human behavior understanding
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Author(s):  
Padmapriya K.C. ◽  
Leelavathy V. ◽  
Angelin Gladston

The human facial expressions convey a lot of information visually. Facial expression recognition plays a crucial role in the area of human-machine interaction. Automatic facial expression recognition system has many applications in human behavior understanding, detection of mental disorders and synthetic human expressions. Recognition of facial expression by computer with high recognition rate is still a challenging task. Most of the methods utilized in the literature for the automatic facial expression recognition systems are based on geometry and appearance. Facial expression recognition is usually performed in four stages consisting of pre-processing, face detection, feature extraction, and expression classification. In this paper we applied various deep learning methods to classify the seven key human emotions: anger, disgust, fear, happiness, sadness, surprise and neutrality. The facial expression recognition system developed is experimentally evaluated with FER dataset and has resulted with good accuracy.



2021 ◽  
Author(s):  
Tianjiao Li ◽  
Jun Liu ◽  
Wei Zhang ◽  
Yun Ni ◽  
Wenqian Wang ◽  
...  


2021 ◽  
pp. 104185
Author(s):  
Xiaohua Huang ◽  
Abhinav Dhall ◽  
Guoying Zhao ◽  
Wenming Zheng ◽  
Matti Peitikänen


2021 ◽  
Vol 23 ◽  
pp. 415-428 ◽  
Author(s):  
Inwoong Lee ◽  
Doyoung Kim ◽  
Sanghoon Lee


Author(s):  
Cheng Dai ◽  
Xingang Liu ◽  
Hao Xu ◽  
Laurence Tianruo Yang ◽  
Jamal Deen


Author(s):  
Anis Kacem ◽  
Mohamed Daoudi ◽  
Boulbaba Ben Amor ◽  
Stefano Berretti ◽  
Juan Carlos Alvarez-Paiva




2019 ◽  
Vol 1 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Zhiwen Yu ◽  
He Du ◽  
Fei Yi ◽  
Zhu Wang ◽  
Bin Guo


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