Machine vision-based fatigue driving pre-warning system suitable for smart phone

A smart phone and machine vision technology, applied to instruments, alarms, computer parts, etc., can solve the problems of high price and failure to popularize the driving fatigue warning system, and achieve the effect of portability and popularization

Inactive Publication Date: 2015-04-29
清华大学苏州汽车研究院(吴江)
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, the current price of such products in the market is as high as several thousand yuan, which is very expens...

Method used

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  • Machine vision-based fatigue driving pre-warning system suitable for smart phone
  • Machine vision-based fatigue driving pre-warning system suitable for smart phone
  • Machine vision-based fatigue driving pre-warning system suitable for smart phone

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Embodiment

[0033] The preferred embodiments of the present invention will be further described with reference to the accompanying drawings.

[0034] The present invention mainly uses a machine vision-based method for fatigue detection, supplemented by driver behavior analysis to enhance the accuracy and robustness of detection.

[0035] Today's smart phones generally integrate cameras, acceleration sensors, gravity sensors and positioning modules, and at the same time have at least 1GHz CPU and 512MB of memory, these hardware conditions.

[0036] Such as figure 1 As shown, the fatigue driving early warning system suitable for smart phones in the present invention includes four modules: smart phone, fatigue detection module, driver behavior analysis module, and early warning module.

[0037] The smart phone includes an image acquisition module and a sensor information acquisition module.

[0038] Image acquisition module: collect driver facial information through the camera.

[0039] The sen...

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Abstract

The invention discloses a machine vision-based fatigue driving pre-warning system suitable for a smart phone. The machine vision-based fatigue driving warning system comprises the smart phone which acquires the facial information of a driver through a camera and acquires the speed information, the acceleration information and the gravitational acceleration information of a current vehicle through a sensor information acquisition module, a fatigue detection module which judges the fatigue state of the driver by detecting an eye movement status and the change of head posture of the driver, a driver behavior analysis module which is used for modeling the driving status information of a user comprehensively, and comparing the model of the driving status information with a statistical analysis method model to assist the judgment for the current behavior status of the driver, and a pre-warning module which is used for comparing the fatigue detection result with the driving behavior analysis result comprehensively, and giving a fatigue alarm by a voice prompt. The driving behavior is analyzed automatically to form a data analysis library, and a mobile phone acceleration sensor is combined to judge the dangerous driving behavior of the driver.

Description

technical field [0001] The invention relates to a machine vision fatigue driving early warning system, in particular to a machine vision fatigue driving early warning system suitable for smart phones. Background technique [0002] With the rapid increase of the number of motor vehicles and the rapid development of expressways, traffic accidents occur frequently, causing huge property losses and casualties to countries all over the world. How to reduce traffic accidents has become a worldwide problem, among which, the prevention of fatigue driving is a key technology that countries and major automobile manufacturers in the world are currently working hard to develop. According to the latest statistics from the Ministry of Communications, more than 200,000 people are injured or killed in road traffic safety accidents in my country every year, 50% of which are caused by drivers who are unconscious and cause traffic accidents. Long-time driving, lack of sleep, physiological cha...

Claims

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Application Information

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IPC IPC(8): G08B21/06G06K9/00
CPCG08B21/06G06V20/597
Inventor 张伟
Owner 清华大学苏州汽车研究院(吴江)
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