Facial emotion recognition method based on deep sparse convolutional neural network

A convolutional neural network, convolutional neural technology, applied in biological neural network models, character and pattern recognition, acquisition/recognition of facial features, etc., can solve problems such as poor local optimal value and poor neural network generalization performance

Inactive Publication Date: 2017-12-22
CHINA UNIV OF GEOSCIENCES (WUHAN)
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Problems solved by technology

In deep learning, the choice of optimization algorithm is very important. In some previous studies, only the setting of the network structure was emphasized. The traditional gradient descent algorithm is easy to fall into a poor local optimum, resulting in poor generalization performance of the neural network. Difference

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  • Facial emotion recognition method based on deep sparse convolutional neural network
  • Facial emotion recognition method based on deep sparse convolutional neural network
  • Facial emotion recognition method based on deep sparse convolutional neural network

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Embodiment Construction

[0095] The present invention will be further described below in conjunction with drawings and embodiments.

[0096] The present invention provides a face emotion recognition method based on deep sparse convolutional neural network, and its overall flow chart is as follows figure 1 shown. Firstly, image preprocessing is performed on the emotional image samples, that is, the direction of the face is corrected and cropped, and histogram equalization is implemented; then the underlying emotional features are extracted based on PCA; finally, the constructed deep sparse convolutional neural network is used for mining and learning High-level emotional features are identified and classified, and NAGD is used to train and optimize network weights to optimize the entire network structure, thereby improving the performance of facial emotion recognition.

[0097] The facial emotion recognition method based on deep sparse convolutional neural network can be divided into three parts, namel...

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Abstract

The invention provides a facial emotion recognition method based on a deep sparse convolutional neural network. The method comprises the following steps: to begin with, carrying out emotion image preprocessing; then, carrying out emotion feature extraction; and finally, carrying out emotion feature identification and classification. The facial emotion recognition method based on the deep sparse convolutional neural network carries out optimization on weight of the deep sparse convolutional neural network through a Nesterov accelerated gradient descent algorithm to enable network structure to be optimal, thereby improving generalization of the face emotion recognition algorithm; since the NAGD has a precognition capability, the algorithm can be prevented from being too fast or too slow foreseeingly; and meanwhile, response capability of the algorithm can be enhanced, and better local optimum value can be obtained.

Description

technical field [0001] The invention relates to a face emotion recognition method based on a deep sparse convolutional neural network, which belongs to the field of pattern recognition. Background technique [0002] In recent years, with the development of various technologies, the degree of intelligence in society is also increasing, and people are increasingly eager to experience natural and harmonious human-computer interaction. However, emotion has always been an insurmountable gap between man and machine. Therefore, breaking through the bottleneck of current affective computing is the key to the development of artificial emotion field. Expression is one of the important channels for human to express emotion. Facial emotion recognition has certain application value in the fields of human-computer interaction, fatigue driving detection, remote care and pain assessment, and its application prospect is very broad. Therefore, achieving more accurate expression recognition ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/06
CPCG06N3/061G06V40/175G06F18/2136G06F18/214
Inventor 吴敏苏婉娟陈略峰周梦甜刘振焘曹卫华
Owner CHINA UNIV OF GEOSCIENCES (WUHAN)
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