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Article

On-road driver eye movement tracking using head-mounted devices

Authors:

S. KirschenbaumAuthors Info & Claims

ETRA '02: Proceedings of the 2002 symposium on Eye tracking research & applications

Pages 61 - 68

https://doi.org/10.1145/507072.507086

Published: 25 March 2002 Publication History

Abstract

It is now evident from anecdotal evidence and preliminary research that distractions can hinder the task of operating a vehicle, and consequently reduce driver safety. However with increasing wireless connectivity and the portability of office devices, the vehicle of the future is visualized as an extension of the static work place - i.e. an office-on-the-move, with a phone, a fax machine and a computer all within the reach of the vehicle operator. For this research a Head mounted Eye-tracking Device (HED), is used for tracking the eye movements of a driver navigating a test route in an automobible while completing various driving tasks. Issues arising from data collection of eye movements during the completion of various driving tasks as well as the analysis of this data are discussed. Methods for collecting video and scan-path data, as well as difficulties and limitations are also reported.

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https://doi.org/10.1109/ICITE56321.2022.10101399
Razi AChen XLi HWang HRusso BChen YYu H(2022)Deep learning serves traffic safety analysis: A forward‐looking reviewIET Intelligent Transport Systems10.1049/itr2.1225717:1(22-71)Online publication date: 27-Aug-2022
https://doi.org/10.1049/itr2.12257
Tabuchi MHirotomi T(2022)Using Fiducial Marker for Analyzing Wearable Eye-Tracker Gaze Data Measured While CookingHCI International 2022 - Late Breaking Papers. Multimodality in Advanced Interaction Environments10.1007/978-3-031-17618-0_15(192-204)Online publication date: 2-Oct-2022
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On-road driver eye movement tracking using head-mounted devices
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks

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Published In

cover image ACM Conferences

ETRA '02: Proceedings of the 2002 symposium on Eye tracking research & applications

March 2002

156 pages

ISBN:1581134673

DOI:10.1145/507072

Conference Chair:
Andrew T. Duchowski
Clemson University
,
Program Chairs:
Roel Vertegaal
Queens University (Canada)
,
John W. Senders
University of Toronto (Canada)

Copyright © 2002 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 25 March 2002

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ETRA02: Eye Tracking Research and Application

March 25 - 27, 2002

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ETRA '02 Paper Acceptance Rate 18 of 29 submissions, 62%;

Overall Acceptance Rate 69 of 137 submissions, 50%

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Cited By

Shi WLiu Y(2022)A Novel Navigation System on AR Helmet with Driving Attention Analysis2022 IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE)10.1109/ICITE56321.2022.10101399(204-208)Online publication date: 11-Nov-2022
https://doi.org/10.1109/ICITE56321.2022.10101399
Razi AChen XLi HWang HRusso BChen YYu H(2022)Deep learning serves traffic safety analysis: A forward‐looking reviewIET Intelligent Transport Systems10.1049/itr2.1225717:1(22-71)Online publication date: 27-Aug-2022
https://doi.org/10.1049/itr2.12257
Tabuchi MHirotomi T(2022)Using Fiducial Marker for Analyzing Wearable Eye-Tracker Gaze Data Measured While CookingHCI International 2022 - Late Breaking Papers. Multimodality in Advanced Interaction Environments10.1007/978-3-031-17618-0_15(192-204)Online publication date: 2-Oct-2022
https://doi.org/10.1007/978-3-031-17618-0_15
Fan XWang FSong DLu YLiu J(2021)GazMon: Eye Gazing Enabled Driving Behavior Monitoring and PredictionIEEE Transactions on Mobile Computing10.1109/TMC.2019.296276420:4(1420-1433)Online publication date: 1-Apr-2021
https://doi.org/10.1109/TMC.2019.2962764
Panetta KWan QRajeev SKaszowska AGardony ANaranjo KTaylor HAgaian S(2020)ISeeColor: Method for Advanced Visual Analytics of Eye Tracking DataIEEE Access10.1109/ACCESS.2020.29809018(52278-52287)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2980901
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Li RVictor Chen YZhang LShen ZCheryl Qian Z(2020)Effects of Perception of Head-Up Display on the Driving Safety of Experienced and Inexperienced DriversDisplays10.1016/j.displa.2020.101962(101962)Online publication date: Jun-2020
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Panetta KWan QKaszowska ATaylor HAgaian S(2019)Software Architecture for Automating Cognitive Science Eye-Tracking Data Analysis and Object AnnotationIEEE Transactions on Human-Machine Systems10.1109/THMS.2019.289291949:3(268-277)Online publication date: Jun-2019
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Hochin TShinohara YNishizaki Y(2019)Detection of Driver's Eye Fixation on a Moving Target by Using Line Fitting2019 6th International Conference on Computational Science/Intelligence and Applied Informatics (CSII)10.1109/CSII.2019.00010(13-18)Online publication date: May-2019
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Hochin TShinohara YNishizaki Y(2019)Detection of Driver’s Eye Fixation on a Moving Target by Using Line Fitting2019 IEEE International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD)10.1109/BCD.2019.8885069(94-99)Online publication date: May-2019
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