Portraits and perception: configural information in creating and recognizing face images.

Configural information has long been considered important for face recognition. However, traditional portraiture instruction encourages the artist to use a 'generic' configuration for faces rather than attempting to replicate precise feature positions. We examine this intriguing paradox with two tasks designed to test the extent to which configural information is incorporated into face representations. In Experiment 1, we use a simplified face production task to examine how accurately feature configuration can be incorporated in the generated likenesses. In Experiment 2, we ask if the 'portraits' created in Experiment 1 are discriminable from veridical images. The production and recognition results from these experiments show a consistent pattern. Subjects are quite poor at arranging facial features (eyes, nose and mouth) in their correct locations, and at distinguishing erroneous configurations from correct ones. This seeming insensitivity to configural relations is consistent with artists' practice of creating portraits based on a generic geometric template. Interestingly, the frame of reference artists implicitly use for this generic template - the external face contour - emerges as a significant modulator of performance in our experimental results. Production errors are reduced and recognition performance is enhanced in the presence of outer contours. We discuss the implications of these results for face recognition models, as well as some possible perceptual reasons why portraits are so difficult to create.