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A driver fatigue detection method and device based on convolutional neural network

A convolutional neural network, driver fatigue technology, applied in the field of driver fatigue detection to reduce the incidence of traffic accidents

Active Publication Date: 2022-02-25
SHANDONG INSPUR SCI RES INST CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The technical task of the present invention is to provide a driver fatigue detection method and device based on convolutional neural network to solve how to use convolutional neural network to detect the fatigue degree of the driver, and to give an alarm to the driver who is already tired. The problem of reducing the incidence of traffic accidents

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  • A driver fatigue detection method and device based on convolutional neural network
  • A driver fatigue detection method and device based on convolutional neural network

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Experimental program
Comparison scheme
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Embodiment 1

[0044] as attached figure 1 Shown, the driver's fatigue detection method based on convolutional neural network of the present invention, this method comprises the steps:

[0045] S1. Collect face image data in various situations, and perform feature marking on the image; wherein, collect face image data in various situations including day and night and face images with eyes open and eyes closed in different environments ;The face image is taken by an infrared vehicle camera; among them, the face image can also be searched for suitable pictures on the Internet for marking, etc., and the pictures are not less than tens of thousands;

[0046] S2. Using the cnn convolutional neural network algorithm to train the image data set to obtain a corresponding model; the specific steps are as follows:

[0047] S201. Set two front convolution layers: including 32 convolution kernels, each convolution kernel is 3*3, the edge is not supplemented, the convolution step is 1 to the right and d...

Embodiment 2

[0064] as attached figure 2 As shown, the driver fatigue detection device based on the convolutional neural network, the device includes a host, a vehicle camera, a sound and a loading module, the loading module is installed in the host, and the host is respectively connected to and controls the vehicle camera and audio; the switch of the host is connected to the car or The locomotive starting device is connected to ensure that the host starts immediately when the car or locomotive is started; the camera is installed on the dashboard of the car or in the locomotive driver's cab where the facial expressions of the main driver can be captured without blocking the line of sight; the host and the audio are installed in the cab without The position that affects the driver's behavior or embedded in the center console; the loading module is used for camera shooting and processing.

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Abstract

The invention discloses a driver fatigue detection method and device based on a convolutional neural network, which belongs to the field of artificial intelligence. The fatigued driver gives an alarm reminder, and the technical scheme is as follows: S1, collect face image data in various situations, and perform feature marking on the image; S2, use the cnn convolutional neural network algorithm to train the image data set , obtain the corresponding model; S3, write the corresponding python code loading program to the model trained in step S2; S4, install the loading program in the step S3 in the host computer of the center console in the cab; S5, in the cab The on-board camera takes pictures of the driver and sends them to the loading program for inference, and uses the trained model to judge whether the driver is driving in fatigue. The invention also discloses a driver fatigue detection device based on a convolutional neural network.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a driver fatigue detection method and device based on a convolutional neural network. Background technique [0002] Convolutional neural network is an efficient recognition method that has been developed in recent years and has attracted widespread attention. In the 1960s, Hubel and Wiesel found that its unique network structure can effectively reduce the complexity of the feedback neural network when studying the neurons used for local sensitivity and direction selection in the cat cerebral cortex, and then proposed the convolutional neural network ( Convolutional Neural Networks-referred to as CNN). Now, CNN has become one of the research hotspots in many scientific fields, especially in the field of pattern classification, because the network avoids the complex preprocessing of images and can directly input original images, so it has been more widely used. The new reco...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/59G06V10/774G06N3/04G06N3/08
CPCG06N3/08G06V20/597G06N3/045G06F18/214
Inventor 于治楼戴鸿君裘肖明
Owner SHANDONG INSPUR SCI RES INST CO LTD