Efficient Drowsiness Detection by Facial Features Monitoring
نویسندگان
چکیده
منابع مشابه
特集 Drowsiness Detection Using Facial Expression Features*
This paper presents the method of detecting driver’s drowsiness level from the facial expression. The motivation for this research is to realize the novel safety system which can detect the driver’s slight drowsiness and keep the driver awake while driving. The brain wave is commonly used as the drowsiness index. However, it is not suitable for the in-vehicle system since it is measured with se...
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In this paper we describe a real time facial features tracker applied to the detection of some basic drowsiness behaviours in drivers, with a colour camera. It uses stochastic colour segmentation to robustly track a person’s skin and some facial features (eyes and lips).The system recovers 3D face direction, classifies rotation in all viewing directions and detects the driver’s state analysing ...
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This paper demonstrates design and fabrication o f a mechatronic system for human drowsiness detection. This system can be used in multiple places. For example, in factories, it is used on some dangerous machinery and in cars in order t o prevent the operator o r driver from falling asleep. This system is composed of three parts: (1) mechanical, (2) electrical and (3) image processing system. A...
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The increase in vehicle accidents due to the driver drowsiness over the last years highlights the need for developing reliable drowsiness assistant systems by a reference drowsiness measure. Therefore, the thesis at hand is aimed at classifying the driver vigilance state based on eye movements using electrooculography (eog). In order to give an insight into the states of driving, which lead to ...
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Today most accidents are caused by drivers’ fatigue, drowsiness and losing attention on the road ahead. In this paper, a system is introduced, using RGB-D cameras to automatically identify drowsiness and give warning. In this system two important modules have been utilized simultaneously to identify the state of driver’s mouth and eyes for detecting drowsiness. At first, using the depth informa...
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ژورنال
عنوان ژورنال: Research Journal of Applied Sciences, Engineering and Technology
سال: 2014
ISSN: 2040-7459,2040-7467
DOI: 10.19026/rjaset.7.539