Fatigue state detecting method for eliminating driver individual difference by utilizing online learning

A fatigue state and detection method technology, which is applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of difficult to guarantee detection accuracy, achieve suppression of abnormal states and bad behaviors, reduce the incidence of vicious traffic accidents, The effect of promoting the practical process

Active Publication Date: 2013-04-03
清华大学苏州汽车研究院(吴江)
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AI Technical Summary

Problems solved by technology

In terms of driver fatigue feature vector extraction, most fatigue detection methods do not fully consider the concealment and individual differences of fatigue features, and only involve common features with statistical mean significance. Fati

Method used

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  • Fatigue state detecting method for eliminating driver individual difference by utilizing online learning
  • Fatigue state detecting method for eliminating driver individual difference by utilizing online learning
  • Fatigue state detecting method for eliminating driver individual difference by utilizing online learning

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Embodiment

[0036] Embodiment: The present invention uses the camera to collect the driver's facial video image, and uses a general classifier constructed based on eye movement characteristic parameters (such as blinking frequency, blinking speed, etc.) The fatigue pattern classifier constructed on the basis of time-varying features (such as the change of blink frequency, the change of blink speed, etc.) realizes the identification of the driver's fatigue state; figure 1 As shown, it specifically includes the following steps:

[0037] (1) Collect the video images of the driver's face, and use the expert scoring method based on facial video to establish a driver's facial video database. Each sample in the database is a video clip with a length of 30 seconds, and each sample is assigned a fatigue Status tab; specifically, the following steps are included:

[0038] (11) Use the camera to collect the driver's facial video image, and use the video segmentation software to sequentially segment...

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Abstract

The invention discloses a fatigue state detecting method for eliminating driver individual difference by utilizing online learning and through eye motion characteristics. The method comprises the following steps of obtaining a video image of a driver through a camera, detecting the face of the driver according to the video image and processing the video image to obtain driver eye motion characteristics; and comparing the driver eye motion characteristics and data under the condition that the driver is sober, wherein a result exceeds a threshold value shows that the driver is in a fatigue driving state, and if the result does not exceed the threshold value, the driver eye motion characteristics are learned on line in the meanwhile, and information obtained through online learning are continuously compared till a vehicle stops. By means of the fatigue state detecting method, the driver eye position characteristics are detected, and driver characteristics are learned to distinguish whether the driver is in the fatigue driving state or not, so that accidental risk is prevented in advance, and accordingly driving safety of the driver is improved.

Description

technical field [0001] The invention relates to the technical field of automobile safety, in particular to a fatigue state detection method for eliminating individual differences of drivers by using online learning. Background technique [0002] The increase in the number of motor vehicles has led to an increase in the number of road traffic accidents and the number of accident deaths. According to statistics, global road traffic accidents account for about 90% of the total number of safety accidents. Among the abnormal deaths, road traffic accidents have already Become a veritable "number one killer". Fatigue driving is one of the causes of road traffic accidents, and its probability of causing major traffic accidents is much higher than other traffic accidents. In my country, accidents caused by fatigue driving account for 20% of road traffic accidents and more than 30% of expressway accidents every year, directly leading to the death of more than 3,000 people every year....

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 成波张伟
Owner 清华大学苏州汽车研究院(吴江)
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