基于眼距检测的驾驶员睡意检测

2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) Pub Date : 1900-01-01 DOI:10.1109/SITIS.2016.110

Oraan Khunpisuth, Taweechai Chotchinasri, Varakorn Koschakosai, Narit Hnoohom

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引用次数: 47

摘要

本文的目的是设计一种方法来提醒昏昏欲睡的司机在驾驶行为。车祸的原因之一是司机的睡意。因此，本研究试图通过创建一个实验来计算困倦程度来解决这个问题。本文的一个要求是利用树莓派相机和树莓派3模块，它们能够计算驾驶员的困倦程度。驾驶员头部倾斜和眨眼的频率被用来判断驾驶员是否感到昏昏欲睡。通过对10名志愿者的评估，面部和眼睛检测的准确率高达99.59%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Driver Drowsiness Detection Using Eye-Closeness Detection

The purpose of this paper was to devise a way to alert drowsy drivers in the act of driving. One of the causes of car accidents comes from drowsiness of the driver. Therefore, this study attempted to address the issue by creating an experiment in order to calculate the level of drowsiness. A requirement for this paper was the utilisation of a Raspberry Pi Camera and Raspberry Pi 3 module, which were able to calculate the level of drowsiness in drivers. The frequency of head tilting and blinking of the eyes was used to determine whether or not a driver felt drowsy. With an evaluation on ten volunteers, the accuracy of face and eye detection was up to 99.59 percent.

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2016 12th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS)

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