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Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition
This paper introduces a real-time Driver Monitoring System (DMS) designed to monitor driver behavior while driving, employing facial landmark estimation-based behavior recognition. The system utilizes an infrared (IR) camera to capture and analyze video data. Through facial landmark estimation, cruc...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10600215/ https://www.ncbi.nlm.nih.gov/pubmed/37880264 http://dx.doi.org/10.1038/s41598-023-44955-1 |
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author | Kim, Dohun Park, Hyukjin Kim, Tonghyun Kim, Wonjong Paik, Joonki |
author_facet | Kim, Dohun Park, Hyukjin Kim, Tonghyun Kim, Wonjong Paik, Joonki |
author_sort | Kim, Dohun |
collection | PubMed |
description | This paper introduces a real-time Driver Monitoring System (DMS) designed to monitor driver behavior while driving, employing facial landmark estimation-based behavior recognition. The system utilizes an infrared (IR) camera to capture and analyze video data. Through facial landmark estimation, crucial information about the driver’s head posture and eye area is extracted from the detected facial region, obtained via face detection. The proposed method consists of two distinct modules, each focused on recognizing specific behaviors. The first module employs head pose analysis to detect instances of inattention. By monitoring the driver’s head movements along the horizontal and vertical axes, this module assesses the driver’s attention level. The second module implements an eye-closure recognition filter to identify instances of drowsiness. Depending on the continuity of eye closures, the system categorizes them as either occasional drowsiness or sustained drowsiness. The advantages of the proposed method lie in its efficiency and real-time capabilities, as it solely relies on IR camera video for computation and analysis. To assess its performance, the system underwent evaluation using IR-Datasets, demonstrating its effectiveness in monitoring and recognizing driver behavior accurately. The presented real-time Driver Monitoring System with facial landmark-based behavior recognition offers a practical and robust approach to enhance driver safety and alertness during their journeys. |
format | Online Article Text |
id | pubmed-10600215 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106002152023-10-27 Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition Kim, Dohun Park, Hyukjin Kim, Tonghyun Kim, Wonjong Paik, Joonki Sci Rep Article This paper introduces a real-time Driver Monitoring System (DMS) designed to monitor driver behavior while driving, employing facial landmark estimation-based behavior recognition. The system utilizes an infrared (IR) camera to capture and analyze video data. Through facial landmark estimation, crucial information about the driver’s head posture and eye area is extracted from the detected facial region, obtained via face detection. The proposed method consists of two distinct modules, each focused on recognizing specific behaviors. The first module employs head pose analysis to detect instances of inattention. By monitoring the driver’s head movements along the horizontal and vertical axes, this module assesses the driver’s attention level. The second module implements an eye-closure recognition filter to identify instances of drowsiness. Depending on the continuity of eye closures, the system categorizes them as either occasional drowsiness or sustained drowsiness. The advantages of the proposed method lie in its efficiency and real-time capabilities, as it solely relies on IR camera video for computation and analysis. To assess its performance, the system underwent evaluation using IR-Datasets, demonstrating its effectiveness in monitoring and recognizing driver behavior accurately. The presented real-time Driver Monitoring System with facial landmark-based behavior recognition offers a practical and robust approach to enhance driver safety and alertness during their journeys. Nature Publishing Group UK 2023-10-25 /pmc/articles/PMC10600215/ /pubmed/37880264 http://dx.doi.org/10.1038/s41598-023-44955-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Kim, Dohun Park, Hyukjin Kim, Tonghyun Kim, Wonjong Paik, Joonki Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition |
title | Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition |
title_full | Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition |
title_fullStr | Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition |
title_full_unstemmed | Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition |
title_short | Real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition |
title_sort | real-time driver monitoring system with facial landmark-based eye closure detection and head pose recognition |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10600215/ https://www.ncbi.nlm.nih.gov/pubmed/37880264 http://dx.doi.org/10.1038/s41598-023-44955-1 |
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