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Hyper-realistic face masks: a new challenge in person identification

Overview of attention for article published in Cognitive Research: Principles and Implications, October 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#2 of 230)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
86 news outlets
twitter
88 tweeters
googleplus
3 Google+ users

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
30 Mendeley
Title
Hyper-realistic face masks: a new challenge in person identification
Published in
Cognitive Research: Principles and Implications, October 2017
DOI 10.1186/s41235-017-0079-y
Pubmed ID
Authors

Jet Gabrielle Sanders, Yoshiyuki Ueda, Kazusa Minemoto, Eilidh Noyes, Sakiko Yoshikawa, Rob Jenkins

Abstract

We often identify people using face images. This is true in occupational settings such as passport control as well as in everyday social environments. Mapping between images and identities assumes that facial appearance is stable within certain bounds. For example, a person's apparent age, gender and ethnicity change slowly, if at all. It also assumes that deliberate changes beyond these bounds (i.e., disguises) would be easy to spot. Hyper-realistic face masks overturn these assumptions by allowing the wearer to look like an entirely different person. If unnoticed, these masks break the link between facial appearance and personal identity, with clear implications for applied face recognition. However, to date, no one has assessed the realism of these masks, or specified conditions under which they may be accepted as real faces. Herein, we examined incidental detection of unexpected but attended hyper-realistic masks in both photographic and live presentations. Experiment 1 (UK; n = 60) revealed no evidence for overt detection of hyper-realistic masks among real face photos, and little evidence of covert detection. Experiment 2 (Japan; n = 60) extended these findings to different masks, mask-wearers and participant pools. In Experiment 3 (UK and Japan; n = 407), passers-by failed to notice that a live confederate was wearing a hyper-realistic mask and showed limited evidence of covert detection, even at close viewing distance (5 vs. 20 m). Across all of these studies, viewers accepted hyper-realistic masks as real faces. Specific countermeasures will be required if detection rates are to be improved.

Twitter Demographics

The data shown below were collected from the profiles of 88 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 17%
Student > Ph. D. Student 4 13%
Other 4 13%
Researcher 3 10%
Student > Bachelor 2 7%
Other 4 13%
Unknown 8 27%
Readers by discipline Count As %
Psychology 15 50%
Computer Science 3 10%
Social Sciences 2 7%
Neuroscience 2 7%
Unknown 8 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 750. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 March 2021.
All research outputs
#15,547
of 18,945,734 outputs
Outputs from Cognitive Research: Principles and Implications
#2
of 230 outputs
Outputs of similar age
#427
of 333,396 outputs
Outputs of similar age from Cognitive Research: Principles and Implications
#1
of 40 outputs
Altmetric has tracked 18,945,734 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 230 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.3. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 333,396 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.