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Fatigue driving recognition method and system based on multiple features

A technology for fatigue driving and recognition methods, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of low recognition accuracy and poor adaptability, and achieve high recognition accuracy, strong adaptability, and improved signal-to-noise ratio. Effect

Pending Publication Date: 2020-08-25
HUNAN UNIV +1
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Problems solved by technology

[0006] Aiming at the deficiencies of the prior art, the present invention provides a multi-feature-based fatigue driving recognition method and system to solve the problems of low recognition accuracy and poor adaptability of the existing detection methods

Method used

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  • Fatigue driving recognition method and system based on multiple features
  • Fatigue driving recognition method and system based on multiple features
  • Fatigue driving recognition method and system based on multiple features

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Embodiment Construction

[0076] The technical solutions in the present invention are clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0077] Such as figure 1 As shown, a kind of fatigue driving identification method based on multi-feature provided by the present invention comprises:

[0078] 1. Obtain a single video frame image in real time, and preprocess the video single frame image. The specific preprocessing process is:

[0079] (1.1) Use adaptive median filter to smooth and denoise the video single frame image.

[0080] The ultimate goal of video image denoising is to improve the quality of the captu...

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Abstract

The invention discloses a fatigue driving recognition method and system based on multiple features, and the method and system carry out the preprocessing of an image, filter noise, and avoid problemsthat the image quality is poor and the detection precision is low because the image is affected by an external environment factor. The AdaBoost algorithm is adopted to stably, quickly and efficientlydetect the human face, so that the complexity of human face detection is reduced. According to the scale space-based face target tracking algorithm, a self-adaptive high-confidence updating strategy is adopted, and when an error occurs in a target tracking stage, the confidence of target detection is relatively low, and a model is not updated, so that the risk of drifting of the tracking algorithmis effectively reduced, and the tracking precision is improved. The SVM classifier is adopted for eye state recognition, the precision of eye state recognition is improved, and therefore the method is high in recognition precision and high in adaptability to the environment.

Description

technical field [0001] The invention belongs to the technical field of driving safety, and in particular relates to a multi-feature-based fatigue driving identification method and system. Background technique [0002] Nowadays, the driver fatigue detection technology is becoming more and more mature, and the fatigue detection methods can be mainly divided into three categories: [0003] One is the detection method based on the vehicle, which mainly judges the fatigue state by collecting the driving parameters of the vehicle and analyzing the abnormal fluctuation of the parameters. Such detection methods include steering wheel angle degree detection, steering wheel steering grip detection, vehicle speed detection, vehicle offset detection, brake pedal force detection and accelerator pedal force detection, etc. Most of the current vehicles are equipped with different types of sensors to collect real-time parameters such as driving speed, steering wheel angle, fuel consumption...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
CPCG06V40/168G06V40/172G06V20/597G06V10/44G06F18/2411G06F18/214
Inventor 胡峰松彭清舟徐蓉程哲坤
Owner HUNAN UNIV
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