Driver’s Eye State Detection Based on Support Vector Machine-decision Tree

GUAN Yu-ping; SONG Li-xin

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Driver’s Eye State Detection Based on Support Vector Machine-decision Tree

更新时间：2026-07-10

- Driver’s Eye State Detection Based on Support Vector Machine-decision Tree
- Vol. 15, Issue 6, Pages: 5-8(2010)
- 作者机构：
  
  哈尔滨理工大学电气与电子工程学院
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP274
- Published：2010
- 稿件说明：
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GUAN Yu-ping, SONG Li-xin. Driver’s Eye State Detection Based on Support Vector Machine-decision Tree[J]. 2010, 15(6): 5-8.
DOI：

GUAN Yu-ping, SONG Li-xin. Driver’s Eye State Detection Based on Support Vector Machine-decision Tree[J]. 2010, 15(6): 5-8. DOI：

摘要

为提高驾驶疲劳检测系统中人眼状态检测的速度和准确性

提出一种基于支持向量机决策树(SVMDT)的人眼检测方法

此方法可以同时完成人眼的定位与状态检测.首先对样本进行光照不均校正和直方图处理

然后用离散余弦变换和主成分分析提取特征向量

用SVMDT训练得到睁-闭眼和有-无眼子分类器.检测时先用先验知识去除部分非人眼区域

最后利用SVMDT进行人眼检测.实验证明此方法提高了人眼状态检测的速度

同时也有较好的准确性.

Abstract

In order to improve the detecting speed and the accuracy in driver fatigue detection

an eye detection method based on SVM-Decision Tree is proposed in this paper

which can achieve the location and the state detection of the eyes at the same time.Firstly

the eye samples are processed through uneven light correction and histogram specification;then extracted by DCT and PCA

the feature vector is trained by SVMDT

thus the open-close eye sub-classifier and the yes-no eye sub-classifier can be obtained.In the det...

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