Fatigue detection system based on machine vision and fatigue detection method thereof

A technology of fatigue detection and machine vision, which is applied in the field of image processing, can solve the problems that cannot meet the requirements of detecting mild fatigue state, and achieve the effect of intelligent detection of human fatigue, high accuracy and reduction of accidents

Inactive Publication Date: 2017-11-17
ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE
View PDF3 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The accuracy of fatigue discrimination based on physiological signals (EEG signals, ECG signals, etc.) is high, and relatively subtle signals can be captured, which can meet the requirements for human fatigue detection to a certain extent, but traditional contact physiological signals The collection method has brought a lot of inconvenience to practical applications and has obvious limitations; the fatigue discrimination method based on the characteristics of human physiologica

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
  • Fatigue detection system based on machine vision and fatigue detection method thereof
  • Fatigue detection system based on machine vision and fatigue detection method thereof
  • Fatigue detection system based on machine vision and fatigue detection method thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] Through the description of the embodiments below, the specific implementation of the present invention includes the shape, structure, mutual position and connection relationship between the various parts, the function and working principle of each part, the manufacturing process and the operation and use method of the various components involved. etc., to make further detailed descriptions to help those skilled in the art have a more complete, accurate and in-depth understanding of the inventive concepts and technical solutions of the present invention.

[0040] In order to achieve the above object, the technical solution provided by the present invention is as follows: a fatigue detection method based on machine vision, comprising the following steps:

[0041] 1. Establish facial micro-expression models in different states;

[0042]2. Capture face images in real time through the camera and extract micro-expression changes;

[0043] 3. Project the extracted facial micr...

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 discloses a fatigue detection system based on machine vision and a fatigue detection method thereof. Facial micro-expressions are tracked and captured in real time according to presentation of micro-signals generated by people under the fatigue state on the facial micro-expressions, the captured micro-expressions are matched with a pre-established facial micro-expression model, the fatigue determination parameter F is extracted by analyzing the matching degree and heart rate variability analysis is also performed, and the final fatigue level is obtained by integration of two types of analysis according to a certain weight so that the possible error can be eliminated to the greatest extent, and the current fatigue state of the human body can be accurately judged. The operation is simple and the cost is low, and the micro fatigue signals can still be accurately captured so as to play an important role in enhancing the work efficiency, reducing accidents and protecting human health and avoiding falling sick from overwork.

Description

technical field [0001] The invention belongs to the technical field of image processing, relates to the detection of micro-expressions of human bodies, and in particular to a fatigue detection system and method based on machine vision. Background technique [0002] With the rapid development of economy and technology, the pace of people's life is constantly accelerating, and the long-term continuous study or work mode has become the normal life of people today. This fast-paced lifestyle is promoting social development and human progress. At the same time, it inevitably brings some side effects. In fact, people's physiological endurance is limited, and long-term uninterrupted work will reduce people's physiological functions and cause the body to feel fatigued. Working or studying in a state of fatigue will make it difficult for people to concentrate, resulting in a decrease in learning or work efficiency, and may even cause accidents in some situations. Simultaneously, if ...

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
IPC IPC(8): G06T17/00G06K9/00
CPCG06T17/00G06V40/168G06V40/174G06V40/172
Inventor 魏利胜甘泉王碧晨胡方方鲁冬艳
Owner ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE
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