基于机器视觉的驾驶员嘴部状态检测方法研究
首发时间:2004-03-16
摘要:在采用机器视觉对驾驶员进行驾驶行为监测时,嘴部状态识别是关键技术之一。事实上,驾驶员在正常驾驶、说话及打哈欠(瞌睡)三种状态下的嘴部张开程度有一定的区别。根据这一特点,本文利用Fisher分类器提取嘴唇的轮廓和位置,然后利用嘴唇区域的几何特征作为特征值,组成特征矢量,作为三层BP神经网络的输入,输出对应正常驾驶、说话及打哈欠(瞌睡)三种不同精神状态。试验结果表明,该网络可快速有效地识别驾驶员嘴部状态。
关键词: 行为监测; 机器视觉 Fisher分类器; 特征提取 BP神经网络.
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Study on Monitoring Method of Driver Mouth State
Abstract:When we use the machine vision to inspect the driver’s driving behavior, the identifying of the mouth state is one of the key technologies. In fact, when a driver drives in a normal, talking or dozing state, his/her mouth opening degree will quite different. According to this fact, this paper uses the Fisher classifier to extract the mouth figure and site, then uses the mouth region’s geometry character as the feature value, and put all of these features to make up an eigenvector as the input of a three-level Bp network, then we get the output among three different spirit states. The experiment results show that this new method can inspect the driver’s mouth region state accurately and quickly.
Keywords: Behavior inspection Machine vision Fisher classifier Features extraction BP network.
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No.4812048107939945****
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