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Interactive Visualization for Understanding of Attention Patterns

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Eye Tracking and Visualization (ETVIS 2015)

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

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Abstract

Discovering users’ behavior via eye-tracking data analysis is a common task that has important implications in many domains including marketing, design, behavior study, and psychology. In our project, we are interested in analyzing eye-tracking data to investigate differences between age groups in emotion regulation using visual attention. To achieve this goal, we adopted a general-purposed interactive visualization method, namely Glyph, to conduct temporal analysis on participants’ fixation data. Glyph facilitates comparison of abstract data sequences to understand group and individual patterns. In this article, we show how a visualization system adopting the Glyph method can be constructed, allowing us to understand how users shift their fixations and dwelling given different stimuli, and how different user groups differ in terms of these temporal eye-tracking patterns. The discussion demonstrates the utility of Glyph not only for the purpose of our project, but also for other eye-tracking data analyses that require exploration within the space of temporal patterns.

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Acknowledgements

This work was supported in part by NIA grant R21 AG044961.

Author information

Authors and Affiliations

  1. Texas A&M University-Commerce, 2200 Campbell St, Commerce, TX, 75428, USA

    Truong-Huy D. Nguyen

  2. Northeastern University, 360 Huntington Avenue, Boston, MA, 02115, USA

    Magy Seif El-Nasr & Derek M. Isaacowitz

Authors
  1. Truong-Huy D. Nguyen
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  2. Magy Seif El-Nasr
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  3. Derek M. Isaacowitz
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Corresponding author

Correspondence to Truong-Huy D. Nguyen .

Editor information

Editors and Affiliations

  1. VISUS, University of Stuttgart, Stuttgart, Germany

    Michael Burch

  2. Max Planck Institute for Biological Cybernetics, TĂĽbingen, Germany

    Lewis Chuang

  3. SIAT, Simon Fraser University, Surrey, British Columbia, Canada

    Brian Fisher

  4. VIS, University of Stuttgart, Stuttgart, Germany

    Albrecht Schmidt

  5. VISUS, University of Stuttgart, Stuttgart, Germany

    Daniel Weiskopf

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Nguyen, TH.D., El-Nasr, M.S., Isaacowitz, D.M. (2017). Interactive Visualization for Understanding of Attention Patterns. In: Burch, M., Chuang, L., Fisher, B., Schmidt, A., Weiskopf, D. (eds) Eye Tracking and Visualization. ETVIS 2015. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-47024-5_2

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