Literature DB >> 21890124

Variability in photos of the same face.

Rob Jenkins1, David White, Xandra Van Montfort, A Mike Burton.   

Abstract

Psychological studies of face recognition have typically ignored within-person variation in appearance, instead emphasising differences between individuals. Studies typically assume that a photograph adequately captures a person's appearance, and for that reason most studies use just one, or a small number of photos per person. Here we show that photographs are not consistent indicators of facial appearance because they are blind to within-person variability. Crucially, this within-person variability is often very large compared to the differences between people. To investigate variability in photos of the same face, we collected images from the internet to sample a realistic range for each individual. In Experiments 1 and 2, unfamiliar viewers perceived images of the same person as being different individuals, while familiar viewers perfectly identified the same photos. In Experiment 3, multiple photographs of any individual formed a continuum of good to bad likeness, which was highly sensitive to familiarity. Finally, in Experiment 4, we found that within-person variability exceeded between-person variability in attractiveness. These observations are critical to our understanding of face processing, because they suggest that a key component of face processing has been ignored. As well as its theoretical significance, this scale of variability has important practical implications. For example, our findings suggest that face photographs are unsuitable as proof of identity.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21890124     DOI: 10.1016/j.cognition.2011.08.001

Source DB:  PubMed          Journal:  Cognition        ISSN: 0010-0277


  97 in total

1.  FFA and OFA Encode Distinct Types of Face Identity Information.

Authors:  Maria Tsantani; Nikolaus Kriegeskorte; Katherine Storrs; Adrian Lloyd Williams; Carolyn McGettigan; Lúcia Garrido
Journal:  J Neurosci       Date:  2021-01-15       Impact factor: 6.167

2.  A data-driven approach to stimulus selection reveals an image-based representation of objects in high-level visual areas.

Authors:  David D Coggan; Afrodite Giannakopoulou; Sanah Ali; Burcu Goz; David M Watson; Tom Hartley; Daniel H Baker; Timothy J Andrews
Journal:  Hum Brain Mapp       Date:  2019-07-23       Impact factor: 5.038

3.  Repeated short presentations of morphed facial expressions change recognition and evaluation of facial expressions.

Authors:  Jun Moriya; Yoshihiko Tanno; Yoshinori Sugiura
Journal:  Psychol Res       Date:  2012-11-21

4.  Categorization training changes the visual representation of face identity.

Authors:  Fabian A Soto
Journal:  Atten Percept Psychophys       Date:  2019-07       Impact factor: 2.199

5.  Infrequent identity mismatches are frequently undetected.

Authors:  Megan H Papesh; Stephen D Goldinger
Journal:  Atten Percept Psychophys       Date:  2014-07       Impact factor: 2.199

6.  Modeling first impressions from highly variable facial images.

Authors:  Richard J W Vernon; Clare A M Sutherland; Andrew W Young; Tom Hartley
Journal:  Proc Natl Acad Sci U S A       Date:  2014-07-28       Impact factor: 11.205

7.  Person information facilitates memory for face identity.

Authors:  Katia Mattarozzi; Valentina Colonnello; Paolo Maria Russo; Alexander Todorov
Journal:  Psychol Res       Date:  2018-06-15

8.  The poverty of embodied cognition.

Authors:  Stephen D Goldinger; Megan H Papesh; Anthony S Barnhart; Whitney A Hansen; Michael C Hout
Journal:  Psychon Bull Rev       Date:  2016-08

9.  Pain modulation by your partner: An experimental investigation from a social-affective perspective.

Authors:  Katrin Hillmer; Judith Kappesser; Christiane Hermann
Journal:  PLoS One       Date:  2021-07-22       Impact factor: 3.240

10.  UNSW Face Test: A screening tool for super-recognizers.

Authors:  James D Dunn; Stephanie Summersby; Alice Towler; Josh P Davis; David White
Journal:  PLoS One       Date:  2020-11-16       Impact factor: 3.240

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