Facial Expression Recognition Based on Gabor Wavelet Transform and Relevance Vector Machine

2014 ◽  
Vol 11 (1) ◽  
pp. 295-302 ◽  
Author(s):  
Jinxin Ruan
Keyword(s):  
Wavelet Transform ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Relevance Vector Machine ◽  
Gabor Wavelet ◽  
Expression Recognition ◽  
Gabor Wavelet Transform

Facial expression recognition based on Gabor wavelet transform and 2-channel CNN

2019 ◽  
Vol 18 (02) ◽  
pp. 2050003 ◽  
Author(s):  
Shu Qin ◽  
Zhengzhou Zhu ◽  
Yuhang Zou ◽  
Xiaowei Wang
Keyword(s):  
Wavelet Transform ◽  
Facial Expression ◽  
Facial Expression Recognition ◽  
Histogram Equalization ◽  
Medical Industry ◽  
Gabor Wavelet ◽  
Expression Recognition ◽  
Service Recommendation ◽  
Recognition Method ◽  
Gabor Wavelet Transform

Facial expression recognition is one of the hotspots in the fields of computer vision and deep learning. It has very important applications in the domains of learning service recommendation, human–computer interaction and medical industry. Aiming at the problem that the traditional expression recognition method is not accurate, this paper proposes a method combining Gabor wavelet transform and convolutional neural network. Firstly, face positioning, cropping, histogram equalization and other preprocessing are performed on the expression image. Then we extract key frames of expression sequences. After that the Gabor wavelet transform is performed on the expression image to obtain magnitude and phase characteristics. Finally, we design a 2-channel CNN for training and classification. The experiment achieves an accuracy of 96.81% on the CK+ database and it has a certain improvement compared with the Gabor wavelet transform and the traditional CNN alone.

Sign in / Sign up

Export Citation Format

Share Document