Face recognition-based fatigue driving detection method

A fatigue driving and detection method technology, applied in character and pattern recognition, acquisition/recognition of facial features, image data processing, etc., can solve problems such as operation pause or improper correction time, lane departure, affecting harmonious life, etc., to achieve high recognition Accuracy and Adaptability, Effect of Improving Accuracy

Inactive Publication Date: 2017-02-01
防城港市港口区高创信息技术有限公司
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Problems solved by technology

If the driver does not have a good rest or drives for a long time, he is prone to fatigue. Once tired, the driver's attention, judgment, decision-making and motor awareness will be weakened. If he continues to drive the vehicle, the action will be delayed or premature, and the operation will stop or correct Improper time and other wrong operations can easily lead to t

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  • Face recognition-based fatigue driving detection method
  • Face recognition-based fatigue driving detection method
  • Face recognition-based fatigue driving detection method

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Embodiment Construction

[0054] The following specific examples further illustrate the present invention, but are not intended to limit the present invention.

[0055] Experiment 1 uses the integral projection algorithm of the present invention to locate the eyes and mouth.

[0056] In the cab, face images of 3 experimenters (indicated by experimenter 1, experimenter 2, and experimenter 3) were actually collected. Each person had different expression changes during the collection process. Each person collected 200 images. A total of 600 face color images, one of the images of person 1 was selected, and the integral projection algorithm of the present invention was used to locate the eyes and mouth. The obtained experimental data are shown in Table 1 below.

[0057] The values ​​of Y1, Y2, Y3, Y4 and X1, X2, X3 obtained by projection in Table 1

[0058] parameter Y1 Y2 Y3 Y4 X1 X2 X3 value 90 139 216 263 82 200 134

[0059] The eye and mouth positioning experiment was ...

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Abstract

The invention discloses a face recognition-based fatigue driving detection method. The method includes the following steps that: human face video image acquisition is carried out; an integral projection algorithm is adopted to carry out eye and mouth positioning on the first frame of image, the images of a left eye portion, a right eye portion and a mouth portion are extracted; an adaptive particle filtering-based eye tracking algorithm is adopted to carry out eye tracking; an improved horizontal projection-based eye and mouth state recognition method is adopted to carry out recognition; eye and mouth fatigue information extraction is carried out, a PERCLOS value, blink frequency, eye closing time and the number of times of yawning are calculated; and fatigue judgment is performed on a driver based on the PERCLOS value, the blink frequency, the eye closing time and the number of times of yawning. According to the defects of an original horizontal projection method, an improved horizontal projection method is adopted to recognize eye and mouth states, and therefore, high recognition accuracy and high adaptability can be achieved; and the fatigue judgment algorithm can improve judgment accuracy.

Description

technical field [0001] The invention relates to a fatigue driving detection method based on face recognition. Background technique [0002] Fatigue driving refers to the phenomenon of blurred vision, unresponsiveness, distraction, and stiff movements caused by factors such as long-term driving, lack of sleep, or physical discomfort. And the disorder of psychological function, appear the phenomenon that driving skill declines. If the driver does not have a good rest or drives for a long time, he is prone to fatigue. Once tired, the driver's attention, judgment, decision-making and motor awareness will be weakened. Improper time and other wrong operations can easily lead to traffic accidents. In order to ensure safety, fatigue driving should be strictly prohibited. [0003] According to the latest statistics, if the driver is inattention within 3 seconds, it will cause about 80% of traffic accidents, mainly including lane departure and rear-end collision accidents. The occur...

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Application Information

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IPC IPC(8): G06K9/00G06T7/00G08B21/06
CPCG08B21/06G06T2207/20068G06T2207/30201G06T2207/10016G06V40/171G06V40/175
Inventor 陈泉
Owner 防城港市港口区高创信息技术有限公司
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