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Micro-expression recognition method based on deep learning

A recognition method and deep learning technology, applied in the field of image processing, can solve problems such as low recognition rate, insufficient data set, and complexity, and achieve the effects of reducing system complexity, shortening training time, and improving convenience

Pending Publication Date: 2020-06-30
道和安邦(天津)安防科技有限公司
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Problems solved by technology

[0006] At present, the problems encountered in micro-expression recognition based on deep learning mainly include the problem of low recognition rate caused by insufficient data set and insufficient network structure, and the complex and expensive equipment used in the current recognition leads to the collection of complex and expensive equipment. high problem

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Embodiment Construction

[0028] The solution of the present invention will be further described below in conjunction with the drawings.

[0029] A micro-expression recognition method based on deep learning. The specific steps are as follows image 3 Shown:

[0030] In this implementation example, we choose the published CASMEI and CASMEII data sets. Due to the large differences in the amount of expression data in the database, we finally choose 55 anger data, 74 disgust data, 131 happiness data, and 36 surprise data. And 21 fear data, a total of 317 data.

[0031] Step 1: Video data cropping; because the micro expressions are not easy to be noticed and the duration is about 1 / 25~1 / 5s, we crop the video data containing expression actions. The cropped video requires a uniform duration of 3 seconds. The cropped video is divided into frames, and the expression image sequence from the beginning to the end is extracted. Since the shortest sample in the CASMEII expression database contains 4 frames and the longest...

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Abstract

The invention discloses a micro-expression recognition method based on deep learning. The micro-expression recognition method comprises the following steps: 1, cutting, framing and extracting video data containing expression actions; 2, performing face alignment, face clipping, normalization and other preprocessing on the extracted expression sequence; 3, performing data enhancement operation on the obtained data set; 4, establishing a neural network model; 5, dividing all facial expression data into a training set and a test set in proportion; and 6, testing the model by using the test set, outputting information such as identification accuracy, identification time, errors and the like, and selecting the current model when the identification rate meets the requirements. The micro-expression recognition method based on deep learning has the advantages of being simple, efficient, low in cost, high in precision and the like.

Description

Technical field [0001] The present invention relates to the technical field of image processing, in particular to a micro-expression recognition method based on deep learning. Background technique [0002] Emotion recognition technology has matured with the update of equipment and the development of artificial intelligence. It is widely used in various fields such as clinical medicine, emotional intelligence, national security, and political psychology. The existing emotion recognition methods mainly include the following two. One is the detection of physical signs based on sophisticated instruments, which can recognize and classify emotions by detecting physiological signals such as human brain electricity, ECG, pulse waves, and the other is intelligent facial emotion recognition based on machine learning. Detection is mainly achieved by capturing the movement of facial muscles, such as raising the corner of the mouth when happy, so as to realize emotion recognition. [0003] The...

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Application Information

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IPC IPC(8): G06K9/00G06N3/04
CPCG06V40/174G06N3/045
Inventor 王峰相虎生牛锦宋剑桥贾海蓉马军辉师泽州相宸卓王飞
Owner 道和安邦(天津)安防科技有限公司
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