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  4. Biometrics in the Era of COVID-19: Challenges and Opportunities
 
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2022
Journal Article
Title

Biometrics in the Era of COVID-19: Challenges and Opportunities

Abstract
Since early 2020, the COVID-19 pandemic has had a considerable impact on many aspects of daily life. A range of different measures have been implemented worldwide to reduce the rate of new infections and to manage the pressure on national health services. A primary strategy has been to reduce gatherings and the potential for transmission through the prioritisation of remote working and education. Enhanced hand hygiene and the use of facial masks have decreased the spread of pathogens when gatherings are unavoidable. These particular measures present challenges for reliable biometric recognition, e.g. for facial-, voice-and hand-based biometrics. At the same time, new challenges create new opportunities and research directions, e.g. renewed interest in non-constrained iris or periocular recognition, touch-less fingerprint-and vein-based authentication and the use of biometric characteristics for disease detection. This article presents an overview of the research carried out to address those challenges and emerging opportunities.
Author(s)
Gomez-Barrero, Marta
Hochschule Ansbach
Drozdowski, Pawel
Hochschule Darmstadt  
Rathgeb, Christian
Hochschule Darmstadt  
Patino, Jose
EURECOM, France
Todisco, Massimiliano
EURECOM, France
Nautsch, Andreas
EURECOM, France
Damer, Naser  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Priesnitz, Jannier
Hochschule Darmstadt  
Evans, Nicholas
EURECOM, France
Busch, Christoph
Hochschule Darmstadt  
Journal
IEEE Transactions on Technology and Society  
Project(s)
Next Generation Biometric Systems  
Next Generation Biometric Systems  
Zuverlässige, sichere und Datenschutz-bewahrende multi-biometrische Personen Authentifizierung  
Funder
Bundesministerium für Bildung und Forschung -BMBF-
Hessisches Ministerium für Wissenschaft und Kunst
Deutsche Forschungsgemeinschaft -DFG-, Bonn  
Open Access
DOI
10.1109/TTS.2022.3203571
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • Lead Topic: Digitized Work

  • Lead Topic: Smart City

  • Lead Topic: Visual Computing as a Service

  • Research Line: Computer vision (CV)

  • Research Line: Human computer interaction (HCI)

  • Research Line: Machine Learning (ML)

  • Biometrics

  • Machine learning

  • Security technologies

  • Human-centered computing

  • Society

  • ATHENE

  • CRISP

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