Face emotion analysis method and system based on multi-task learning and deep learning

Abstract

The face emotion analysis method and system based on multi-task learning and deep learning provided by the present invention include using a convolutional neural network to learn the convolution layer of a preset analysis task in a face database to obtain a face analysis model; A face image, using a face detection algorithm to analyze the face image to be analyzed, extracting the face area in the face image to be analyzed; using the face analysis model to predict the face image to be analyzed, and obtaining Emotional information corresponding to each face area in the face image to be analyzed. The present invention applies the concept of multi-task learning to the convolutional neural network, so that a variety of face-related analysis tasks can be identified with the same analysis model, which can reduce the size of the analysis model and speed up the recognition time. In addition, the present invention uses different convolutional layers to describe different parts of the face, so that the tasks of each convolutional layer are relatively single and specialized, and better recognition effects can be achieved.

Description

technical field [0001] The invention belongs to the technical field of computer vision and human-computer interaction image processing, and specifically relates to a face emotion analysis method based on multi-task learning and deep learning. Background technique [0002] With the development of computer vision technology, more and more related technologies have been applied in the context of human-computer interaction in recent years, especially emotional computing. Through the automatic facial emotion recognition system, people's emotions can be understood more easily, so that people can quickly and directly obtain user emotional feedback through computers, thereby improving the quality of human-computer interaction. [0003] In the existing facial emotion recognition system, the common method is to extract low-level feature values ​​from the facial image after capturing the facial image, and then use machine learning to train a classifier for emotional classification (suc...

AI Technical Summary

Problems solved by technology

Although the face action unit and emotional space have been widely used in the task of face emotion recognition, and can achieve good results, each still has some limitations.

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