Summary: Superrecognizers focus less on the eye region and distribute their gaze more evenly than typical viewers, extracting more information from other facial features.
Source: APS
Super recognition never forgets a face. They can see their childhood friend in a rear-view mirror and instantly know it’s them. They help police departments and security agencies identify suspects. They also make good private detectives and unofficial investigators.
But as fascinating as their superpower is, it remains poorly understood. Until now, scientists thought super-recognizers were so good with faces because they holistically processed them by taking a snapshot of the face and memorizing it.
In an article published on August 31 in the journal Psychological sciencespsychologists from UNSW Sydney and the University of Wollongong (UOW) have challenged this view, proving that super-recognizers – who make up around 2% of society – look at faces like all of us, but do faster and more accurately.
How can this happen?
UNSW researcher and lead author of the study, Dr. James Dunn, explains that when super-recognizers see a new face, they break it up into parts and then store them in the brain as composite images.
“They are still able to recognize faces better than others, even when they can only see smaller regions at a time. This suggests that they can piece together an overall impression from small pieces, rather than from from a holistic impression taken at a single glance,” Dunn said.
For the purposes of the study, co-lead author Dr. Sébastien Miellet, a UOW researcher in the School of Psychology and an expert in active vision, used eye-tracking technology to analyze how super-recognition scans and deal with faces and their parts.
“With great precision, we can see not only where people are looking, but also what pieces of visual information they are using,” Miellet said.
When studying the visual processing patterns of superrecognizers, Dunn and Miellet realized that unlike typical recognizers, superrecognizers focused less on the eye region and distributed their gaze more evenly than typical viewers, extracting information of other facial features, especially when learning faces. .
“So the advantage of super-recognition is their ability to pick up very distinctive visual information and put all the pieces of a face together like a puzzle, quickly and accurately,” Miellet said.
UNSW and UOW researchers will continue to study the population of super-recognizers.
Miellet thinks one hypothesis is that the superpower of super-recognizers may come from a particular curiosity and behavioral interest in others. Potentially, super-grateful people can also be more empathetic than most of us.
“In the next stages of our study, we will equip some typical super-recognizers and viewers with a handheld eye tracker and release them into the streets to observe, not in the lab but in real life, how they interact with the world,” , said Miellet.
About this visual memory research news
Author: Lea Thayer
Source: APS
Contact: Lea Thayer – APS
Image: Image is in public domain
See also
Original research: Access closed.
“Facial information sampling in super-recognition” by Sébastien Miellet et al. Psychological sciences
Summary
Sampling facial information in super-recognition
The perceptual processes underlying individual differences in facial recognition ability remain poorly understood.
We compared the visual sampling of 37 adult super-recognizers—individuals with superior facial recognition ability—with that of 68 typical adult viewers by measuring gaze position as they learned and recognized unfamiliar faces. In both phases, participants viewed faces through “projector” apertures of varying size, with face information limited in real time around their point of fixation.
We found greater accuracy in super-recognition at all aperture sizes, showing that their superiority is not based on global sampling of face information, but is also evident when forced to adopt piecemeal sampling. Additionally, the super-recognizers fixed more, focused less on the eye area, and distributed their gaze more than typical viewers.
These differences were most apparent when learning faces and were consistent with trends we observed across the ability spectrum, suggesting that they reflect factors that vary dimensionally in the general population.
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