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Alison Campbell, James Tanaka; Task effects on perceived identity of unfamiliar faces in open card sorting.. Journal of Vision 2017;17(10):999. doi: 10.1167/17.10.999.
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© ARVO (1962-2015); The Authors (2016-present)
Face perception is tantamount to identity perception. While identity representations in memory can be engaged to categorize different images of a familiar face (e.g., Barack Obama, George Clooney) with little interference from superficial variations in appearance and lighting, images of an unfamiliar face can be categorized only on the basis of perceptual information in the image. The difference in identity perception in familiar and unfamiliar face images is captured in a face sorting task where observers often perceive different images of the same person as different identities, but only when the face is unfamiliar (e.g., Jenkins et al., 2011; Neil et al., 2016). The current research addresses whether the formation of sub-identities of unfamiliar persons are idiosyncratic or systematic and whether the nature of the sorting task itself influences judgements of identity. In this study, participants were presented with 40 face images either simultaneously or sequentially and asked to group the images according to identity. Replicating previous results (Jenkins et al., 2011), participants tended to overestimate the number of identities in the face images (M = 6.35, SD = 5.76; 2 identities in the set). Jaccard similarity coefficients showed that participants in the simultaneous group were reliably more accurate than participants in the sequential group (p = .01). Hierarchical cluster analysis revealed shared sorting strategies amongst participants, however categorization structures diverged across conditions with respect to both the size and composition of the clusters. Results suggest that perceived identity of an unfamiliar face may be based on predictable parameters (e.g. hair, makeup, lighting), but that those parameters may change depending on the demands and procedures of the categorization task.
Meeting abstract presented at VSS 2017
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