Rajith Vidanaarachchi

Rajith Vidanaarachchi

Post-Doc Researcher and Educator at the University of Melbourne

Imagery, Privacy and Ethics: An Overview of Partially Occluded Facial Biometric Analysis in the Era of Face Masks

Published in International Conference on Electrical, Computer and Energy Technologies (ICECET) 2021, 2022

The COVID-19 pandemic has drastically changed human lifestyles, with implications on many aspects of human life. With the proliferation of masks to combat the spread of the virus, many computer vision workflows have been inadvertently affected to varying degrees. Consequently, many research articles have been dedicated to evaluating the impact to existing facial imagery recognition problems. Several works have attempted to either extend existing facial models or develop new techniques specific to masked faces. Many new benchmark tasks have also been introduced in this subdomain. However, a detailed review of such advancements is not available for perusal in this critical area for COVID-safe protocol development. In this work, we address this issue as the first review of masked facial recognition tasks and techniques robust to masked facial images. Our motivation is to provide a central reference for automated public health and COVID-safe identification protocols while also exploring the ethical aspects of further development of such techniques.

Download paper here

R. Vidanaarachchi, S. Seneviratne, N. Kasthuriarachchi, J. S. Wijnands and S. Rasnayaka, “Imagery, Privacy and Ethics: An Overview of Partially Occluded Facial Biometric Analysis in the Era of Face Masks,” 2021 International Conference on Electrical, Computer and Energy Technologies (ICECET), 2021, pp. 1-8, doi: 10.1109/ICECET52533.2021.9698503.

BibTeX

@INPROCEEDINGS{9698503,
  author={Vidanaarachchi, Rajith and Seneviratne, Sachith and Kasthuriarachchi, Nuran and Wijnands, Jasper S. and Rasnayaka, Sanka},
  booktitle={2021 International Conference on Electrical, Computer and Energy Technologies (ICECET)}, 
  title={Imagery, Privacy and Ethics: An Overview of Partially Occluded Facial Biometric Analysis in the Era of Face Masks}, 
  year={2021},
  volume={},
  number={},
  pages={1-8},
  abstract={The COVID-19 pandemic has drastically changed human lifestyles, with implications on many aspects of human life. With the proliferation of masks to combat the spread of the virus, many computer vision workflows have been inadvertently affected to varying degrees. Consequently, many research articles have been dedicated to evaluating the impact to existing facial imagery recognition problems. Several works have attempted to either extend existing facial models or develop new techniques specific to masked faces. Many new benchmark tasks have also been introduced in this subdomain. However, a detailed review of such advancements is not available for perusal in this critical area for COVID-safe protocol development. In this work, we address this issue as the first review of masked facial recognition tasks and techniques robust to masked facial images. Our motivation is to provide a central reference for automated public health and COVID-safe identification protocols while also exploring the ethical aspects of further development of such techniques.},
  keywords={},
  doi={10.1109/ICECET52533.2021.9698503},
  ISSN={},
  month={Dec},}