research-article

An eye tracking dataset for point of gaze detection

Authors:

Christopher D. McMurrough,

Vangelis Metsis,

Jonathan Rich,

Fillia MakedonAuthors Info & Claims

ETRA '12: Proceedings of the Symposium on Eye Tracking Research and Applications

Pages 305 - 308

https://doi.org/10.1145/2168556.2168622

Published: 28 March 2012 Publication History

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Abstract

This paper presents a new, publicly available eye tracking dataset, aimed to be used as a benchmark for Point of Gaze (PoG) detection algorithms. The dataset consists of a set of videos recording the eye motion of human test subjects as they were looking at, or following, a set of predefined points of interest on a computer visual display unit. The eye motion was recorded using a Mobile Eye, head mounted, infrared monocular camera. The ground truth of the point of gaze and head location and direction in the three dimensional space are provided together with the data. The ground truth regarding the point of gaze at is known in advance since the subjects are always looking at predefined targets, whereas, the head position in 3D is captured using a Vicon Motion Tracking System.

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Mathew AKhan AKhalid TSouissi R(2024)GESCAM : A Dataset and Method on Gaze Estimation for Classroom Attention Measurement2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW63382.2024.00068(636-645)Online publication date: 17-Jun-2024
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Index Terms

An eye tracking dataset for point of gaze detection
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Tracking
      2. Computer vision tasks
        Scene understanding

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Published In

ETRA '12: Proceedings of the Symposium on Eye Tracking Research and Applications

March 2012

420 pages

ISBN:9781450312219

DOI:10.1145/2168556

Conference Chairs:
Carlos H. Morimoto
University of São Paulo, Brazil
,
Howell Istance
Montfort University, UK
,
Editor:
Stephen N. Spencer
University of Washington
,
Program Chairs:
Jeffrey B. Mulligan
NASA
,
Pernilla Qvarfordt
FX Palo Alto

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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Association for Computing Machinery

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Published: 28 March 2012

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Division of Computer and Network Systems

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ETRA '12

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ETRA '12: Eye Tracking Research and Applications

March 28 - 30, 2012

California, Santa Barbara

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https://doi.org/10.1109/WACV57701.2024.00588
Kotwal KÖzbulak GMarcel S(2024)Assessing the Reliability of Biometric Authentication on Virtual Reality Devices2024 IEEE International Joint Conference on Biometrics (IJCB)10.1109/IJCB62174.2024.10744429(1-9)Online publication date: 15-Sep-2024
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Mathew AKhan AKhalid TSouissi R(2024)GESCAM : A Dataset and Method on Gaze Estimation for Classroom Attention Measurement2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW63382.2024.00068(636-645)Online publication date: 17-Jun-2024
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Recommendations

Low-cost head position tracking for gaze point estimation

Eye detection and coarse localization of pupil for video-based eye tracking systems

Pupil vs. Eyelid: Evaluating the Accuracy of Blink Detection in Pupil-based Eye Tracking Devices

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