Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

Key point extraction-based driver fatigue driving monitoring system and method

A fatigue driving and monitoring system technology, applied to computer components, character and pattern recognition, instruments, etc., can solve the problem of not extracting feature points, etc., to reduce the incidence of traffic accidents and improve the accuracy

Inactive Publication Date: 2018-08-03
上海瀚所信息技术有限公司
View PDF8 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Most of the existing fatigue monitoring methods based on image processing only obtain the position of the human eye, and do not further extract feature points for local feature information such as the human eye.

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
  • Key point extraction-based driver fatigue driving monitoring system and method
  • Key point extraction-based driver fatigue driving monitoring system and method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0022] The above and / or additional aspects and advantages of the present invention will become apparent and comprehensible from the following description of the embodiments in conjunction with the accompanying drawings.

[0023] figure 1 An embodiment of the driver fatigue driving monitoring system based on key point extraction of the present invention is shown, including an image acquisition module 1, a feature point positioning module 2 and a state determination module 3 connected in sequence, and also includes a frame state determination module 3 connected Image transmission module 4 and alarm module 5. Wherein, the image collection module 1 includes a camera, an infrared supplementary light and a video decoder for real-time collection of the facial image of the driver. The feature point positioning module 2 uses the existing ASM (Active Shape Model) algorithm to locate the key feature points in each frame of facial images, including the contours of key parts such as human...

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 key point extraction-based driver fatigue driving monitoring system and method. The system comprises an image acquisition module, a feature point positioning module and a state judgement module, wherein the image acquisition module is used for acquiring face images of drivers; the feature point positioning module is used for positioning key feature points in each frame offace image; and the state judgement module is used for judging opening amplitudes corresponding to the eyes and mouth of the current driver according to the key feature points positioned in each frameof face image, and judging that the driver is in fatigue driving if the opening amplitudes, of the eyes and mouth of the driver, corresponding to Q frames of images in continuous P frames of face images are smaller than corresponding predetermined threshold values, wherein P and Q are preset values. According to the system and method, a key feature point extraction-based face state monitoring wayis put forward, so that local feature information of drivers during fatigue driving can be obtained, states of the eyes and mouths can be correctly judged, benefit is brought to improve the monitoring correctness, and the drivers can be timely reminded to have a rest, so as to reduce the traffic accident rate.

Description

technical field [0001] The invention relates to the field of driver fatigue driving monitoring, in particular to a driver fatigue driving monitoring system and method based on key point extraction. Background technique [0002] Fatigue driving is a major cause of traffic accidents. Most of the existing fatigue driving monitoring technologies use contact devices to monitor the driver's physiological characteristics, so as to determine whether there is a dangerous behavior of fatigue driving. However, the contact monitoring device will affect the driver's driving behavior to a certain extent, and there are potential safety hazards. The monitoring method based on computer vision can use the driver's facial features to judge the fatigue state without affecting normal driving. Most of the existing fatigue monitoring methods based on image processing only obtain the position of human eyes, and do not further extract feature points for local feature information such as human eyes....

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): G06K9/00G08B21/06
CPCG08B21/06G06V40/171G06V20/597
Inventor 王帅丁华泽纪立李鲁明兰青李凤荣何为缪伟忠
Owner 上海瀚所信息技术有限公司
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
Eureka Blog
Learn More
PatSnap group products