An analysis of facial expression recognition under partial facial image occlusion

2008 ◽  
Vol 26 (7) ◽  
pp. 1052-1067 ◽  
Author(s):  
Irene Kotsia ◽  
Ioan Buciu ◽  
Ioannis Pitas
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Facial Image

scholarly journals Improved Facial Expression Recognition Based on DWT Feature for Deep CNN

Electronics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 324 ◽  
Author(s):  
Ridha Bendjillali ◽  
Mohammed Beladgham ◽  
Khaled Merit ◽  
Abdelmalik Taleb-Ahmed
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Facial Expression Recognition ◽  
Histogram Equalization ◽  
Detection Algorithm ◽  
Discrete Wavelet ◽  
Expression Recognition ◽  
Facial Image ◽  
Illumination Changes ◽  
The Face

Facial expression recognition (FER) has become one of the most important fields of research in pattern recognition. In this paper, we propose a method for the identification of facial expressions of people through their emotions. Being robust against illumination changes, this method combines four steps: Viola–Jones face detection algorithm, facial image enhancement using contrast limited adaptive histogram equalization (CLAHE) algorithm, the discrete wavelet transform (DWT), and deep convolutional neural network (CNN). We have used Viola–Jones to locate the face and facial parts; the facial image is enhanced using CLAHE; then facial features extraction is done using DWT; and finally, the extracted features are used directly to train the CNN network, for the purpose of classifying the facial expressions. Our experimental work was performed on the CK+ database and JAFFE face database. The results obtained using this network were 96.46% and 98.43%, respectively.

scholarly journals A Facial Expression Recognition Algorithm Based on Local Binary Pattern and Empirical Mode Decomposition

2014 ◽  
Vol 8 (1) ◽  
pp. 599-604
Author(s):  
Hong Yang ◽  
Deli Zhu
Keyword(s):  
Facial Expression ◽  
Empirical Mode Decomposition ◽  
High Frequency ◽  
Facial Expression Recognition ◽  
Local Binary Pattern ◽  
Recognition Algorithm ◽  
Expression Recognition ◽  
Facial Image ◽  
Mode Decomposition ◽  
Full Face

To improve the efficiency of facial expression recognition, this paper puts forward a kind of recognition algorithm based on local binary pattern (LBP) and empirical mode decomposition (EMD). First of all, process the empirical mode decomposition into the preprocessing facial image, and bring forward many a high frequency images instead of the original image; then, divide the sub domain of the high frequency image and obtain the sub domain LBP histogram and full face histogram; finally, identify the expression of the generated LBP histogram. Through the experiment on JAFFE database, it shows that the method is effective for facial expression recognition.

Graph-based dynamic ensemble pruning for facial expression recognition

2019 ◽  
Vol 49 (9) ◽  
pp. 3188-3206 ◽  
Author(s):  
Danyang Li ◽  
Guihua Wen ◽  
Xu Li ◽  
Xianfa Cai
Keyword(s):  
Facial Expression ◽  
Facial Expression Recognition ◽  
Expression Recognition ◽  
Ensemble Pruning
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