Deep learning-based emotion recognition method and system

A technology of deep learning and emotion recognition, applied in character and pattern recognition, instruments, computer components, etc., can solve problems such as it is difficult to carry out preventive work objectively, and achieve the effect of stable working state

Inactive Publication Date: 2017-05-10
GUANGDONG POLYTECHNIC NORMAL UNIV
View PDF5 Cites 53 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Even if there are dedicated HR personnel to track and understand the work pressure of employees, it is impossible to study all employees every day, not to mention that these HRs themselves also have mood swings, so it is difficult to carry out preventive work objectively

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Deep learning-based emotion recognition method and system
  • Deep learning-based emotion recognition method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0026] Embodiment one, refer to figure 1 As shown, according to the design scheme provided by the present invention, a deep learning-based emotion recognition system specifically includes:

[0027] The face image acquisition module is based on three parts: the deep learning expression recognition module and the expression warning module.

[0028] The face image acquisition module is used to acquire the frontal image of the employee's face, and store the image in the image database in the form of the employee's ID and check-in date.

[0029] The facial expression recognition module based on deep learning realizes fine adjustment of deep learning network parameters in the training phase, and performs facial emotion feature classification after the training is completed.

Embodiment 2

[0030] Embodiment two: reference figure 2 As shown, step 101. Facial image acquisition, obtains the frontal image of the employee's face, names the image according to the employee's ID and check-in date, and stores it in the image database according to the employee's ID as the key.

[0031] Step 102. Preprocessing the face image, adjusting the face image to an RGB image with a size of 227*227.

[0032] Step 103. Based on facial expression recognition based on deep learning, the face image is calculated to obtain the emotional feature classification of the face through the trained VGGNet network, and the emotional classification is stored in the employee's emotional database.

[0033] Step 104. Emotional comparative analysis and early warning. Compare the emotions of employees with abnormal emotions in the past week in the emotional database. If the emotions are abnormal only on the day of attendance, an early warning will be sent to the relevant psychological counselors. If t...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a deep learning-based emotion recognition method and system. The system includes a face image acquisition module, a deep learning-based facial expression recognition module and a facial expression early warning module. The facial images of employees are acquired when the employees punch in every time; the emotions of the employees are analyzed through adopting a deep learning algorithm-based facial expression analysis algorithm, and the emotions are compared with historical emotions; and when the emotions are abnormal, the system sends alarm information to relevant personnel. According to the deep learning-based emotion recognition method and system of the present invention, the deep learning algorithm is adopted to perform emotional analysis on the employees, and therefore, deep-level humanistic care can be provided for the employees.

Description

technical field [0001] The present invention relates to a recognition of work pressure, in particular to an emotion recognition method and system based on deep learning. [0002] technical background [0003] Facial expressions are an important carrier of human communication and an important way of non-verbal communication. Mental state, health status and other factors are extremely closely related. [0004] Facial expressions are an important way for humans to express emotions and convey their inner world and attitudes. Therefore, facial expressions can be used to analyze and judge the work pressure of employees, and then carry out psychological intervention. At present, in enterprises and institutions, the identity authentication of employees through facial recognition has gradually become popular when commuting to and from get off work. Therefore, machine learning algorithms can be used to recognize facial expressions, and then the mental state and psychological activiti...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V40/172
Inventor 雷方元戴青云赵慧民蔡君魏文国罗建桢
Owner GUANGDONG POLYTECHNIC NORMAL UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap