Fatigue driving detection device and detection method based on machine vision human eye recognition

Abstract

The invention discloses a fatigue driving detection method based on machine vision human eye recognition. The detection method includes the steps: capturing a human face in a captured image, and tracking and positioning human eyes in real time to obtain a human eye image; processing the human eye image; extracting eye characteristics of a human eye area-of-interest; acquiring human eye characteristics in a waking state, fusing the characteristics according to the acquired human eye height characteristics and human eye blinking frequency characteristics, and judging degree of fatigue; giving analarm for the degree of fatigue. The eye characteristics include the human eye height characteristics and the human eye blinking frequency characteristics. By extracting the eye characteristics of auser, PERCLOS in a detection cycle is calculated and then compared with set PERCLOS, different degrees of fatigue are distinguished according to comparison results, and the user is reminded of two different degrees of fatigue including slight fatigue and severe fatigue. The invention further discloses a fatigue driving detection device based on machine vision human eye recognition.

Description

technical field [0001] The invention relates to a fatigue driving detection device, in particular to a fatigue driving detection device and detection method based on machine vision and human eye recognition. Background technique [0002] According to incomplete statistics, there are at least 100,000 traffic accidents caused by fatigue driving in the world every year, causing direct economic losses as high as 12.5 billion US dollars. Faced with such a severe social reality, some research has been done at home and abroad. There are five main aspects of detection technology, which are based on physiological signals, body responses, manipulation behavior, vehicle behavior, and information fusion. [0003] Fatigue detection methods based on physiological signals usually require the driver to wear corresponding devices (electrodes, EEG caps, etc.) The fatigue change process produces great interference, so it is not suitable for application in actual conditions, and is mostly used...

AI Technical Summary

Problems solved by technology

There is no simple and perfect fatigue detection device and fatigue driving reminder device on the market at home and abroad. The existing fatigue detection devices in foreign countries have high detection costs and the fatigue detection effect is not ideal.

Images