Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Fatigue driving safety monitoring method based on human eye state detection

A technology for fatigue driving and safety monitoring, which is applied to instruments, character and pattern recognition, computer components, etc. It can solve the problems of difficult realization and high image quality in the eyeball area, and achieve the goals of reducing false alarms, improving detection rate, and high alarm accuracy Effect

Active Publication Date: 2016-12-07
ZHEJIANG ICARE VISION TECH
View PDF7 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method requires high image quality in the eyeball area, which is difficult to achieve in actual use

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 driving safety monitoring method based on human eye state detection
  • Fatigue driving safety monitoring method based on human eye state detection
  • Fatigue driving safety monitoring method based on human eye state detection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0021] Below in conjunction with embodiment and attached figure 1 The present invention is described further:

[0022] The equipment used for data collection in this embodiment is an infrared camera installed in the cab. Installation requirements: The camera is set up in the center, the focal length of the camera is required to be about 8MM, and the distance between the camera and the face is 70-80cm. Set the parameters required by the algorithm, mainly including the number of statistical video frames and the upper and lower thresholds of fatigue detection. For infrared video data, call the algorithm interface provided by this algorithm, and the algorithm will call the corresponding model according to the input image to give the current fatigue state of the driver, and will give an alarm message if fatigued. The specific implementation is as follows, see figure 1 and figure 2 :

[0023] 1. Use an infrared camera to collect face images.

[0024] 2. Grayscale the face ima...

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 relates to a fatigue driving safety monitoring method based on human eye state detection. According to the invention, various complex factors in the driving process are fully considered. Firstly, the situation that human eye data caused by accidental factors are not reliable is eliminated. Therefore, human eyes can be accurately positioned. After that, the current state of the human eyes can be judged from the visual level of the human eyes. In this way, the complex eyeball analysis technique and the trajectory analysis technique are not required.

Description

technical field [0001] The invention belongs to the technical field of intelligent safety, and relates to a fatigue driving safety monitoring method based on human eye state detection. Background technique [0002] Fatigue driving detection is an important part of safe driving. How to automatically detect the driver's fatigue state while driving and remind the driver to drive safely has become a widely concerned issue. There are many methods for fatigue detection. "Driver Fatigue Detection" 104887253A provides an indication of dangerous driving conditions by collecting data related to the vehicle's yaw rate over a period of time and calculating its deviation from the ideal trajectory. Since there are many factors affecting the change of the yaw rate, the reliability of the yaw rate data collected by this method is not strong. "Fatigue Detection System and Method" 105718033A, by collecting pictures of eyeball images, and counting the proportion of red pixels. This method r...

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): G06K9/00G08B21/06
CPCG08B21/06G06V20/597
Inventor 尚凌辉董江凯薛云峰林国锡
Owner ZHEJIANG ICARE VISION TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products