PCA = Gabor for Expression Recognition
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PCA = Gabor for Expression Recognition

  • Author(s): Dailey, Matthew N;
  • Cottrell, Garrison W
  • et al.
Abstract

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

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