Facial feature based driver attention state detection method

A state detection and facial feature technology, applied in the field of intelligent vehicle safety assistance driving, can solve the problems of reducing driver fatigue and the accuracy of distraction state detection system

Inactive Publication Date: 2016-05-11
CHINA FIRST AUTOMOBILE
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  • Description
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AI Technical Summary

Problems solved by technology

However, after successfully extracting the driver's physiological response characteristics (eyelid size, blink times, gaze direction, etc.), there are certain problems in judging from the driver's physiological response characteristics to

Method used

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  • Facial feature based driver attention state detection method
  • Facial feature based driver attention state detection method
  • Facial feature based driver attention state detection method

Examples

Experimental program
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Effect test

Embodiment 1

[0079] The driver's facial feature collection and extraction system adopted is SmartEye, its sampling frequency is 50Hz, and the reading frequency of driver's facial feature parameters is 50Hz.

[0080] Such as figure 2 As shown, the driver's attention state detection method based on facial features of the present invention comprises the following steps:

[0081] 1. Driver fatigue state detection based on PERCLOS;

[0082] 2. Driver fatigue state detection based on blink frequency;

[0083] 3. Driver distraction detection based on sight distribution;

[0084] 4. Early warning of driver fatigue or distraction;

[0085] The driver's fatigue state detection based on PERCLOS described in the technical solution comprises the following steps:

[0086] 1. If figure 1 As shown, according to the differences of different drivers, the steps of initializing the driver's eyelid size threshold are as follows:

[0087] a. Read and save the eyelid size of the first 500 groups of driver...

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Abstract

The invention relates to a facial feature based driver attention state detection method. The detection method is characterized by comprising the following steps of performing PERCLOS based driver fatigue state detection; performing blink frequency based driver fatigue state detection; performing sight line distribution based driver attention distraction state detection; and sending out early warning for driver fatigue and attention distraction state, wherein the early warning for fatigue or attention distraction state is carried out continuously for a certain time to avoid frequent switching between different states; the early warning priority is as follows: fatigue driving is greater than attention distraction that is greater than normal driving; and the attention state of the driver can be accurately detected through the physiological reaction characteristics of the driver, and early warning is sent out for driver fatigue and the attention distraction state; collection and extraction of the facial features of the driver are not included; the sampling efficiency of the adopted driver facial feature collection and extracting system is fHz; and the frequency for reading the driver facial feature is f<0> Hz.

Description

technical field [0001] The invention relates to a method for detecting a driver's attention state, in particular to a method for detecting a driver's attention state based on facial features, and belongs to the field of intelligent vehicle safety assisted driving. Background technique [0002] Driver fatigue and distraction are important factors causing road traffic accidents. Studies have shown that more than 23% of collisions and near-collisions are related to the state of driver's attention. However, with the continuous increase of in-vehicle information systems, this phenomenon is becoming more and more serious. [0003] Real-time and effective detection of driver's fatigue and distraction is an important measure to improve driving safety and road traffic environment. [0004] At present, the methods for detecting the driver's attention state can be roughly divided into five types: [0005] 1) Detection methods based on the driver's physiological signals, such as EEG, ...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06V20/597
Inventor 刘月杰李胜江朱俊洁孙婧金立生牛清宁
Owner CHINA FIRST AUTOMOBILE
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