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Eye state recognition method for drivers with glasses
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| Zeitschriftentitel: | Journal of Physics: Conference Series |
|---|---|
| Personen und Körperschaften: | , , , |
| In: | Journal of Physics: Conference Series, 1213, 2019, 5, S. 052049 |
| Format: | E-Article |
| Sprache: | Unbestimmt |
| veröffentlicht: |
IOP Publishing
|
| Schlagwörter: |
| author_facet |
Geng, Lei Yin, Haibing Xiao, Zhitao Xi, Jiangtao Geng, Lei Yin, Haibing Xiao, Zhitao Xi, Jiangtao |
|---|---|
| author |
Geng, Lei Yin, Haibing Xiao, Zhitao Xi, Jiangtao |
| spellingShingle |
Geng, Lei Yin, Haibing Xiao, Zhitao Xi, Jiangtao Journal of Physics: Conference Series Eye state recognition method for drivers with glasses General Physics and Astronomy |
| author_sort |
geng, lei |
| spelling |
Geng, Lei Yin, Haibing Xiao, Zhitao Xi, Jiangtao 1742-6588 1742-6596 IOP Publishing General Physics and Astronomy http://dx.doi.org/10.1088/1742-6596/1213/5/052049 <jats:title>Abstract</jats:title> <jats:p>Eye state recognition is a key step in fatigue detection method. However, factors such as occlusion of different types of glasses and changes in lighting conditions may have some impact on eye state recognition. In order to solve these problems, a driver’s eye state recognition method based on deep learning is proposed. Firstly, the driver’s face images are acquired using an infrared acquisition device. Secondly the multi-task cascaded convolution neural networks are used to detect the face bounding box and feature points of the driver’s face image, and then the eye regions are extracted. Finally the Convolution Neural Network (CNN) is adopted to identify the open and closed state of the eyes. Experimental result shows that the proposed method can accurately identify the state of eyes and help to calculate the fatigue parameters of drivers.</jats:p> Eye state recognition method for drivers with glasses Journal of Physics: Conference Series |
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IOP Publishing, 2019 |
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IOP Publishing |
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Journal of Physics: Conference Series |
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| title |
Eye state recognition method for drivers with glasses |
| title_unstemmed |
Eye state recognition method for drivers with glasses |
| title_full |
Eye state recognition method for drivers with glasses |
| title_fullStr |
Eye state recognition method for drivers with glasses |
| title_full_unstemmed |
Eye state recognition method for drivers with glasses |
| title_short |
Eye state recognition method for drivers with glasses |
| title_sort |
eye state recognition method for drivers with glasses |
| topic |
General Physics and Astronomy |
| url |
http://dx.doi.org/10.1088/1742-6596/1213/5/052049 |
| publishDate |
2019 |
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052049 |
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<jats:title>Abstract</jats:title>
<jats:p>Eye state recognition is a key step in fatigue detection method. However, factors such as occlusion of different types of glasses and changes in lighting conditions may have some impact on eye state recognition. In order to solve these problems, a driver’s eye state recognition method based on deep learning is proposed. Firstly, the driver’s face images are acquired using an infrared acquisition device. Secondly the multi-task cascaded convolution neural networks are used to detect the face bounding box and feature points of the driver’s face image, and then the eye regions are extracted. Finally the Convolution Neural Network (CNN) is adopted to identify the open and closed state of the eyes. Experimental result shows that the proposed method can accurately identify the state of eyes and help to calculate the fatigue parameters of drivers.</jats:p> |
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| author | Geng, Lei, Yin, Haibing, Xiao, Zhitao, Xi, Jiangtao |
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| author_sort | geng, lei |
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| description | <jats:title>Abstract</jats:title> <jats:p>Eye state recognition is a key step in fatigue detection method. However, factors such as occlusion of different types of glasses and changes in lighting conditions may have some impact on eye state recognition. In order to solve these problems, a driver’s eye state recognition method based on deep learning is proposed. Firstly, the driver’s face images are acquired using an infrared acquisition device. Secondly the multi-task cascaded convolution neural networks are used to detect the face bounding box and feature points of the driver’s face image, and then the eye regions are extracted. Finally the Convolution Neural Network (CNN) is adopted to identify the open and closed state of the eyes. Experimental result shows that the proposed method can accurately identify the state of eyes and help to calculate the fatigue parameters of drivers.</jats:p> |
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| spelling | Geng, Lei Yin, Haibing Xiao, Zhitao Xi, Jiangtao 1742-6588 1742-6596 IOP Publishing General Physics and Astronomy http://dx.doi.org/10.1088/1742-6596/1213/5/052049 <jats:title>Abstract</jats:title> <jats:p>Eye state recognition is a key step in fatigue detection method. However, factors such as occlusion of different types of glasses and changes in lighting conditions may have some impact on eye state recognition. In order to solve these problems, a driver’s eye state recognition method based on deep learning is proposed. Firstly, the driver’s face images are acquired using an infrared acquisition device. Secondly the multi-task cascaded convolution neural networks are used to detect the face bounding box and feature points of the driver’s face image, and then the eye regions are extracted. Finally the Convolution Neural Network (CNN) is adopted to identify the open and closed state of the eyes. Experimental result shows that the proposed method can accurately identify the state of eyes and help to calculate the fatigue parameters of drivers.</jats:p> Eye state recognition method for drivers with glasses Journal of Physics: Conference Series |
| spellingShingle | Geng, Lei, Yin, Haibing, Xiao, Zhitao, Xi, Jiangtao, Journal of Physics: Conference Series, Eye state recognition method for drivers with glasses, General Physics and Astronomy |
| title | Eye state recognition method for drivers with glasses |
| title_full | Eye state recognition method for drivers with glasses |
| title_fullStr | Eye state recognition method for drivers with glasses |
| title_full_unstemmed | Eye state recognition method for drivers with glasses |
| title_short | Eye state recognition method for drivers with glasses |
| title_sort | eye state recognition method for drivers with glasses |
| title_unstemmed | Eye state recognition method for drivers with glasses |
| topic | General Physics and Astronomy |
| url | http://dx.doi.org/10.1088/1742-6596/1213/5/052049 |