A Review of Facial Expression Recognition
DOI:
https://doi.org/10.54097/fcis.v2i1.2969Keywords:
Expression recognition, Deep learning, Feature extractionAbstract
With the development of deep learning, deep learning is becoming more and more common for facial recognition. We summarize some widely used public data sets for facial expression recognition; The basic flow of facial expression recognition is briefly introduced. This paper mainly analyzes some existing deep learning methods, especially deep convolutional neural network. The structure analysis and performance comparison of four classical convolutional neural networks (AlexNet, GoogleNet, VGGNet and ResNet) are carried out. Finally, the present research on expression recognition is summarized and prospected.
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HINTON GE, OSINDE ROS, Teh YW. A fast learning algorithm for deep belief nets[J]. Neural computation, 2006, 18(7): 1527-1554.
LIU M, LI S, SHAN S, et al. Au-inspired deep networks for facial expression feature learning [J]. Neurocomputing,2015, 159: 126-136.
ZENG N, ZHANG H, SONG B, et al. Facial expression recognition via learning deep sparse autoencoders [J]. Neurocomputing, 2018, 273: 643-649.
DHALL A, GOECKE R, Lucey S, et al. Collecting Large, Richly Annotated Facial-Expression Databases from Movies[J]. IEEE Multimedia, 2012, 19(3): 34-41.
HE K, ZHANG X, REN S, et al. Deep Residual Learning for Image Recognition[C]. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015: 770-778.
SIMONYAN K, ZISSERMAN A. Very Deep Convolutional Networks for Large-Scale Image Recognition[J]. Computer Science, 2014, 1409(15): 1-9.
HUANG G, LIU Z, et al. Densely Connected Convolutional Networks[C], Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2017:4700-4708.
GIRSHICK R, DONAHUE J, DARRELL T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation [C]//Proceedings of the IEEE conference on computer vision and pattern recognition, 2014: 580-587.
CUI R, LIU M, LIU M. Facial expression recognition based on ensemble of mulitple CNNs [C]//Chinese Conference on Biometric Recognition. Springer, Cham, 2016: 511-518.
XIAO S, DING P, FUJI REN, Facial Expression recognition based on ROI-KNN convolutional neural network [J] , 2016, 42( 6): 883-891.
TRAN L, YIN X, LIU X. Disentangled representation learning gan for pose-invariant face recognition[C]// Proceedings of the IEEE conference on computer vision and pattern recognition, 2017: 1415-1424.
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