More than a sum of parts: Robust face recognition by integrating variation

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Abstract

Familiarity incrementally improves our ability to identify faces. It has been hypothesized that this improvement reflects the refinement of memory representations which incorporate variation in appearance across encounters. Although it is established that exposure to variation improves face identification accuracy, it is not clear how variation is assimilated into internal face representations. To address this, we used a novel approach to isolate the effect of integrating separate exposures into a single-identity representation. Participants (n=113) were exposed to either a single video clip or a pair of video clips of target identities. Pairs of video clips were presented as either a single identity (associated with a single name, e.g. Betty-Sue) or dual identities (associated with two names, e.g. Betty and Sue). Results show that participants exposed to pairs of video clips showed better matching performance compared with participants trained with a single clip. More importantly, identification accuracy was higher for faces presented as single identities compared to faces presented as dual identities. This provides the first direct evidence that the integration of information across separate exposures benefits face matching, thereby establishing a mechanism that may explain people’s impressive ability to recognize familiar faces.

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APA

Menon, N., Kemp, R. I., & White, D. (2018). More than a sum of parts: Robust face recognition by integrating variation. Royal Society Open Science, 5(5). https://doi.org/10.1098/rsos.172381

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