loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Raluca Brehar ; George Coblişan ; Attila Füzes and Radu Dănescu

Affiliation: Technical University of Cluj-Napoca, Romania

Keyword(s): Object Detection, Distracted Driving, Driver Monitoring.

Abstract: A framework for distracted driving level or the degree of attention which a driver pays to the act of driving, is presented in this paper. It uses visual based action recognition models applied on color images that capture the driver’s face and hands. The proposed approach contains a temporal sequence model that aggregates information from two object detectors which recognize distracting contexts generated by (1) distracting objects that appear in the images such as mobile devices and (2) the face orientation of the driver, the hands and their position with respect to the wheel. The driver’s attention score is predicted using the temporal sequence classification model, a long short term memory, that considers time series features computed based on object detection information.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.226.214.91

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Brehar, R.; Coblişan, G.; Füzes, A. and Dănescu, R. (2023). Driver Attention Estimation Based on Temporal Sequence Classification of Distracting Contexts. In Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-758-670-5; ISSN 2184-2809, SciTePress, pages 578-585. DOI: 10.5220/0012160200003543

@conference{icinco23,
author={Raluca Brehar. and George Coblişan. and Attila Füzes. and Radu Dănescu.},
title={Driver Attention Estimation Based on Temporal Sequence Classification of Distracting Contexts},
booktitle={Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2023},
pages={578-585},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012160200003543},
isbn={978-989-758-670-5},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - Driver Attention Estimation Based on Temporal Sequence Classification of Distracting Contexts
SN - 978-989-758-670-5
IS - 2184-2809
AU - Brehar, R.
AU - Coblişan, G.
AU - Füzes, A.
AU - Dănescu, R.
PY - 2023
SP - 578
EP - 585
DO - 10.5220/0012160200003543
PB - SciTePress