Visual sense-based fatigue driving identification method fusing heart rate and facial features

A fatigue driving and facial feature technology, applied in the field of fatigue driving recognition, can solve problems such as discomfort, driver inconvenience, light, and the influence of the orientation of the head of the glasses

Active Publication Date: 2020-09-11
SOUTH CHINA UNIV OF TECH
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AI Technical Summary

Problems solved by technology

However, wearing the device is inconvenient for the driver and may make them feel uncomfortable
Existing fatigue driving detection methods use RGB images to extract eye openings, where lighting

Method used

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  • Visual sense-based fatigue driving identification method fusing heart rate and facial features
  • Visual sense-based fatigue driving identification method fusing heart rate and facial features
  • Visual sense-based fatigue driving identification method fusing heart rate and facial features

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Embodiment Construction

[0061] The present invention will be further described below in conjunction with examples and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0062] Such as figure 1 , the present embodiment provides a vision-based fusion of heart rate and facial features fatigue driving recognition method, comprising the following steps:

[0063] S1. Use the depth camera to extract three fatigue features: heart rate, eye opening and mouth opening;

[0064] S2. Apply the RNN layer of the recurrent neural network to obtain the time information of the eye opening degree and the mouth opening degree;

[0065] S3. Combining fuzzy reasoning with RNN to extract time information of heart rate;

[0066] S4, using a relationship layer comprising two levels of RNN to extract the connection between the three features;

[0067] S5. Outputting the driver's fatigue level.

[0068] The depth camera described in step S1 is an RGB-D camera, the RGB-D camera is...

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Abstract

The invention discloses a visual sense-based fatigue driving identification method fusing heart rate and facial features. The method comprises the following steps: S1, extracting three fatigue characteristics, namely heart rate, eye opening degree and mouth opening degree, by using a depth camera; s2, applying a recurrent neural network (RNN) layer to obtain time information of the eye opening degree and the mouth opening degree; s3, combining fuzzy reasoning with RNN, and extracting time information of the heart rate; s4, extracting relations among the three features by using a relation layercontaining two stages of RNNs; and S5, outputting the fatigue degree of the driver. According to the method, the time sequence information related to the fatigue driving characteristics and the connection information among the characteristics are extracted, so that the fatigue detection performance of the driver is improved. Fuzzy reasoning and RNN are combined to solve the problems of fuzzinessand noise, temporal information related to the heart rate is extracted, the opening degree of eyes and the opening degree of the mouth can be determined more accurately through the depth image, and the driving fatigue recognition precision is effectively improved.

Description

technical field [0001] The invention belongs to the technical field of intelligent transportation, and in particular relates to a fatigue driving recognition method based on vision fusion of heart rate and facial features. Background technique [0002] Drivers are in a state of fatigue driving, and their ability to recognize road conditions and driving skills is significantly reduced. Research results show that 25%-30% of traffic accidents are caused by fatigue driving. In order to overcome this problem, it is necessary to develop a system that can effectively detect driver's fatigue driving and warn them in time. [0003] Driver fatigue can be detected by using a wearable device to measure a driver's heart rate or extracting facial features using an RGB camera. However, wearable devices will cause inconvenience and discomfort to drivers, and the detection accuracy of RGB cameras may be affected by light, glasses, and head orientation. In addition, most existing methods i...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N5/04A61B5/024A61B5/18
CPCG06N5/048A61B5/024A61B5/165A61B5/18A61B2503/22G06V40/171G06V20/597G06N3/045G06F18/253
Inventor 杜广龙
Owner SOUTH CHINA UNIV OF TECH
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