Driver Drowsiness Detection Using Multi-Channel Second Order Blind Identifications
نویسندگان
چکیده
منابع مشابه
Driver Drowsiness Detection Using Multi-feature Analysis
now a day’s Road accidents are common in developed as well as developing countries. These accidents happen due to different different reasons like sleeping disorders, working in night shift or more than eight hours as over time, side effects of medicine, alcohol, speeding, freakishness of teenager’s etc. One of the most important reasons is drowsiness. Drowsiness means sleepiness, which affects...
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Drivers who do not take regular breaks when driving long distances run a high risk of becoming drowsy a state which they often fail to recognize early enough according to the experts. Studies show that around one quarter of all serious motorway accidents are attributable to sleepy drivers in need of a rest, meaning that drowsiness causes more road accidents than drink-driving. Attention assist ...
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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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In the present paper a Multi Input Multi Output (MIMO) source separation method for dynamic channels is proposed. The algorithm is based on second order statistics of the observed signals. A new separation structure, based on cofactors, is proposed with a parametrization such as to reduce the number of estimated parameters to a minimum. Simulations with the algorithm are presented.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2019
ISSN: 2169-3536
DOI: 10.1109/access.2019.2891971