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

2 Citaten (Scopus)

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
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 → 15 jan. 2021 Congresnummer: 25 https://www.micc.unifi.it/icpr2020/

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
Verkorte titel	ICPR 2020
Land/Regio	Italië
Stad	Milan
Periode	10/01/21 → 15/01/21
Internet adres	https://www.micc.unifi.it/icpr2020/

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. 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. redacteur / Alberto Del Bimbo ; Rita Cucchiara ; Stan Sclaroff ; Giovanni Maria Farinella ; Tao Mei ; Marco Bertini ; Hugo Jair Escalante ; Roberto Vezzani. Springer, 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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title = "A Web-Based Eye Tracking Data Visualization Tool",

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",

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, ICPR 2020 ; Conference date: 10-01-2021 Through 15-01-2021",

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doi = "10.1007/978-3-030-68796-0_29",

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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, 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 et al.

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, 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

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

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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.

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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

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, redacteurs, Pattern Recognition. ICPR International Workshops and Challenges, 2021, Proceedings. Springer. 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

A Web-Based Eye Tracking Data Visualization Tool

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