Facial Expression Recognition Algorithm Based on Multi-scale Feature Deep Learning
Recognizing emotions through facial expressions has been widely applied in normal life.Among deep learning algo-rithms,Convolutional Neural Networks(CNN)have achieved great success in the field of facial expression recognition.However,it still faces the problem of information redundancy and data deviation,which affects the performance of facial expression recognition algorithm.Therefore,a Multi-scale Image Convolutional Network(GCN)based on landmarks extracted from facial images is pro-posed.The proposed method is simulated on CK+,JAFFE,FER2013 and RAF-DB datasets.The results show that the proposed method is superior to AUDN,BDBN,SCNN and other traditional deep learning frameworks,and has higher accuracy on different data sets.
万方数据
维普
