Results 261 to 270 of about 56,380 (293)

Driver Fatigue Detection Based Intelligent Vehicle Control

18th International Conference on Pattern Recognition (ICPR'06), 2006
Driver fatigue problem is one of the important factors that cause traffic accidents. Therefore the vision-based driver fatigue detection is the most prospective commercial applications of HCI. However, it is a challenging issue due to a variety of factors such as head and eyes moving fast, external illuminations interference and realistic lighting ...
null Zutao Zhang, null Jia-shu Zhang
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Driver fatigue detection system based on DSP

SPIE Proceedings, 2012
To detect driver fatigue states effectively and in real time, a driver fatigue detection system was built, which take ICETEK-DM6347 module as system core, near-infrared LED as light source, and CCD camera as picture gathering device. An improved PER-NORFACE detection method combined several simple and efficient image processing algorithms was ...
Qian Wang, Fu liang Yu, Lixin Song
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Driver fatigue detection based on fuzzy fusion

2008 Chinese Control and Decision Conference, 2008
A method of driver fatigue detection is proposed in this paper. Kalman filter is used to track the eyes. The curvature of up-eyelid and the distance of eyelid are fused to recognize the states of eye. This method can overcome the disadvantage of using single feature which is half-baked, not exact and uncertain.
null Wenhui Dong, null Peishu Qu, null Jing Han   +2 more
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Driver Fatigue Detection using Machine Learning

Since driver weariness plays a significant role in traffic accidents, developing trustworthy detection technologies is crucial to improving road safety. In order to track and evaluate driver fatigue levels in real time, this study presents a machine learning (ML) based method.
Kharat, Tushar, Meshram, Samyank, Kadam, Karan, Kardile, Atharva, Navle, Dr. Mahesh   +4 more
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Driver Fatigue Detection Based on Eye Status

2010 International Conference on Multimedia Technology, 2010
It designed a driver fatigue detection system using the eye's open and close status for decision. It firstly uses an adaptive skin color region for face segmentation. After that, the face region gradient is calculated and adaptively thresholded. It uses a color HOG algorithm to pick out the eye region features.
Sanyuan Zhao, Tin Shen
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Driver Fatigue Detection by Fusing Multiple Cues

2007
A video-based driver fatigue detection system is presented. The system automatically locates the face in the first frame, and then tracks the eyes in subsequent frames. Four cues which characterises fatigue are used to determine the fatigue level.
Rajinda Senaratne, David Hardy, Bill Vanderaa, Saman Halgamuge   +3 more
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Driver Fatigue Detection Using Deep Learning Algorithm

2022
Recently, machine gaining expertise of strategies have been used to predict a driver's circumstance in order to grant records that will decorate road safety. A driver's circumstance can be estimated through a driver's facial expressions and riding behaviors.
Manjesh, H. R., Kumar, B. S. Pavan, Vinay, G., Vinay, N., Anand, M.   +4 more
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Driver Fatigue Detection and Visual Awareness Application

2021
Accidents are a censorious disease suffered by this society, Although the swamping rise of the vehicular industry has become a boon for the human livelihood, the industry also bought many factors of physical disruption. The factors for these disruptions are as follows Driver’s incapability of surrounding awareness, Driver’s Drowsiness, Safety measures ...
Vishnu, Vuggepalli, Prasada, Preeti, Praneetha, Vellanki Kavya   +2 more
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Detecting fatigued drivers with vehicle simulators

2019
In the United States, several major research efforts have been directed at both determining the validity of the current hours-of- service regulations (how long a driver is allowed to be behind the wheel), and developing methods for determining if a driver is fit for duty.
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Using facial landmarks to detect driver fatigue

2022 IEEE XXIX International Conference on Electronics, Electrical Engineering and Computing (INTERCON), 2022
A. Martinez, F. Berrospi, V. Porras, M. Portocarrero   +3 more
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