Article

Masked face identification is improved by diagnostic feature training

Details

Citation

Carragher DJ, Towler A, Mileva VR, White D & Hancock PJB (2022) Masked face identification is improved by diagnostic feature training. Cognitive Research: Principles and Implications, 7 (1), Art. No.: 30. https://doi.org/10.1186/s41235-022-00381-x

Abstract
To slow the spread of COVID-19, many people now wear face masks in public. Face masks impair our ability to identify faces, which can cause problems for professional staff who identify offenders or members of the public. Here, we investigate whether performance on a masked face matching task can be improved by training participants to compare diagnostic facial features (the ears and facial marks)—a validated training method that improves matching performance for unmasked faces. We show this brief diagnostic feature training, which takes less than two minutes to complete, improves matching performance for masked faces by approximately 5%. A control training course, which was unrelated to face identification, had no effect on matching performance. Our findings demonstrate that comparing the ears and facial marks is an effective means of improving face matching performance for masked faces. These findings have implications for professions that regularly perform face identification.

Keywords
Cognitive Neuroscience; Experimental and Cognitive Psychology

Journal
Cognitive Research: Principles and Implications: Volume 7, Issue 1

StatusPublished
FundersEPSRC Engineering and Physical Sciences Research Council and Australian Research Council
Publication date31/12/2022
Publication date online05/04/2022
Date accepted by journal17/03/2022
URLhttp://hdl.handle.net/1893/34148
PublisherSpringer Science and Business Media LLC
eISSN2365-7464

People (3)

People

Dr Daniel Carragher

Dr Daniel Carragher

Research Assistant, Psychology

Professor Peter Hancock

Professor Peter Hancock

Professor, Psychology

Dr Viktoria Mileva

Dr Viktoria Mileva

Lecturer in Psychology, Psychology

Projects (1)

FACERVM - Face Matching
PI: