Multiple Features Extraction and Coordination Using Gabor Wavelet Transformation and Fisherfaces with Application to Facial Expression Recognition

Author(s):  
Haibin Liu ◽  
Guobao Zhang ◽  
Yongming Huang ◽  
Fei Dong
2006 ◽  
Vol 06 (01) ◽  
pp. 125-138 ◽  
Author(s):  
YONGZHAO ZHAN ◽  
JINGFU YE ◽  
DEJIAO NIU ◽  
PENG CAO

Facial expression recognition technology plays an important role in research areas such as psychological studies, image understanding and virtual reality etc. In order to achieve subject-independent facial expression recognition and obtain robustness against illumination variety and image deformation, facial expression recognition methods based on Gabor wavelet transformation and elastic templates matching are presented in this paper. First given a still image containing facial expression information, preprocessors are executed which include gray and scale normalization. Secondly, Gabor wavelet filters are adopted to extract expression features. Then the elastic graph for expression features is constructed. Finally, elastic templates matching algorithm and K-nearest neighbors classifier are used to recognize facial expression. Experiments show that expression features can be extracted effectively by Gabor wavelet transformation, which is insensitive to illumination variety and individual difference, and high recognition rate can be obtained using elastic templates matching algorithm, which is subject-independent.


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