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Facial Expression Recognition Using Convolutional Neural Network

Facial expressions are part of human language and are often used to convey emotions. With the development of human-computer interaction technology, people pay more and more attention to facial expression recognition (FER) technology. Besides, in the domain of FER, human beings have made some progress. In this paper, we reviewed the development of FER: VGGNet, ResNet, GoogleNet, and AlexNet. Besides, we studied some ideas of CNN (Convolutional Neural Network), and we used FER2013, which is one of the most significant databases of human faces, as the dataset to be considered. Furthermore, we made some improvements based on the original methods of FER. By training the FER2013 dataset with different revised ways, the best result of accuracy we got is 0.6424. At last, we generated and summarized the progress and deficiencies in this study.