Facial Expression Recognition Based on Gabor Features and Fuzzy Classifier

Xi Bin Jia; Chun Cheng Wen

doi:10.4028/www.scientific.net/AMM.182-183.1046

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 182-183Facial Expression Recognition Based on Gabor...

Facial Expression Recognition Based on Gabor Features and Fuzzy Classifier

Abstract:

A novel facial expression recognition method based on Gabor features and fuzzy classifier is proposed. Gabor wavelet is employed for feature extraction because it has good characteristics, which make it very suitable for the area of facial expression recognition. Because high-dimensional Gabor features are quite redundant, DCT and 2DPCA are respectively used to reduce dimensions and select valid features. Finally, expressions are recognized with fuzzy k-nearest neighbor classifier, which is demonstrated to be a more effective classifier. The experimental results show that the proposed method has high computational speed and good recognition rate.

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Periodical:

Applied Mechanics and Materials (Volumes 182-183)

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1046-1050

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.182-183.1046

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Online since:

June 2012

Authors:

Xi Bin Jia, Chun Cheng Wen

Keywords:

Facial Expression Recognition, Feature Extraction, Fuzzy Classifier

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