A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Real Time Driver Alertness System Based on Eye Aspect Ratio and Head Pose Estimation
https://orcid.org/http://orcid.org/0000-0003-0912-7473
https://orcid.org/http://orcid.org/0000-0001-6254-7990
https://orcid.org/http://orcid.org/0000-0002-1483-2583
https://orcid.org/http://orcid.org/0000-0002-0878-7405
https://orcid.org/http://orcid.org/0000-0002-0643-8551
Drowsy driving is one of the main causes of traffic accidents that leads to the loss of men and material. There are two methods to detect the alertness of the driver: first method focuses on the driver’s performance and second method focuses on the driver’s state. Furthermore, methods focusing on driver’s state are of two types groups: methods using brain signals and methods using image processing. This paper presents a real-time image processing system to detect the alertness of a driver based on the estimation of eye-aspect ratio (EAR) and the head-pose (HP) estimation. A camera is used to obtain the data of the driver and computer vision based methods are used to detect driver’s state. The video segments captured by the camera are analyzed using image processing techniques. The EAR and the HP are continuously estimated to detect the alertness of a vehicle driver. The proposed scheme will have benefits in minimizing the accidents by alerting the driving about his current state.
Real Time Driver Alertness System Based on Eye Aspect Ratio and Head Pose Estimation
https://orcid.org/http://orcid.org/0000-0003-0912-7473
https://orcid.org/http://orcid.org/0000-0001-6254-7990
https://orcid.org/http://orcid.org/0000-0002-1483-2583
https://orcid.org/http://orcid.org/0000-0002-0878-7405
https://orcid.org/http://orcid.org/0000-0002-0643-8551
Drowsy driving is one of the main causes of traffic accidents that leads to the loss of men and material. There are two methods to detect the alertness of the driver: first method focuses on the driver’s performance and second method focuses on the driver’s state. Furthermore, methods focusing on driver’s state are of two types groups: methods using brain signals and methods using image processing. This paper presents a real-time image processing system to detect the alertness of a driver based on the estimation of eye-aspect ratio (EAR) and the head-pose (HP) estimation. A camera is used to obtain the data of the driver and computer vision based methods are used to detect driver’s state. The video segments captured by the camera are analyzed using image processing techniques. The EAR and the HP are continuously estimated to detect the alertness of a vehicle driver. The proposed scheme will have benefits in minimizing the accidents by alerting the driving about his current state.
Real Time Driver Alertness System Based on Eye Aspect Ratio and Head Pose Estimation
https://orcid.org/http://orcid.org/0000-0003-0912-7473
https://orcid.org/http://orcid.org/0000-0001-6254-7990
https://orcid.org/http://orcid.org/0000-0002-1483-2583
https://orcid.org/http://orcid.org/0000-0002-0878-7405
https://orcid.org/http://orcid.org/0000-0002-0643-8551
Drowsy driving is one of the main causes of traffic accidents that leads to the loss of men and material. There are two methods to detect the alertness of the driver: first method focuses on the driver’s performance and second method focuses on the driver’s state. Furthermore, methods focusing on driver’s state are of two types groups: methods using brain signals and methods using image processing. This paper presents a real-time image processing system to detect the alertness of a driver based on the estimation of eye-aspect ratio (EAR) and the head-pose (HP) estimation. A camera is used to obtain the data of the driver and computer vision based methods are used to detect driver’s state. The video segments captured by the camera are analyzed using image processing techniques. The EAR and the HP are continuously estimated to detect the alertness of a vehicle driver. The proposed scheme will have benefits in minimizing the accidents by alerting the driving about his current state.
Real Time Driver Alertness System Based on Eye Aspect Ratio and Head Pose Estimation
Lect. Notes in Networks, Syst.
Arsenyeva, Olga (editor) / Romanova, Tatiana (editor) / Sukhonos, Maria (editor) / Tsegelnyk, Yevgen (editor) / Mundra, Ronak (author) / Srinivasulu, Avireni (author) / Ravariu, Cristian (author) / Bhargav, Appasani (author) / Musala, Sarada (author)
International Conference on Smart Technologies in Urban Engineering ; 2022 ; Kharkiv, Ukraine
2022-11-29
10 pages
Article/Chapter (Book)
Electronic Resource
English
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