Feature Fusion Algorithm for Facial Expression Recognition
Wending Liu · 2009
The facial expression image were segmented to form the eyebrows,eyes and mouth areas,and these areas were computed with Higher-order Local Auto-Correlations method,through which the Weighted Principal Component Analysis values of these areas were obtained according to facial expression measure system Face Action Coding System(FACS) in psychology.In classification part,minimum-distance classifier was used to recognize different expressions.Based on the CMU-PITTSBURGH AU-Coded Face Expression Image Database,the results showed that the features fusing method was superior to PCA-based method.