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

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

Samenvatting

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.

Originele taal-2	Engels
Titel	Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings
Redacteuren	Alberto Del Bimbo, Rita Cucchiara, Stan Sclaroff, Giovanni Maria Farinella, Tao Mei, Marco Bertini, Hugo Jair Escalante, Roberto Vezzani
Uitgeverij	Springer Science and Business Media Deutschland GmbH
Pagina's	405-419
Aantal pagina's	15
ISBN van geprinte versie	9783030687953
DOI's	https://doi.org/10.1007/978-3-030-68796-0_29
Status	Gepubliceerd - 2021
Evenement	25th International Conference on Pattern Recognition Workshops, ICPR 2020 - Milan, Italië Duur: 10 jan 2021 → 11 jan 2021

Publicatie series

Naam	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12663 LNCS
ISSN van geprinte versie	0302-9743
ISSN van elektronische versie	1611-3349

Congres

Congres	25th International Conference on Pattern Recognition Workshops, ICPR 2020
Land	Italië
Stad	Milan
Periode	10/01/21 → 11/01/21

Bibliografische nota

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.

Toegang tot document

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

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Citeer dit

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 (editors), Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings (blz. 405-419). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12663 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-68796-0_29

Bakardzhiev, Hristo ; van der Burgt, Marloes ; Martins, Eduardo ; van den Dool, Bart ; Jansen, Chyara ; van Scheppingen, David ; Wallner, Günter ; Burch, Michael. / A Web-Based Eye Tracking Data Visualization Tool. Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings. redacteur / Alberto Del Bimbo ; Rita Cucchiara ; Stan Sclaroff ; Giovanni Maria Farinella ; Tao Mei ; Marco Bertini ; Hugo Jair Escalante ; Roberto Vezzani. Springer Science and Business Media Deutschland GmbH, 2021. blz. 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.",

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note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 25th International Conference on Pattern Recognition Workshops, ICPR 2020 ; Conference date: 10-01-2021 Through 11-01-2021",

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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 (redactie), 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 Science and Business Media Deutschland GmbH, blz. 405-419, 25th International Conference on Pattern Recognition Workshops, ICPR 2020, Milan, Italië, 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; van den Dool, Bart; Jansen, Chyara; van Scheppingen, David; Wallner, Günter ; Burch, Michael.

Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings. redactie / Alberto Del Bimbo; Rita Cucchiara; Stan Sclaroff; Giovanni Maria Farinella; Tao Mei; Marco Bertini; Hugo Jair Escalante; Roberto Vezzani. Springer Science and Business Media Deutschland GmbH, 2021. blz. 405-419 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12663 LNCS).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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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.

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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, redacteurs, Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. blz. 405-419. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-68796-0_29