Driver Drowsiness Detection Based on Face Feature and Perclos
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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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...
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 کاملDriver Drowsiness Detection System Based on Feature Representation Learning Using Various Deep Networks
Statistics have shown that 20% of all road accidents are fatigue-related, and drowsy detection is a car safety algorithm that can alert a snoozing driver in hopes of preventing an accident. This paper proposes a deep architecture referred to as deep drowsiness detection (DDD) network for learning effective features and detecting drowsiness given a RGB input video of a driver. The DDD network co...
متن کاملFeature-based Human Face Detection Feature-based Human Face Detection
Human face detection has always been an important problem for face, expression and gesture recognition. Though numerous attempts have been made to detect and localize faces, these approaches have made assumptions that restrict their extension to more general cases. We identify that the key factor in a generic and robust system is that of using a large amount of image evidence, related and reinf...
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ژورنال
عنوان ژورنال: International Journal of Scientific Research in Science and Technology
سال: 2021
ISSN: 2395-602X,2395-6011
DOI: 10.32628/ijsrst218319