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Fatigue driving detection method and device

A technology of fatigue driving and detection method, applied in the field of fatigue driving detection based on deep neural network, can solve problems such as large amount of calculation, inability to run embedded devices in real time, and inability to be practical.

Active Publication Date: 2019-01-22
SHENZHEN HORIZON ROBOTICS TECH CO LTD
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the accuracy of this method has been improved, this method has a large amount of calculation and cannot be run in real time on embedded devices, so it is not practical

Method used

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  • Fatigue driving detection method and device
  • Fatigue driving detection method and device

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Embodiment Construction

[0029] Embodiments of the present invention will be described below with reference to the drawings. Elements and features described in one drawing or one embodiment of the present invention may be combined with elements and features shown in one or more other drawings or embodiments. It should be noted that representation and description of components and processes that are not related to the present invention and known to those of ordinary skill in the art are omitted from the drawings and descriptions for the purpose of clarity.

[0030] figure 1 It is a flow chart of the fatigue driving detection method provided by Embodiment 1 of the present invention. It includes the following steps:

[0031] Firstly, in step S101, a moving image of the front face of the driver collected by a camera is received. For example, images are collected with resolutions of 640*480 pixels, 1280*720 pixels, and 1920*1080 pixels.

[0032] Here, the camera can be an ordinary camera or a monocular...

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Abstract

The invention discloses a driver's fatigue driving detection method and a detection device. The method comprises the following steps: receiving an acquired frontal face image of a driver; conducting human face detection in the acquired image; and further positioning human eyes and / or mouth in a detected human face, and the method further comprises steps of positioning the detected human eyes and / or mouth based on a deep neural network model, and identifying the status of the human eyes; and tracking change of the human eye status in a multi-frame image, and judging whether the driver gets fatigued or not. By virtue of the detection method and device, fatigue driving can be accurately detected in real time with high robustness.

Description

technical field [0001] The present disclosure generally relates to the technical field of automobile safety driving, and specifically relates to a method and device for detecting fatigue driving based on a deep neural network. Background technique [0002] With the development of society and economy, motor vehicles have increased sharply, and traffic accidents caused by fatigue driving have become more and more frequent. Aiming at this phenomenon, various fatigue driving detection technologies have been produced, including the fatigue driving detection technology based on the driver's physiological characteristics. When the driver is tired, he will show physiological characteristics such as bowing his head and increasing the frequency of eye closure. By detecting these physiological characteristics of the driver through the monitoring device, it can be judged whether the driver is tired. The fatigue driving detection technology based on the driver's physiological character...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A61B5/00
CPCA61B5/00A61B5/6826A61B2503/22
Inventor 杨铭白涛都大龙黄畅
Owner SHENZHEN HORIZON ROBOTICS TECH CO LTD