Survey on Facial Expression Recognition: History, Applications, and Challenges

被引:12
|
作者
Zhao, Xibin [1 ]
Zhu, Junjie [2 ]
Luo, Bingjun [2 ]
Gao, Yue [1 ]
机构
[1] Tsinghua Univ, Sch Software, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Beijing 100084, Peoples R China
关键词
Feature extraction; Generative adversarial networks; Face recognition; Deep learning; Vehicles; History; Roads;
D O I
10.1109/MMUL.2021.3107862
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Facial expressions are most important channels for transmitting affective information in human interaction. In the early 1970s, due to the limitation of weak computing power and powerless algorithms, automatic facial expression recognition (AFER) entered the freezing period for a long time. However, with the geometrical growth of computing power and the rapid improvement of algorithms, the accuracy of AFER has been significantly enhanced. FER has ushered in the flowering and fruitful application in different fields such as medical treatment, transportation, and business. This article introduces and surveys these recent advances. We first provide a detailed review of the related studies in FER, including emotion representation, well-known datasets, and FER's history. Next, we detailed the background and practical significance of FER technology's application in different fields. We finally summarize some of the scientific and engineering challenges to promote better use of FER in real-world applications.
引用
收藏
页码:38 / 44
页数:7
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