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Received:October 15, 2020 Revised:November 18, 2020
Received:October 15, 2020 Revised:November 18, 2020
中文摘要: 针对现有疲劳驾驶检测方法中实时性和泛化能力不足的问题, 本文提出了一种基于卷积神经网络(Convolutional Neural Networks, CNN)和支持向量机(Support Vector Machine, SVM)的疲劳驾驶闭眼特征检测方法, 使用CNN获取人脸相关特征点的位置并定位眼部感兴趣区域(Region Of Interest, ROI), 通过灰度化和直方图均衡化操作减弱光照差异的影响, 提取ROI的方向梯度直方图(Histogram of Oriented Gradient, HOG), 并用SVM对HOG进行分类, 相应的判断出原始图像是否包含疲劳驾驶闭眼特征. 本文给出了所提方法在PC平台和ARM平台实现的实时性验证, 在不同光照和背景条件下对多位受测人员进行测试, 实验结果表明该方法对疲劳驾驶闭眼特征检测准确率在94%以上, 处理速度满足实时性要求, 且具有较强的泛化能力.
Abstract:To deal with the insufficient competence for real-time detection and generalization of the existing methods for fatigue driving detection, this study proposes a detection method of eye closure features, which integrates the Convolutional Neural Network (CNN) and Support Vector Machine (SVM). The CNN is employed to extract facial feature points and locate the eye Region Of Interest (ROI). Then the Histogram of Oriented Gradient (HOG) of the ROI serves as the feature classified by SVM to determine whether there exists the eye closure feature of fatigue driving in the original image. There into, graying and histogram equalization contribute to weakening the impact of illumination variation. The proposed method is implemented on both the PC platform and the ARM embedded platform, which is verified with regard to examinees subject to different levels of illumination. Experimental results prove that the method reaches an accuracy of above 94% for detecting eye closure features, with strong generalization and satisfied real-time reaction.
keywords: fatigue driving eye closure detection cascade Convolutional Neural Networks (CNN) histogram equalization Support Vector Machine (SVM)
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王俊杰,汪洋堃,张峰,张士文,戴毅,郁晓冬.基于CNN和SVM的疲劳驾驶闭眼特征实时检测.计算机系统应用,2021,30(6):118-126
WANG Jun-Jie,WANG Yang-Kun,ZHANG Feng,ZHANG Shi-Wen,DAI Yi,YU Xiao-Dong.Real-Time Detection for Eye Closure Feature of Fatigue Driving Based on CNN and SVM.COMPUTER SYSTEMS APPLICATIONS,2021,30(6):118-126
王俊杰,汪洋堃,张峰,张士文,戴毅,郁晓冬.基于CNN和SVM的疲劳驾驶闭眼特征实时检测.计算机系统应用,2021,30(6):118-126
WANG Jun-Jie,WANG Yang-Kun,ZHANG Feng,ZHANG Shi-Wen,DAI Yi,YU Xiao-Dong.Real-Time Detection for Eye Closure Feature of Fatigue Driving Based on CNN and SVM.COMPUTER SYSTEMS APPLICATIONS,2021,30(6):118-126
