Figure 1

Recognition performances using Linear Fisher Discriminant Analysis.

Identity trained Fisherface projections were applied to identity (ID:ID), sex (ID:SE), race (ID:RA) and facial expression (ID:EX); facial expression trained Fisherface projections were applied to facial expression (EX:EX), identity (EX:ID) and sex (EX:SE); sex trained Fisherface projections were applied to sex (SE:SE) and facial expression (SE:EX). (A) Percent correct classification for identity, sex and race properties. Color-codes of the boxplots refer to the facial properties tested; i.e. blue = identity, green = sex, red = race. (B) Percent correct classification for facial expression and identity properties. Color-codes of the boxplots refer to the facial properties tested; i.e. blue = facial expression, green = identity. (C). Percent correct classification for sex and facial expression properties. Color-codes of the boxplots refer to the facial properties tested; i.e. red = sex. (A–C). Notches in boxplots indicate whether medians (red horizontal bars) are significantly different from each other. Non-overlapping notch intervals are significant at the 5% level. Whisker intervals cover +/−2.7 standard deviations (i.e. 99.3% in normally distributed data).