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A dataset for point of gaze detection using head poses and eye images

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Abstract

This paper presents a new, publicly available dataset, aimed to be used as a benchmark for Point of Gaze (PoG) detection algorithms. The dataset consists of two modalities that can be combined for PoG definition: (a) a set of videos recording the eye motion of human participants as they were looking at, or following, a set of predefined points of interest on a computer visual display unit (b) a sequence of 3D head poses synchronized with the video. The eye motion was recorded using a Mobile Eye-XG, head mounted, infrared monocular camera and the head position by using a set of Vicon motion capture cameras. 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 is known in advance since the participants are always looking at predefined targets on a monitor.

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Notes

  1. http://www.vicon.com/.

  2. http://www.asleyetracking.com/.

  3. The dataset can be downloaded from:heracleia.uta.edu/eyetracking.

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Acknowledgments

This work is supported in part by the National Science Foundation under award numbers CNS 0923494 and CNS 1035913. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. The University of Texas at Arlington, Arlington, USA

    Christopher D. McMurrough, Vangelis Metsis & Fillia Makedon

  2. Rutgers, The State University of New Jersey, TEI Crete, Piscataway, USA

    Dimitrios Kosmopoulos

  3. University of Piraeus, Piraeus, Greece

    Ilias Maglogiannis

Authors
  1. Christopher D. McMurrough
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  2. Vangelis Metsis
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  3. Dimitrios Kosmopoulos
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  4. Ilias Maglogiannis
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  5. Fillia Makedon
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Corresponding author

Correspondence to Ilias Maglogiannis.

Additional information

This work is supported in part by the National Science Foundation under award numbers CNS 0923494 and CNS 1035913. Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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McMurrough, C.D., Metsis, V., Kosmopoulos, D. et al. A dataset for point of gaze detection using head poses and eye images. J Multimodal User Interfaces 7, 207–215 (2013). https://doi.org/10.1007/s12193-013-0121-4

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  • DOI: https://doi.org/10.1007/s12193-013-0121-4

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