التفاصيل البيبلوغرافية
| العنوان: |
Driver fatigue detection system based on eye based features extraction using deep learning algorithm. |
| المؤلفون: |
Swathi, D., Nisha, S. Rahmath, Rajeshram, V., Priyadharshini, V., Pavithra, M., Sowmiya, E., Subiksha, R. S. |
| المصدر: |
AIP Conference Proceedings; 2023, Vol. 2822 Issue 1, p1-6, 6p |
| مصطلحات موضوعية: |
MACHINE learning, DEEP learning, FEATURE extraction, FATIGUE (Physiology), COMPUTER vision, EYE tracking |
| مستخلص: |
Drowsiness and sleepiness impair a driver's ability to control his or her vehicle, as well as their natural reflexes, identification, and perception. Drivers with lower levels of vigilance are seen driving during a night time or overdriving, resulting in accidents and posing a serious menace to humans and community. As a result, in this current trend in the automobile business, it is necessary to have a driver aid system that can find fatigue and weariness in drivers. In this project it suggest a prototype computer vision device that isn't obtrusive for real-time to check a driver's alertness. Because human eyes store a wealth of details about the driver's health, such as peer, degree of focus and weariness, tracking of the eyes is one of the important method for future assistive driving technology. One issue that many eye monitoring systems proposed to this point have is their sensitivity to changes in lighting sources. As a result, their options for car packages are severely limited. The detection and monitoring of attention in real time is a hot topic in the laptop imaginative and prescient community. Face alignment can benefit from attention localization and monitoring. This challenge describes an eye recognition and pursuing technique that works in a variety of light circumstance. It is essentially dependent on an equipment that acquires a driver's position, snapshots, the use of a digital camera, and the construction of a software application that can keep a watch on things and avoid accidents. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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