Face-Information Sampling in Super-Recognizers

Abstract

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.

Let's talk about faces: Identifying faces from verbal descriptions

“…An extreme groups design provided more statistical power to detect an effect of face identification skill on face communication ability, if one exists (Feldt, 1961 ). This is consistent with the approach used in many other studies of individual differences in face perception (see White & Burton, 2022 for a review) and with evidence that super‐recognizers superior ability exists on a continuum of ability with typical viewers (Dunn et al, 2022 ; Noyes et al, 2017 ).…”

Selecting police super-recognisers

“…Given that super-recognisers sample more information from faces [ 42 ] and make identity decisions relatively quickly [ 23 ], we predicted that their advantage over controls would be greatest for photoboards containing multiple images of the same face, which would enable them to construct more detailed identity representations in memory. Results did not support this prediction, with super-recognisers (SR-Weak) showing the same advantage over Controls in 1 images and 8 image conditions (main effect of photoboard size: F (1, 59) = 11.04, p = .002, η p 2 = .16; non-sig interaction: F (1, 59) < 1, p = .933, η p 2 = .00; see S1 Appendix for further details).…”

Looking at faces in the wild

“…For example, many lab-based studies have found associations between face-processing ability and face information sampling patterns (e.g. 4,[66][67][68][69][70][71] for a review see 72 ). Relatedly, developmental disorders have been associated with abonomal social attention in laboratory-based studies (e.g.…”

“…For the face-to-face interaction task, we processed gaze data using landmark and heatmap registration methods. Participant heatmaps were analysed using principal components analysis (PCA) to identify major components (PCs) in the inter-individual variation of heatmaps, returning a set of PCs ranked according to their explained variance (see also 64 , 66 ).The raw input data for the PCA is shown in Supplementary Materials (Fig. S4 ).…”

“…www.nature.com/scientificreports/ according to their explained variance (see also 64,66 ).The raw input data for the PCA is shown in Supplementary Materials (Fig. S4).…”