A Web-Based Eye Tracking Data Visualization Tool

Hristo Bakardzhiev; Marloes van der Burgt; Eduardo Martins; Bart van den Dool; Chyara Jansen; David van Scheppingen; Günter Wallner; Michael Burch

doi:10.1007/978-3-030-68796-0_29

A Web-Based Eye Tracking Data Visualization Tool

Hristo Bakardzhiev, Marloes van der Burgt, Eduardo Martins, Bart van den Dool, Chyara Jansen, David van Scheppingen, Günter Wallner, Michael Burch

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

5 Citations (Scopus)

Abstract

Visualizing eye tracking data can provide insights in many research fields. However, visualizing such data efficiently and cost-effectively is challenging without well-designed tools. Easily accessible web-based approaches equipped with intuitive and interactive visualizations offer to be a promising solution. Many of such tools already exist, however, they mostly use one specific visualization technique. In this paper, we describe a web application which uses a combination of different visualization methods for eye tracking data. The visualization techniques are interactively linked to provide several perspectives on the eye tracking data. We conclude the paper by discussing challenges, limitations, and future work.

Original language	English
Title of host publication	Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings
Editors	Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani
Place of Publication	Cham
Publisher	Springer
Pages	405-419
Number of pages	15
ISBN (Print)	978-3-030-68795-3
DOIs	https://doi.org/10.1007/978-3-030-68796-0_29
Publication status	Published - 2021
Event	25th International Conference on Pattern Recognition Workshops, ICPR 2020 - Milan, Italy Duration: 10 Jan 2021 → 15 Jan 2021 Conference number: 25 https://www.micc.unifi.it/icpr2020/

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12663 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	25th International Conference on Pattern Recognition Workshops, ICPR 2020
Abbreviated title	ICPR 2020
Country/Territory	Italy
City	Milan
Period	10/01/21 → 15/01/21
Internet address	https://www.micc.unifi.it/icpr2020/

Keywords

Eye tracking
Information visualization
Multiple linked views

Access to Document

10.1007/978-3-030-68796-0_29

Cite this

Bakardzhiev, H., van der Burgt, M., Martins, E., van den Dool, B., Jansen, C., van Scheppingen, D., Wallner, G., & Burch, M. (2021). A Web-Based Eye Tracking Data Visualization Tool. In A. Del Bimbo, R. Cucchiara, S. Sclaroff, G. M. Farinella, T. Mei, M. Bertini, H. J. Escalante, & R. Vezzani (Eds.), Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings (pp. 405-419). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12663 LNCS). Springer. https://doi.org/10.1007/978-3-030-68796-0_29

Bakardzhiev, Hristo ; van der Burgt, Marloes ; Martins, Eduardo et al. / A Web-Based Eye Tracking Data Visualization Tool. Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings. editor / Alberto Del Bimbo ; Rita Cucchiara ; Stan Sclaroff ; Giovanni Maria Farinella ; Tao Mei ; Marco Bertini ; Hugo Jair Escalante ; Roberto Vezzani. Cham : Springer, 2021. pp. 405-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Visualizing eye tracking data can provide insights in many research fields. However, visualizing such data efficiently and cost-effectively is challenging without well-designed tools. Easily accessible web-based approaches equipped with intuitive and interactive visualizations offer to be a promising solution. Many of such tools already exist, however, they mostly use one specific visualization technique. In this paper, we describe a web application which uses a combination of different visualization methods for eye tracking data. The visualization techniques are interactively linked to provide several perspectives on the eye tracking data. We conclude the paper by discussing challenges, limitations, and future work.",

keywords = "Eye tracking, Information visualization, Multiple linked views",

author = "Hristo Bakardzhiev and {van der Burgt}, Marloes and Eduardo Martins and {van den Dool}, Bart and Chyara Jansen and {van Scheppingen}, David and G{\"u}nter Wallner and Michael Burch",

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booktitle = "Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings",

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Bakardzhiev, H, van der Burgt, M, Martins, E, van den Dool, B, Jansen, C, van Scheppingen, D, Wallner, G & Burch, M 2021, A Web-Based Eye Tracking Data Visualization Tool. in A Del Bimbo, R Cucchiara, S Sclaroff, GM Farinella, T Mei, M Bertini, HJ Escalante & R Vezzani (eds), Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12663 LNCS, Springer, Cham, pp. 405-419, 25th International Conference on Pattern Recognition Workshops, ICPR 2020, Milan, Italy, 10/01/21. https://doi.org/10.1007/978-3-030-68796-0_29

A Web-Based Eye Tracking Data Visualization Tool. / Bakardzhiev, Hristo; van der Burgt, Marloes; Martins, Eduardo et al.
Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings. ed. / Alberto Del Bimbo; Rita Cucchiara; Stan Sclaroff; Giovanni Maria Farinella; Tao Mei; Marco Bertini; Hugo Jair Escalante; Roberto Vezzani. Cham: Springer, 2021. p. 405-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12663 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - A Web-Based Eye Tracking Data Visualization Tool

AU - Bakardzhiev, Hristo

AU - van der Burgt, Marloes

AU - Martins, Eduardo

AU - van den Dool, Bart

AU - Jansen, Chyara

AU - van Scheppingen, David

AU - Wallner, Günter

AU - Burch, Michael

N1 - Conference code: 25

PY - 2021

Y1 - 2021

N2 - Visualizing eye tracking data can provide insights in many research fields. However, visualizing such data efficiently and cost-effectively is challenging without well-designed tools. Easily accessible web-based approaches equipped with intuitive and interactive visualizations offer to be a promising solution. Many of such tools already exist, however, they mostly use one specific visualization technique. In this paper, we describe a web application which uses a combination of different visualization methods for eye tracking data. The visualization techniques are interactively linked to provide several perspectives on the eye tracking data. We conclude the paper by discussing challenges, limitations, and future work.

AB - Visualizing eye tracking data can provide insights in many research fields. However, visualizing such data efficiently and cost-effectively is challenging without well-designed tools. Easily accessible web-based approaches equipped with intuitive and interactive visualizations offer to be a promising solution. Many of such tools already exist, however, they mostly use one specific visualization technique. In this paper, we describe a web application which uses a combination of different visualization methods for eye tracking data. The visualization techniques are interactively linked to provide several perspectives on the eye tracking data. We conclude the paper by discussing challenges, limitations, and future work.

KW - Eye tracking

KW - Information visualization

KW - Multiple linked views

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 419

BT - Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings

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A2 - Cucchiara, Rita

A2 - Sclaroff, Stan

A2 - Farinella, Giovanni Maria

A2 - Mei, Tao

A2 - Bertini, Marco

A2 - Escalante, Hugo Jair

A2 - Vezzani, Roberto

PB - Springer

CY - Cham

T2 - 25th International Conference on Pattern Recognition Workshops, ICPR 2020

Y2 - 10 January 2021 through 15 January 2021

ER -

Bakardzhiev H, van der Burgt M, Martins E, van den Dool B, Jansen C, van Scheppingen D et al. A Web-Based Eye Tracking Data Visualization Tool. In Del Bimbo A, Cucchiara R, Sclaroff S, Farinella GM, Mei T, Bertini M, Escalante HJ, Vezzani R, editors, Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings. Cham: Springer. 2021. p. 405-419. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-68796-0_29

A Web-Based Eye Tracking Data Visualization Tool

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Keywords

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