The invention relates to a multi-angle facial expression recognition method based on deep learning. The method comprises the following steps: preprocessing an acquired original image; positioning and cutting an expression area; face expression image feature extraction: inputting the preprocessed image into a VGGNet deep neural network model to perform feature extraction on the face expression image to obtain a feature map, and inputting the feature map into a neural network of four full connection layers to perform training; and face expression classification: classifying the images of the expressions obtained after training by adopting a Softmax layer, and determining a final expression. According to the method, the deep features of the expression image are extracted by using the VGGNet convolutional neural network, and the extracted features are input into the neural network with four full connection layers for training, so that the method has relatively high recognition rate in terms of loss value, accuracy, precision ratio and recall ratio through experimental results; therefore, the face recognition accuracy and the robustness of the algorithm are improved.
Multi-angle facial expression recognition method based on deep learning