Enhancing images of facial expressions

Facial images can be enhanced by application of an algorithm--the caricature algorithm--that systematically manipulates their distinctiveness (Benson & Perrett, 1991c; Brennan, 1985). In this study, we first produced a composite facial image from natural images of the six facial expressions of fear, sadness, surprise, happiness, disgust, and anger shown on a number of different individual faces (Ekman & Friesen, 1975). We then caricatured the composite images with respect to a neutral (resting) expression. Experiment 1 showed that rated strength of the target expression was directly related to the degree of enhancement for all the expressions. Experiment 2, which used a free rating procedure, found that, although caricature enhanced the strength of the target expression (more extreme ratings), it did not necessarily enhance its purity, inasmuch as the attributes of nontarget expressions were also enhanced. Naming of prototypes, of original exemplar images, and of caricatures was explored in Experiment 3 and followed the pattern suggested by the free rating conditions of Experiment 2, with no overall naming advantage to caricatures under these conditions. Overall, the experiments suggested that computational methods of compositing and caricature can be usefully applied to facial images of expression. Their utility in enhancing the distinctiveness of the expression depends on the purity of expression in the source image.