Affiliation:
1. University of Guelph-Humber, Canada
Abstract
Recognition of unfamiliar faces is difficult in part due to variations in expressions, angles, and image quality. Studies suggest shape and surface properties play varied roles in face learning, and identification of unfamiliar faces uses diagnostic pigmentation/surface reflectance relative to shape information. Here, participants sorted photo-cards of unfamiliar faces by identity, which were shown in their original, stretched, and contrast-negated forms, to examine the utility of diagnostic shape and surface properties in sorting unfamiliar faces by identity. In four experiments, we varied the presentation order of conditions ( contrast-negated first or original first with stretched second across experiments) and whether the same or different photo-cards were seen across conditions. Stretching the images did not impair performance in any measures relative to other conditions. Contrast negation generally exacerbated poor sorting by identity compared with the other conditions. However, seeing the contrast-negated photo-cards last mitigated some of the effects of contrast negation. Together, results suggest an important role for surface properties such as pigmentation and reflectance for sorting by identity and add to literatures on informational content and appearance variability in discrimination of facial identity.
Funder
University of Guelph-Humber Research Grant
Subject
Artificial Intelligence,Sensory Systems,Experimental and Cognitive Psychology,Ophthalmology
Cited by
1 articles.
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