Bimodal emotion recognition method and system based on 3D convolutional neural networks

Abstract

The invention discloses a bimodal emotion recognition method and system based on 3D convolutional neural networks. According to the method, first, two 3D convolutional neural networks for face emotionrecognition and body gesture emotion recognition are constructed respectively, and network model parameters are optimized based on a training set and a verification set of a bimodal face and body gesture database; second, the two neural networks obtained after optimization are tested based on a test set of the bimodal face and body gesture database to obtain a face emotion recognition confusion matrix and a body gesture emotion recognition confusion matrix; and last, priori knowledge of the face emotion recognition confusion matrix and the body gesture emotion recognition confusion matrix isutilized to fuse bimodal recognition results of a newly input face video sequence and body gesture video sequence, and a bimodal emotion classification result is obtained. Through the method, the 3D convolutional neural networks and a bimodal fusion algorithm are adopted, the subjectivity of manual feature design is avoided, the limitation of single-modal emotion recognition is overcome, and the accuracy and robustness of emotion recognition can be effectively improved.

Description

technical field [0001] The invention belongs to the field of machine learning and pattern recognition, and relates to a video emotion recognition method and system, in particular to a dual-mode emotion recognition method and system based on a 3D convolutional neural network. Background technique [0002] With the rapid development of science and technology, human beings rely more and more on computers, and the ability of human-computer interaction has been valued by researchers. One of the important goals of the development of computer science is how to realize the anthropomorphic computer, which has become a hot issue in this field. A key problem that needs to be solved in human-computer interaction is to realize the computer's emotion recognition ability. [0003] Emotion recognition ability is an important aspect of computer intelligence, which reflects the computer's ability to judge the emotional state of the operator or interlocutor through the acquired information. ...

AI Technical Summary

Problems solved by technology

The biggest problem with this method is that it is impossible to extract effective human trunk motion features, and it is difficult to establish an effective human trunk motion feature library and facial expression feature library.

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