Image-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model

The paper analyzes modern methods of driver fatigue. There are a huge variety of methods for assessing the functional states of a person. The detection of the dynamic behavior of the driver in recent years has become an increasingly popular area of research. Dynamic assessment of driver behavior inc...

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Autores principales:	Alexandr Bulygin, Alexey Kashevnik
Formato:	article
Lenguaje:	EN
Publicado:	FRUCT 2021
Materias:	fatigue intelligent transportation systems driver monitoring Telecommunication TK5101-6720
Acceso en línea:	https://doaj.org/article/2ff0e7bdda1e4b41a0cd7e1b04a6d890
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id	oai:doaj.org-article:2ff0e7bdda1e4b41a0cd7e1b04a6d890
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spelling	oai:doaj.org-article:2ff0e7bdda1e4b41a0cd7e1b04a6d8902021-11-20T15:59:33ZImage-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model2305-72542343-073710.23919/FRUCT53335.2021.9599990https://doaj.org/article/2ff0e7bdda1e4b41a0cd7e1b04a6d8902021-10-01T00:00:00Zhttps://www.fruct.org/publications/fruct30/files/Bul.pdfhttps://doaj.org/toc/2305-7254https://doaj.org/toc/2343-0737The paper analyzes modern methods of driver fatigue. There are a huge variety of methods for assessing the functional states of a person. The detection of the dynamic behavior of the driver in recent years has become an increasingly popular area of research. Dynamic assessment of driver behavior includes long-term monitoring, which allows determining functional states, in contrast to modern driver monitoring systems, which assess conditions such as drowsiness and impaired attention for a short (1-10seconds) time interval. Such systems allow us to talk about physiological monitoring, but not neurophysiological, which allows monitoring the functional state of fatigue. Therefore, it makes sense to monitor the state of fatigue of the driver, as well as to warn him in a timely manner in order to avoid collisions with other vehicles.Alexandr BulyginAlexey KashevnikFRUCTarticlefatigueintelligent transportation systemsdriver monitoringTelecommunicationTK5101-6720ENProceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 30, Iss 1, Pp 24-31 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	fatigue intelligent transportation systems driver monitoring Telecommunication TK5101-6720
spellingShingle	fatigue intelligent transportation systems driver monitoring Telecommunication TK5101-6720 Alexandr Bulygin Alexey Kashevnik Image-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model
description	The paper analyzes modern methods of driver fatigue. There are a huge variety of methods for assessing the functional states of a person. The detection of the dynamic behavior of the driver in recent years has become an increasingly popular area of research. Dynamic assessment of driver behavior includes long-term monitoring, which allows determining functional states, in contrast to modern driver monitoring systems, which assess conditions such as drowsiness and impaired attention for a short (1-10seconds) time interval. Such systems allow us to talk about physiological monitoring, but not neurophysiological, which allows monitoring the functional state of fatigue. Therefore, it makes sense to monitor the state of fatigue of the driver, as well as to warn him in a timely manner in order to avoid collisions with other vehicles.
format	article
author	Alexandr Bulygin Alexey Kashevnik
author_facet	Alexandr Bulygin Alexey Kashevnik
author_sort	Alexandr Bulygin
title	Image-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model
title_short	Image-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model
title_full	Image-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model
title_fullStr	Image-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model
title_full_unstemmed	Image-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model
title_sort	image-based fatigue detection of vehicle driver: state-of-the-art and reference model
publisher	FRUCT
publishDate	2021
url	https://doaj.org/article/2ff0e7bdda1e4b41a0cd7e1b04a6d890
work_keys_str_mv	AT alexandrbulygin imagebasedfatiguedetectionofvehicledriverstateoftheartandreferencemodel AT alexeykashevnik imagebasedfatiguedetectionofvehicledriverstateoftheartandreferencemodel
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Image-Based Fatigue Detection of Vehicle Driver: State-of-the-Art and Reference Model

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