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

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4 Author(s)
Guang-Yuan Zhang ; State Key Lab. of Automotive Safety & Energy, Tsinghua Univ., Beijing ; Bo Cheng ; Rui-Jia Feng ; Jia-Wen Li

In the development of advanced vehicle safety systems, monitoring the driverpsilas 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 detection 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 binarization and heuristic rules to screen the contour are firstly used to find the region of interest (ROI) of the driverpsilas eye. Then the Hu invariant moments of the ROI are calculated and further used in developing the SVM 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.

Published in:

Machine Learning and Cybernetics, 2008 International Conference on  (Volume:5 )

Date of Conference:

12-15 July 2008