Deep Learning Methods for Facial Expression Recognition

Abstract

Deep learning is very popular methods for facial expression recognition (FER) and classification. Different types of deep learning algorithms have been used for FER such as deep belief network (DBN) and convolutional neural network (CNN). In this paper, we analyze various deep learning methods and their results. We have chosen Deep convolutional neural network as the best algorithms for facial expression detection and classification. In our study, we have tested the algorithm using Japanese Female facial expressions database (JAFFE) datasets by anaconda software. The deep convolution neural networks with JAFFE datasets accuracy rate around 97.01%.