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2021 | OriginalPaper | Buchkapitel

First Step Towards Creating a Software Package for Detecting the Dangerous States During Driver Eye Monitoring

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Abstract

The problem of detecting human fatigue by the state of the eyes is considered. A program for detecting the state of open/closed eyes has been developed. The Haar cascades were used to search for faces. Then the eyes were detected on the video from simple web-camera, which allowed us to accumulate a sufficient dataset. Training took place using convolutional neural networks, and due to different lighting conditions, different accuracy characteristics were obtained for the left and right eyes. Using Python programming language with the Jupyter Notebook functionality and the OpenCV library, a software package has been developed that allows us to highlight closed eyes when testing for a learning subject (certain person from whose images the model was trained) with an accuracy of about 90% on a camera with a low resolution (640 by 480 pixels). The proposed solution can be used in the tasks of monitoring driver’s state because one of the most frequent reasons of road accidents is driver fatigue.

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Literatur
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Zurück zum Zitat Andriyanov, N.A., Andriyanov, D.A.: pattern recognition on radar images using augmentation. In: Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020. Institute of Electrical and Electronics Engineers Inc., pp. 289–291 (2020). https://doi.org/10.1109/usbereit48449.2020.9117669 Andriyanov, N.A., Andriyanov, D.A.: pattern recognition on radar images using augmentation. In: Proceedings - 2020 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology, USBEREIT 2020. Institute of Electrical and Electronics Engineers Inc., pp. 289–291 (2020). https://​doi.​org/​10.​1109/​usbereit48449.​2020.​9117669
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Zurück zum Zitat Pimplaskar, D., Nagmode, M., Borkar, A.: Real time eye blinking detection and tracking using openCV. Comput. Sci. 3, 1780–1787 (2013) Pimplaskar, D., Nagmode, M., Borkar, A.: Real time eye blinking detection and tracking using openCV. Comput. Sci. 3, 1780–1787 (2013)
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Zurück zum Zitat Kozlovsky, A.I., Porvatov, I.N., Podolsky, M.S.: Review of automotive systems for operational monitoring of the driver’s condition. Results of own research. Science of Science 6, 1–12 (2013) Kozlovsky, A.I., Porvatov, I.N., Podolsky, M.S.: Review of automotive systems for operational monitoring of the driver’s condition. Results of own research. Science of Science 6, 1–12 (2013)
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Zurück zum Zitat Andriyanov, N.A.: Analysis of the acceleration of neural networks inference on intel processors based on openVINO toolkit. In: 2020 Systems of Signal Synchronization, Generating and Processing in Telecommunications, SYNCHROINFO 2020. Institute of Electrical and Electronics Engineers Inc., pp. 1–5 (2020). https://doi.org/10.1109/synchroinfo49631.2020.9166067 Andriyanov, N.A.: Analysis of the acceleration of neural networks inference on intel processors based on openVINO toolkit. In: 2020 Systems of Signal Synchronization, Generating and Processing in Telecommunications, SYNCHROINFO 2020. Institute of Electrical and Electronics Engineers Inc., pp. 1–5 (2020). https://​doi.​org/​10.​1109/​synchroinfo49631​.​2020.​9166067
Metadaten
Titel
First Step Towards Creating a Software Package for Detecting the Dangerous States During Driver Eye Monitoring
verfasst von
Nikita Andriyanov
Copyright-Jahr
2021
DOI
https://doi.org/10.1007/978-3-030-68821-9_29