Bilgisayarlı Görü Yöntemleriyle Sürücüde Uykululuğun Sezimi Detecting Driver Drowsiness Using Computer Vision Techniques
نویسندگان
چکیده
The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Here we employ machine learning techniques to detect driver drowsiness. The system obtained 98% performance in predicting driver drowsiness. This is the highest prediction rate reported to date for detecting real drowsiness. Moreover, the analysis revealed new information about human behavior during drowsy driving.
منابع مشابه
A Survey on Automatic Drowsy Driver Detection System in Image Processing
Due to the increasing growth in population, the occurrence of vehicle accidents has also seen an increase. A detailed analysis shows that, around half million accidents occur in a year, in India alone. Drowsiness and sleeping while driving are now identified as one of the reasons behind fatal crashes and highway accidents caused by drivers. Various drowsiness detection techniques researched are...
متن کاملAutomated Drowsiness Detection For Improved Driving Safety
Several approaches were proposed for the detection and prediction of drowsiness. The approaches can be categorized as estimating the fitness of duty, modeling the sleep-wake rhythms, measuring the vehicle based performance and online operator monitoring. Computer vision based online operator monitoring approach has become prominent due to its predictive ability of detecting drowsiness. Previous...
متن کاملDriver Drowsiness Detection by Identification of Yawning and Eye Closure
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 کاملDrowsiness Detection for Drivers Using Computer Vision
Drowsiness detection system is regarded as an effective tool to reduce the number of road accidents. This project proposes a non-intrusive approach for detecting drowsiness in drivers, using Computer Vision. The algorithm is coded on OpenCV platform in Linux environment. The parameters considered to detect drowsiness are face and eye detection, blinking, eye closure and gaze. Input is captured ...
متن کاملPhysical and Physiological Drowsiness Detection Methods
Driver drowsiness detection technologies have the ability to avoid a catastrophic accident by warning the driver of his drowsiness. A number of methods have been proposed to detect drowsiness in the past few years. These methods are categorized into two major categories. One focuses on detecting physical changes during drowsiness by image processing techniques, such as percentage of eye-closure...
متن کامل