Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.578592
Title: Within-person variability in facial appearance
Author: Cursiter, Heather J.
Awarding Body: University of Glasgow
Current Institution: University of Glasgow
Date of Award: 2013
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Abstract:
Within-person variability has largely been neglected in face processing research, with research typically focusing instead on between-person variability. In experimental settings between-person variability often becomes between-image variability with research using one image to represent a face. This implies that an image is an adequate representation of a face, however one image cannot illustrate the variability that can occur in facial appearance. This thesis argues that overlooking within-person variability is a fundamental flaw in face processing research, as within-person variability is surprisingly large. The experiments in this thesis illustrate the effect of within-person variability in different face processing contexts: face identification, face perception and image memory. Experiments 1 – 7 demonstrate the difficulty of identifying familiar and unfamiliar faces across within-person variability using an image-sorting task. Experiment 8 illustrates the within-person variability that occurs in personality perception, and Experiments 9 and 10 illustrate the within-person variability that occurs in the perception of facial attractiveness. Lastly Experiments 11 and 12 introduce within-person variability to memory recognition and demonstrate the difficulties of remembering multiple images of the same face. From the results of Experiments 1 – 12 it is concluded that within-person variability is highly influential in all the discussed areas of face processing and therefore needs to be taken seriously in face processing research.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.578592  DOI: Not available
Keywords: BF Psychology
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