Face-Information Sampling in Super-Recognizers

Perceptual processes underlying individual differences in face-recognition ability remain poorly understood. We compared visual sampling of 37 adult super-recognizers—individuals with superior face-recognition ability—with that of 68 typical adult viewers by measuring gaze position as they learned a...

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Veröffentlicht in:Psychological science 2022-09, Vol.33 (9), p.1615-1630
Hauptverfasser: Dunn, James D., Varela, Victor P. L., Nicholls, Victoria I., Papinutto, Michael, White, David, Miellet, Sebastien
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container_end_page 1630
container_issue 9
container_start_page 1615
container_title Psychological science
container_volume 33
creator Dunn, James D.
Varela, Victor P. L.
Nicholls, Victoria I.
Papinutto, Michael
White, David
Miellet, Sebastien
description Perceptual processes underlying individual differences in face-recognition ability remain poorly understood. We compared visual sampling of 37 adult super-recognizers—individuals with superior face-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 “spotlight” apertures that varied in size, with face information restricted in real time around their point of fixation. We found higher accuracy in super-recognizers at all aperture sizes—showing that their superiority does not rely on global sampling of face information but is also evident when they are forced to adopt piecemeal sampling. Additionally, super-recognizers made more fixations, focused less on eye region, 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 broader ability spectrum, suggesting that they are reflective of factors that vary dimensionally in the broader population.
doi_str_mv 10.1177/09567976221096320
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subjects Ability
Acknowledgment
Eye fixation
Fixation
Individual differences
Sampling
Viewers
title Face-Information Sampling in Super-Recognizers
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