We used highly variable, so-called ‘ambient’ images to test whether expressions affect the identity recognition of real-world facial images. Using movie segments of two actors unknown to our participants, we created image pairs – each image within a pair being captured from the same film segment. This ensured that, within pairs, variables such as lighting were constant whilst expressiveness differed. We created two packs of cards, one containing neutral face images, the other, their expressive counterparts. Participants sorted the card packs into piles, one for each perceived identity. As with previous studies, the perceived number of identities was higher than the veridical number of two. Interestingly, when looking within piles, we found a strong difference between the expressive and neutral sorting tasks. With expressive faces, identity piles were significantly more likely to contain cards of both identities. This finding demonstrates that, over and above other image variables, expressiveness variability can cause identity confusion; evidently, expression is not disregarded or factored out when we classify facial identity in real-world images. Our results provide clear support for a face processing architecture in which both invariant and changeable facial information may be drawn upon to drive our decisions of identity.
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