Authors:

CALDER, A.J., Burton, A.M., Miller, P. Young, A.W., & Akamatsu, S.

Reference:

Year of publication:

2001

CBU number:

4109

Abstract:

Pictures of facial expressions from the Ekman and Friesen (1976) set were submitted to a principal component analysis (PCA) of their pixel intensities. The output of the PCA was submitted to a series of linear discriminant analyses which revealed three principal findings: (i) a PCA-based system can support facial expression recognition, (ii) continuous two-dimensional models of emotion (e.g., Russell, 1980) are reflected in the statistical structure of the Ekman and Friesen facial expressions, and (iii) components for coding facial expression information are largely different to components for facial identity information. The implications for models of face processing are discussed.