• English
  • Deutsch
  • Log In
    Password Login
    or
  • Research Outputs
  • Projects
  • Researchers
  • Institutes
  • Statistics
Repository logo
Fraunhofer-Gesellschaft
  1. Home
  2. Fraunhofer-Gesellschaft
  3. Artikel
  4. Masked Face Recognition: Human versus Machine
 
  • Details
  • Full
Options
07 May 2022
Journal Article
Titel

Masked Face Recognition: Human versus Machine

Abstract
The recent COVID‐19 pandemic has increased the focus on hygienic and contactless identity verification methods. However, the pandemic led to the wide use of face masks, essential to keep the pandemic under control. The effect of wearing a mask on face recognition (FR) in a collaborative environment is a currently sensitive yet understudied issue. Recent reports have tackled this by evaluating the masked probe effect on the performance of automatic FR solutions. However, such solutions can fail in certain processes, leading to the verification task being performed by a human expert. This work provides a joint evaluation and in‐depth analyses of the face verification performance of human experts in comparison to state‐of‐the‐art automatic FR solutions. This involves an extensive evaluation by human experts and 4 automatic recognition solutions. The study concludes with a set of take‐home messages on different aspects of the correlation between the verification behaviour of humans and machines.
Author(s)
Damer, Naser
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Boutros, Fadi
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Süßmilch, Marius
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Fang, Meiling
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Kirchbuchner, Florian orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Kuijper, Arjan orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Zeitschrift
IET biometrics
Project(s)
Next Generation Biometric Systems
Funder
Bundesministerium für Bildung und Forschung -BMBF-
Konferenz
Gesellschaft für Informatik, Special Interest Group on Biometrics and Electronic Signatures (BIOSIG International Conference) 2021
Thumbnail Image
DOI
10.1049/bme2.12077
Language
English
google-scholar
Fraunhofer-Institut für Graphische Datenverarbeitung IGD
Tags
  • 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

  • Face recognition

  • Performance evaluation

  • Human vision

  • Machine learning

  • ATHENE

  • CRISP

  • Cookie settings
  • Imprint
  • Privacy policy
  • Api
  • Send Feedback
© 2022