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A comparative analysis on driver drowsiness detection using CNN | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 1835-1843 اصل مقاله (744.9 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5894 | ||
| نویسندگان | ||
| V. Naren Thiruvalar* ؛ E. Vimal | ||
| Department of Instrumentation and Control Systems Engineering, PSG College of Technology, Coimbatore, India | ||
| تاریخ دریافت: 20 مرداد 1400، تاریخ بازنگری: 12 شهریور 1400، تاریخ پذیرش: 10 آبان 1400 | ||
| چکیده | ||
| The main objective of this project is to detect driver’s drowsiness and alert the driver which is an important precautionary measure in order to avoid accidents. Here two different algorithms based on Convolution Neural Network (CNN) were applied and the results were compared respectively. “Highway Hypnosis” is a serious issue to be addressed while driving especially on highways. Drivers who travel on highways continuously for more than 3 hours must be aware of this serious problem. If there is proper knowledge of it, fatalities would be drastically reduced. In this project, a dedicated detection coupled with an alarm system is provided to alert the driver in case of drowsiness. CNN is used since it is very effective in analyzing images and videos. In this project, a live video feed is used to detect drowsiness by suitable algorithms. | ||
| کلیدواژهها | ||
| CNN؛ Drowsiness Detection؛ Viola-Jones؛ PERCLOS | ||
| مراجع | ||
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[1] A.D. McDonald, J.D. Lee, C. Schwarz and T.L. Brown, A contextual and temporal algorithm for driver drowsiness detection, Accident Anal. Prevent. 113 (2018) 25–37. [2] S. Mehta, S. Dadhich, S. Gumber and A.J. Bhatt, Real-time driver drowsiness detection system using eye aspect ratio and eye closure ratio, SSRN Elect.J. (2019) 1333–1339. [3] P. Viola and M. Jones, Rapid object detection using a boosted cascade of simple features, Proc. 2001 IEEE Computer Soc. Conf. Computer Vision Pattern Recog. (2001). [4] C.S. Wei, Y.T. Wang, C.T. Lin and T.P. Jung, Toward drowsiness detection using non-hair-bearing EEG-based brain-computer interfaces, IEEE Trans. Neural Syst. Rehabilitation Engin. (2018). [5] https://www.nhtsa.gov/technology-innovation. [6] https://www.anapolweiss.com/what-is-highway-hypnosis. [7] https://coursera.community/data-science-8/tools-for-drawing-cnn-architecture-diagrams-6519. [8] https://sefiks.com/2020/11/20/facial-landmarks-for-face-recognition-with-dlib/. [9] https://www.pyimagesearch.com/2017/04/24/eye-blink-detection-opencv-python-dlib/. | ||
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