Facial expression recognition method based on multi-channel fusion and lightweight neural network

Abstract

The invention provides a facial expression recognition method based on multi-channel fusion and a lightweight neural network, and aims to solve the problems that in a traditional facial expression recognition learning method, the feature extraction process is complex, and deeper high semantic features and deep features cannot be obtained from an original image. According to the facial expression recognition method based on the multi-channel fusion and the lightweight neural network, a three-channel feature image after multi-channel fusion is used as the input of the constructed lightweight neural network, the design idea of deep separable convolution is adopted to reduce the number of parameters and the amount of calculation, and meanwhile, a residual connection mechanism is adopted to construct a network model to solve the problems of network performance degradation and gradient disappearance, so that good performance can be ensured while a deeper network is trained. Experiments show that the model provided by the invention can effectively extract facial expression features and classify expressions, and has good accuracy and robustness.

Description

technical field [0001] The invention belongs to the technical field of facial expression recognition, and in particular relates to a facial expression recognition method based on multi-channel fusion and a lightweight neural network. Background technique [0002] In recent years, machine learning has developed rapidly in the field of artificial intelligence. How to make computers better understand human emotions and further change the relationship between humans and computers has attracted more and more attention from researchers. Psychologist A. Mehrabian's research shows that in the communication between people, the information conveyed by facial expressions occupies a very large proportion, as high as 55%, while only 7% of the proportion depends on the content of the speaker. It can be seen that facial expressions play a vital role in human-to-human communication. Expression recognition is an interdisciplinary subject spanning physiology, neurology, computer science and ...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problem of difficult and incomplete feature extraction in traditional methods, the purpose of the present invention is to provide a facial expression recognition method based on multi-channel fusion and lightweight neural network, thereby further extracting more complete image features, Improve the accuracy and robustness of facial expression recognition

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