Identity From Variation: Representations of Faces Derived From Multiple Instances

Burton, A. Mike; Kramer, Robin S. S.; Ritchie, Kay L.; Jenkins, Rob

doi:10.1111/cogs.12231

Cited by 195 publications

(298 citation statements)

References 54 publications

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“…First, the results of two experiments show that high within-person variability improves both face perceptual discrimination and recognition abilities. Individual faces vary idiosyncratically (Burton, Kramer, Ritchie, & Jenkins, 2015) and so exposure to high ranges of variability in images of a given person might grant insights into the dimensions on which their face varies or remains stable.…”

Section: Discussionmentioning

confidence: 99%

Within-person variability promotes learning of internal facial features and facilitates perceptual discrimination and memory

Robins¹,

Susilo²,

Ritchie³

et al. 2018

Preprint

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Recent research indicates that exposure to within-person variability is essential for developing robust representations of new faces. For example, people perform better on a face matching task after exposure to highly variable photos, compared to less variable photos. However, the specific aspects of face processing that benefit from variability remain unclear. We investigated whether within-person variability improves the ability to match and recognise individual faces, and whether it promotes learning of internal facial features. In one exploratory and one confirmatory experiments, we tested matching and recognition performance of participants after they learned 4 individual faces in a high variability condition and another 4 in a low variability condition. Further, to assess if variability promotes robust learning of invariant facial features (e.g., eyes, nose), we compared performance with and without external facial features (full headshots vs cropped images showing only internal features). We found a large benefit of variability in the recognition task, and a smaller effect on the matching task, but the size of the benefit was comparable with and without the presence of external features. Therefore, within-person variability improves a variety of face recognition skills, and it encourages the encoding of internal facial features.

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Section: Discussionmentioning

confidence: 99%

Within-person variability promotes learning of internal facial features and facilitates perceptual discrimination and memory

Robins¹,

Susilo²,

Ritchie³

et al. 2018

Preprint

Self Cite

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“…Ratings for different photos of the same person can vary more than for photos of different people (Jenkins et al, 2011;Todorov & Porter, 2014). First impressions derived from faces can therefore reflect differences in photos rather than differences in people (Burton, 2013;Burton et al, 2016).…”

Section: Research Aimsmentioning

confidence: 99%

Audiovisual integration in social evaluation.

Mileva

Tompkinson

Watt

et al. 2018

Journal of Experimental Psychology: Human Perception and Perfor

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Our social evaluation of other people is influenced by their faces and their voices. However, rather little is known about how these channels combine in forming 'first impressions'. Over five experiments we investigate the relative contributions of facial and vocal information for social judgements: dominance and trustworthiness. The experiments manipulate each of these sources of information within-person, combining faces and voices giving rise to different social attributions. We report that vocal pitch is a reliable source of information for judgements of dominance (Study 1) but not trustworthiness (Study 4). Faces and voices make reliable, but independent contributions to social evaluation. However, voices have the larger influence in judgements of dominance (Study 2), whereas faces have the larger influence in judgements of trustworthiness (Study 5). The independent contribution of the two sources appears to be mandatory, as instructions to ignore one channel do not eliminate its influence (Study 3). Our results show that information contained in both the face and the voice contributes to first impression formation. This combination is, to some degree, outside conscious control, and the weighting of channel contribution varies according the trait being perceived.

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“…Given the likely difficulty in recruiting a group of people to select images that are representative of appearance, one possibility is to bypass human judgments altogether and to instead select optimal images sets via image statistics (cf. Burton et al, 2016) or algorithm-computed match scores (Scheirer et al, 2011). However, computational solutions to the problem of selecting ideal biometric samples are also elusive (Beveridge et al, 2011).…”

Section: Discussionmentioning

confidence: 99%

“…For example, recent analysis of withinidentity variation in appearance shows that dimensions of variance are often idiosyncratic to individual faces (cf. Burton, Kramer, Ritchie, & Jenkins, 2016), suggesting that the problem of selecting representative photographs is a qualitatively different challenge.…”

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confidence: 99%

Not looking yourself: The cost of self‐selecting photographs for identity verification

White

Burton

Kemp

2015

British J of Psychology

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Photo-identification is based on the premise that photographs are representative of facial appearance. However, previous studies show that ratings of likeness vary across different photographs of the same face, suggesting that some images capture identity better than others. Two experiments were designed to examine the relationship between likeness judgments and face matching accuracy. In Experiment 1, we compared unfamiliar face matching accuracy for self-selected and other-selected high-likeness images. Surprisingly, images selected by previously unfamiliar viewers - after very limited exposure to a target face - were more accurately matched than self-selected images chosen by the target identity themselves. Results also revealed extremely low inter-rater agreement in ratings of likeness across participants, suggesting that perceptions of image resemblance are inherently unstable. In Experiment 2, we test whether the cost of self-selection can be explained by this general disagreement in likeness judgments between individual raters. We find that averaging across rankings by multiple raters produces image selections that provide superior identification accuracy. However, benefit of other-selection persisted for single raters, suggesting that inaccurate representations of self interfere with our ability to judge which images faithfully represent our current appearance.

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Identity From Variation: Representations of Faces Derived From Multiple Instances

Cited by 195 publications

References 54 publications

Within-person variability promotes learning of internal facial features and facilitates perceptual discrimination and memory

Within-person variability promotes learning of internal facial features and facilitates perceptual discrimination and memory

Audiovisual integration in social evaluation.

Not looking yourself: The cost of self‐selecting photographs for identity verification

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