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Technical Program
Paper Detail
| Paper: | MP-L4.5 |
| Session: | Face/Facial Expression Detection and Recognition |
| Time: | Monday, October 9, 16:00 - 16:20 |
| Presentation: |
Lecture
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| Title: |
FACIAL EXPRESSION RECOGNITION USING ADVANCED LOCAL BINARY PATTERNS, TSALLIS ENTROPIES AND GLOBAL APPEARANCE FEATURES |
| Authors: |
Shu Liao; Hong Kong University of Science and Technology | | | | | Wei Fan; Hong Kong University of Science and Technology | | | | | Albert C.S. Chung; Hong Kong University of Science and Technology | | | | | Dit-Yan Yeung; Hong Kong University of Science and Technology | | |
| Abstract: |
This paper proposes a novel facial expression recognition approach based on two sets of features extracted from the face images: texture features and global appearance features. The first set is obtained by using the extended local binary patterns in both intensity and gradient maps and computing the Tsallis entropy of the Gabor filtered responses. The second set of features is obtained by performing nullspace based linear discriminant analysis on the training face images. The proposed method is evaluated by extensive experiments on the JAFFE database, and compared with two widely used facial expression recognition approaches. Experimental results show that the proposed approach maintains high recognition rate in a wide range of resolution levels and outperforms the other alternative methods. |
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