Driver attention state monitoring method and device

Abstract

The invention discloses driver attention state monitoring method and device. An output port of a camera is connected with an input port of a video decoder, and a digital signal processor is externally connected with the video decoder, a storage, a power supply and an alarm buzzer respectively. The method comprises the following steps of: acquiring a face video detection image of a driver by the camera, using the transverse width between two eyes of the driver and the longitudinal distance from the mouth to the middle point of a connecting line of the two eyes, which are detected under the normal state, as standard distances for locating the face, and resetting the standard distances whenever the face is located; comparing the distances actually detected in the driving process with the standard distances; and judging whether the driver is distracted according to the change obtained by comparing the actually detected distances and the standard distances. The invention can monitor the whole forming process of tiredness and distraction of the driver, judge whether the drive is tired and distracted, capture the distraction state of the driver in time, warn dangerous driving behavior such as distraction, and guarantee the safe driving of the driver.

Description

technical field [0001] The invention relates to the technical field of transportation engineering, in particular to a method and a device for detecting driver's attention. Background technique [0002] Drivers often lose control of the direction of the vehicle when they are driving fatigued, distracted by the surrounding things, answering mobile phones, or taking care of minors in the car, resulting in discontinuous and disordered driving behavior. The notable feature is lane departure , rear-end collision and other vehicle accidents. According to this feature, Wang Rongben, Guo Lie and others introduced the use of machine vision technology to monitor drivers in the "Research on Comprehensive Driving Safety Guarantee System Based on Machine Vision" published in July 2006, Volume 14, No. 2, Journal of Shandong Jiaotong University. Based on the movement characteristics of the eyes, mouth, head and other organs, a comprehensive quantitative evaluation model of driver fatigue a...

AI Technical Summary

Problems solved by technology

Driving behavior is a process that requires a high degree of concentration at all times. A small negligence may lead to a fatal accident, and the driver goes from a quasi-awake state of distracted driving to a listless and drowsy state. The formation of fatigue to the dozing state is also a process. When it is detected that the driver is yawning or even dozing off due to fatigue, it may be too late, and the accident is inevitable, and it is difficult to effectively protect the safety of the driver’s life and property.

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