We show that Gabor filter representations give quantitatively
indistinguishable results for classification of facial expressions as local
PCA representations, in contrast to other recent work. We also show that a
simple discriminant analysis automatically locates regions roughly
corresponding to relevant Facial Actions. Finally, we in troduce a method that
typically boosts generalization performance 9% by "peeking" at all of the
unlabeled training patt erns before classifying them.
Pre-2018 CSE ID: CS1999-0629
