevent the transmission of COVID-19

Eyiokur, Fevziye Irem 1; Ekenel, Hazım Kemal; Waibel, Alexander 1
1 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)

Abstract:

Health organizations advise social distancing, wearing face mask, and avoiding touching face to prevent the spread of coronavirus. Based on these protective measures, we developed a computer vision system to help prevent the transmission of COVID-19. Specifically, the developed system performs face mask detection, face-hand interaction detection, and measures social distance. To train and evaluate the developed system, we collected and annotated images that represent face mask usage and face-hand interaction in the real world. Besides assessing the performance of the developed system on our own datasets, we also tested it on existing datasets in the literature without performing any adaptation on them. In addition, we proposed a module to track social distance between people. Experimental results indicate that our datasets represent the real-world’s diversity well. The proposed system achieved very high performance and generalization capacity for face mask usage detection, face-hand interaction detection, and measuring social distance in a real-world scenario on unseen data. The datasets are available at https://github.com/iremeyiokur/COVID-19-Preventions-Control-System.


Verlagsausgabe §
DOI: 10.5445/IR/1000149486
Veröffentlicht am 10.08.2022
Originalveröffentlichung
DOI: 10.1007/s11760-022-02308-x
Scopus
Zitationen: 9
Web of Science
Zitationen: 7
Dimensions
Zitationen: 20
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 1863-1703, 1863-1711
KITopen-ID: 1000149486
Erschienen in Signal, Image and Video Processing
Verlag Springer
Band 17
Heft 4
Seiten 1027–1034
Vorab online veröffentlicht am 22.07.2022
Nachgewiesen in Scopus
Dimensions
Web of Science
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