Perceptual recognition of facial affect: Cross-cultural comparisons

Abstract

Previous research has shown that the perception of affect in faces is well described by the fuzzy logical model of perception (FLMP). In this study, we asked whether the processes involved in recognition depended on the race/culture of the face and/or of the perceiver. A computer-generated face was used to manipulate two features of facial affect: brow deflection and mouth deflection. An expanded-factorial design was used, with four levels of brow deflection crossed with four levels of mouth deflection, as well as their corresponding half-face conditions. Participants identified these faces as either happy or angry. Japanese and U.S. students were tested on faces from these two countries that were texture-mapped onto the animated face. The FLMP gave the best description of performance for both groups and for both types of faces. These findings challenge previous claims of holistic perception, categorical perception, and additive feature integration.