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Fatigue driving monitoring method based on machine vision

A technology of fatigue driving and machine vision, which is applied to instruments, alarms, computer components, etc., can solve the problems that the judgment basis cannot be determined, and the critical judgment threshold cannot be given, so as to achieve high vehicle application potential and low misjudgment rate , easy to use and efficient effect

Inactive Publication Date: 2018-05-01
ANHUI UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The advantage of this type of method is that it does not need to touch the driver's body, and the test results can directly reflect the driving state. The disadvantage is that the judgment basis cannot be determined, and it is impossible to give a clear critical judgment threshold for different drivers.

Method used

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  • Fatigue driving monitoring method based on machine vision

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Effect test

Embodiment 1

[0037] 1) In the present embodiment, the selected main frequency is 2.3GHz, an INTEL Core i5-6300HQ processor based on x64 architecture, the operating system is Windows 10, and the integrated development environment (IDE) selected is Visual Studio 2015. The camera used to collect images is Shuangfeiyan’s home camera PKS-820G, which has 16 million pixels and has an automatic white balance function.

[0038] 2) Connect the camera to the computer through the USB interface;

[0039]3) Start Visual Studio 2015, create a new project and add the source files and header files required by the project, put the classifier related files required by the project in the project directory, and add OPENCV and Dlib libraries in the configuration property page;

[0040] 4) Before compiling, select the active solution configuration as Release in the configuration manager, and select the active solution platform as x64;

[0041] 5) Click the local Windows debugger to run the program. At this time...

Embodiment 2

[0076] 1) This embodiment selects the firefly-RK3399 development board based on the Rockchip RK3399 chip with the highest main frequency of 2.0GHz. Rockchio is a 6-core (dual-core ARM Cortex-A72+quad-core ARM Cortex-A53) 64-bit processor based on big.LITTLE core architecture. The running operating system is a customized version of ubuntu16.04, and the selected compilation tools are gcc, make and cmake. The camera used to collect images is Shuangfeiyan’s home camera PKS-820G, which has 16 million pixels and has an automatic white balance function.

[0077] 2) The main frequency of the project development is 1.70GHz, INTEL core i3-4005U processor based on x64 architecture, and the operating system is ubuntu16.04LTS. The chosen integrated development environment (IDE) is Eclipse CDT.

[0078] 3) Start Eclipse on the PC side, create a new project and add the source files and header files required by the project, put the classifier-related files required by the project in the pro...

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Abstract

The invention discloses a fatigue driving monitoring method based on machine vision. The method mainly monitors the eye changes and the yawns of a driver through video image processing technology, andcomprehensively determines whether the driver is in a fatigue driving state. Compared with a detection method based on physiological signals, the method does not need to contact the driver's body anddoes not affect driving. Compared with a detection method based on driving behaviors, the method has a lower misjudgment rate and more development potential. The method of the present invention includes the following steps: preprocessing a face image; obtaining a human eye standard map; loading a classifier to perform feature classification and determine the open / close state of the human eye standard map; and determining a fatigue driving state.

Description

technical field [0001] The invention relates to a fatigue driving monitoring method, in particular to a machine vision-based fatigue driving monitoring method. Background technique [0002] Driving fatigue refers to the phenomenon that the driver's physiological function and psychological function are out of balance after driving continuously for a long time, and the driving skill declines objectively. The driver's sleep quality is poor or insufficient, and he is prone to fatigue after driving for a long time. Driving fatigue can affect various aspects such as driver's attention, feeling, consciousness, thinking, judgment, will, decision and motion. As the number of vehicles increases year by year, if you continue to drive the vehicle after fatigue, you will feel drowsy, drowsy, weak in limbs, inattentive, poor in judgment, or even in a trance or instant memory loss, delayed or premature action, pause or correction in operation Improper time and other unsafe factors can ea...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G08B21/06
CPCG08B21/06G06V20/597G06F18/2411G06F18/214
Inventor 孙世若王天琪张淼
Owner ANHUI UNIVERSITY
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