Real-time driver eye detection method using Support Vector Machine with Hu invariant moments

被引：7

作者：

Zhang, Guang-Yuan ^{[1
]}

Cheng, Bo ^{[1
]}

Feng, Rui-Jia ^{[1
]}

Li, Jia-Wen ^{[1
]}

机构：

[1] Tsinghua Univ, State Key Lab Automot Safety & Energy, Beijing 100084, Peoples R China

来源：

PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2008年

关键词：

non-intrusive; real-time; eye detection; Support Vector Machine; Hu moment invariant;

D O I：

10.1109/ICMLC.2008.4620921

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In the development of advanced vehicle safety systems, monitoring the driver's vigilance level and issuing an alert when he is not paying enough attention to the road is a promising way to reduce the road accidents. In such driver monitoring systems, developing a reliable real-time driver eye defection method is a crucial part. In this paper, a rear-time eye detection method using Support Vector Machine (SVM) with Hu invariant moments is proposed. In the method binaryzation and heuristic rules to screen the contour are firstly used to find the Region Of Interest (ROI) of the driver's eye. Then the Hu invariant moments of the ROI are calculated and further used in developing the MINI model. The test sets from the experiment were used to validate the classification results. The validation results and conclusions about the performance of the method are presented.

引用

页码：2999 / +

页数：3

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