The Research And Implementation Of Facial Expression Recognition Based On Deep Learning

Facial expression recognition is a challenging research topic in the field of compute vision and pattern recognition.Facial expression recognition has been a hot research field and has a wide range of applications,such as human-computer interaction,security monitoring,lie detection and so on.With the development of the technology,especially since 2006,with the rapid development of Deep Learning technology,eliminating the need for manual design and feature extraction steps for large data sample training and automatic learning characteristics,and thus greatly improve the accuracy and adaptability of algorithm model.Therefore,facial expression recognition based on deep learning has become a hot topic.This paper studies the expression classification of two dimensional face images.This paper proposes a facial expression recognition algorithm based on noise reduction self-encoder,which can effectively reduce the degree of interference between expressions while improving the recognition accuracy.A light convolutional neural network is designed to recognize facial expressions quickly and effectively.A method of expression recognition based on convolution neural network and Recurrent neural network is proposed.At the same time,a data filtering framework and two relatively simple data filtering methods are proposed to preprocess the data.