Driver Drowsiness Detection Algorithm based on Facial Features
نویسندگان
چکیده
منابع مشابه
The Mechanical Design of Drowsiness Detection Using Color Based Features
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...
متن کاملA Review on Driver Drowsiness Detection Techniques
Number of accidents during driving is increasing day by day and drowsy driving has been implicated as a causal factor in many accidents. Goal of driver drowsiness detection systems is to reduce these accidents. It has been seen that most of the accidents occur due to driver’s fatigue and a small due to inattention factor, therefore this paper reviews driver’s fatigue monitoring techniques in de...
متن کامل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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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: Journal of Korea Multimedia Society
سال: 2016
ISSN: 1229-7771
DOI: 10.9717/kmms.2016.19.11.1852