Deep-learning-based driver's fatigue detection method and apparatus

A technology of driver fatigue and deep learning, which is applied in the fields of video surveillance, intelligent transportation, and image processing, and can solve problems such as poor detection accuracy

Pending Publication Date: 2017-02-22
BEIJING ICETECH SCI & TECH CO LTD
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Problems solved by technology

[0005] However, the detection accuracy of the above-mentioned driver fatigue detection method is poor

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  • Deep-learning-based driver's fatigue detection method and apparatus
  • Deep-learning-based driver's fatigue detection method and apparatus

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Embodiment Construction

[0059] In order to enable your examiners to further understand the structure, features and other purposes of the present invention, the attached preferred embodiments are now described in detail as follows. The described preferred embodiments are only used to illustrate the technical solutions of the present invention, not to limit the present invention. invention.

[0060] figure 1 A flow chart of the driver fatigue detection method based on deep learning according to the present invention is given. Such as figure 1 Shown, according to the driver's fatigue detection method based on deep learning of the present invention comprises:

[0061] The first step S1 is to select images of drivers in different states as sample images, train a neural network with deep learning, and obtain a trained driver state recognition model;

[0062] The second step S2 is to collect the driver's video image;

[0063] In the third step S3, a face detection algorithm is used to obtain a face area...

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Abstract

The invention provides a deep-learning-based driver's fatigue detection method, comprising: obtaining the images of a driver in different states as sample images; training the neural network with deep-learning-based to obtain a trained driver state recognizing model; acquiring the video images of the driver; employing a face detection algorithm to obtain the face area from each frame of the video images; utilizing the recognizing model for the state of the well-trained driver to recognize the face area from each frame of the video images and obtaining the state of the driver in each frame of the video images; and based on the state of the driver in the continuous frames of the video images and through eye blinking analysis, yawning analysis and comprehensive analysis, determining whether the driver is fatigued or not and outputting the detection result. Compared with the prior art, the method and apparatus are capable of accurately detecting whether a driver is fatigued or not.

Description

technical field [0001] The invention relates to image processing, video monitoring and intelligent transportation, in particular to a driver fatigue detection method and device based on deep learning. Background technique [0002] Driver fatigue detection is an important factor in causing traffic accidents and thus has been extensively studied. At present, the driver fatigue detection method mainly detects whether the driver is in a fatigue state from the driver's physiological information, facial information and vehicle state. [0003] The detection method based on the driver's physiological information needs to add some measuring equipment on the driver's body to detect the driver's physiological parameters, such as electrocardiogram, electroencephalogram, pulse, etc., but this method is easy to interfere with the driver. The detection method based on the vehicle state can judge whether the driver is in a fatigue state by detecting the abnormality of the steering wheel ro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V40/161G06V40/168G06V40/172G06V20/40G06V20/597
Inventor 谢静崔凯班华忠曾建平李志国
Owner BEIJING ICETECH SCI & TECH CO LTD
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