research-article

ISeeCube: visual analysis of gaze data for video

Authors:

Florian Heimerl,

Daniel WeiskopfAuthors Info & Claims

ETRA '14: Proceedings of the Symposium on Eye Tracking Research and Applications

Pages 351 - 358

https://doi.org/10.1145/2578153.2628812

Published: 26 March 2014 Publication History

Abstract

We introduce a new design for the visual analysis of eye tracking data recorded from dynamic stimuli such as video. ISeeCube includes multiple coordinated views to support different aspects of various analysis tasks. It combines methods for the spatiotemporal analysis of gaze data recorded from unlabeled videos as well as the possibility to annotate and investigate dynamic Areas of Interest (AOIs). A static overview of the complete data set is provided by a space-time cube visualization that shows gaze points with density-based color mapping and spatiotemporal clustering of the data. A timeline visualization supports the analysis of dynamic AOIs and the viewers' attention on them. AOI-based scanpaths of different viewers can be clustered by their Levenshtein distance, an attention map, or the transitions between AOIs. With the provided visual analytics techniques, the exploration of eye tracking data recorded from several viewers is supported for a wide range of analysis tasks.

Supplementary Material

MP4 File (p351-kurzhals.mp4)

Download
49.11 MB

References

[1]

André, P., Wilson, M. L., Russell, A., Smith, D. A., Owens, A., and schraefel, m. 2007. Continuum: designing timelines for hierarchies, relationships and scale. In Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology, 101--110.

Digital Library

[2]

Andrienko, G., Andrienko, N., Burch, M., and Weiskopf, D. 2012. Visual analytics methodology for eye movement studies. IEEE Transactions on Visualization and Computer Graphics 18, 12, 2889--2898.

Digital Library

[3]

Burch, M., Konevtsova, N., Heinrich, J., Höferlin, M., and Weiskopf, D. 2011. Evaluation of traditional, orthogonal, and radial tree diagrams by an eye tracking study. IEEE Transactions on Visualization and Computer Graphics 17, 12, 2440--2448.

Digital Library

[4]

Doermann, D., and Mihalcik, D. 2000. Tools and techniques for video performance evaluation. In Proceedings of the 15th International Conference on Pattern Recognition, 167--170.

Digital Library

[5]

Duchowski, A., and McCormick, B. 1998. Gaze-contingent video resolution degradation. In Proceedings of Photonics West'98 Electronic Imaging, 318--329.

[6]

Duchowski, A. T. 2002. A breadth-first survey of eye-tracking applications. Behavior Research Methods, Instruments, & Computers 34, 4, 455--470.

[7]

Goldstein, R., Woods, R., and Peli, E. 2007. Where people look when watching movies: Do all viewers look at the same place? Computers in Biology and Medicine 37, 7, 957--964.

Digital Library

[8]

Harrower, M., and Brewer, C. 2003. ColorBrewer.org: an online tool for selecting colour schemes for maps. The Cartographic Journal 40, 1, 27--37.

[9]

Hastie, T., Tibshirani, R., and Friedman, J. 2009. The Elements of Statistical learning: data mining, inference and prediction, 2 ed. Springer.

[10]

Holmqvist, K., Nystrm, M., Andersson, R., Dewhurst, R., Halszka, J., and van de Weijer, J. 2011. Eye Tracking: A Comprehensive Guide to Methods and Measures. Oxford University Press.

[11]

Kurzhals, K., and Weiskopf, D. 2013. Space-time visual analytics of eye-tracking data for dynamic stimuli. IEEE Transactions on Visualization and Computer Graphics 19, 12, 2129--2138.

Digital Library

[12]

Lessing, S., and Linge, L. 2002. IICap: A new environment for eye tracking data analysis. Master's thesis. University of Lund, Sweden.

[13]

Levenshtein, V. 1966. Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics-Doklady 10, 8, 707--710.

[14]

Li, X., Çöltekin, A., and Kraak, M.-J. 2010. Visual exploration of eye movement data using the space-time-cube. In Proceedings of the 6th International Conference on Geographic Information Science, 295--309.

Digital Library

[15]

Marchant, P., Raybould, D., Renshaw, T., and Stevens, R. 2009. Are you seeing what I'm seeing? An eye-tracking evaluation of dynamic scenes. Digital Creativity 20, 3, 153--163.

[16]

Mital, P., Smith, T., Hill, R., and Henderson, J. 2011. Clustering of gaze during dynamic scene viewing is predicted by motion. Cognitive Computation 3, 1, 5--24.

[17]

Poole, A., and Ball, L. J. 2006. Eye tracking in HCI and usability research. In Encyclopedia of Human Computer Interaction, C. Ghaoui, Ed. Idea Group Reference, 211--219.

[18]

Richardson, D. C., and Dale, R. 2005. Looking to understand: The coupling between speakers' and listeners' eye movements and its relationship to discourse comprehension. Cognitive Science 29, 6, 1045--1060.

[19]

Ristovski, G., Hunter, M., Olk, B., and Linsen, L. 2013. EyeC: Coordinated views for interactive visual exploration of eye-tracking data. In Proceedings of the 17th International Conference on Information Visualisation, 239--248.

Digital Library

[20]

Santella, A., and DeCarlo, D. 2004. Robust clustering of eye movement recordings for quantification of visual interest. In Proceedings of the 2004 Symposium on Eye Tracking Research & Applications, 27--34.

Digital Library

[21]

Smith, T., and Henderson, J. 2008. Attentional synchrony in static and dynamic scenes. Journal of Vision 8, 6, 773--773.

[22]

Stellmach, S., Nacke, L., and Dachselt, R. 2010. Advanced gaze visualizations for three-dimensional virtual environments. In Proceedings of the 2010 Symposium on Eye Tracking Research & Applications, 109--112.

Digital Library

[23]

Thomas, J. J., and Cook, K. A. 2005. Illuminating the Path: The Research and Development Agenda for Visual Analytics. IEEE Computer Society Press.

[24]

Tien, G., Atkins, M. S., and Zheng, B. 2012. Measuring gaze overlap on videos between multiple observers. In Proceedings of the 2012 Symposium on Eye Tracking Research & Applications, 309--312.

Digital Library

[25]

Tsang, H. Y., Tory, M., and Swindells, C. 2010. eSeeTrack-Visualizing sequential fixation patterns. IEEE Transactions on Visualization and Computer Graphics 16, 6, 953--962.

Digital Library

[26]

Weibel, N., Fouse, A., Emmenegger, C., Kimmich, S., and Hutchins, E. 2012. Let's look at the cockpit: exploring mobile eye-tracking for observational research on the flight deck. In Proceedings of the 2012 Symposium on Eye Tracking Research & Applications, 107--114.

Digital Library

[27]

West, J. M., Haake, A. R., Rozanski, E. P., and Karn, K. S. 2006. eyePatterns: software for identifying patterns and similarities across fixation sequences. In Proceedings of the 2006 Symposium on Eye Tracking Research & Applications, 149--154.

Digital Library

Cited By

Koch MPathmanathan NWeiskopf DKurzhals K(2024)How Deep Is Your Gaze? Leveraging Distance in Image-Based Gaze AnalysisProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3653349(1-7)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3653349
Chen KNgo QKurzhals KMarriott KDwyer TSedlmair MWeiskopf D(2023)Reading Strategies for Graph Visualizations that Wrap Around in Torus TopologyProceedings of the 2023 Symposium on Eye Tracking Research and Applications10.1145/3588015.3589841(1-7)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.1145/3588015.3589841
Pathmanathan NÖney SBecher MSedlmair MWeiskopf DKurzhals K(2023)Been There, Seen That: Visualization of Movement and 3D Eye Tracking Data from Real‐World EnvironmentsComputer Graphics Forum10.1111/cgf.1483842:3(385-396)Online publication date: 27-Jun-2023
https://doi.org/10.1111/cgf.14838
Show More Cited By

Recommendations

ISeeCube: visual analysis of gaze data for video
ETRA '14: Proceedings of the Symposium on Eye Tracking Research and Applications

We introduce a new design for the visual analysis of eye tracking data recorded from dynamic stimuli such as video. ISeeCube includes multiple coordinated views to support different aspects of various analysis tasks. It combines methods for the ...
Space-Time Visual Analytics of Eye-Tracking Data for Dynamic Stimuli

We introduce a visual analytics method to analyze eye movement data recorded for dynamic stimuli such as video or animated graphics. The focus lies on the analysis of data of several viewers to identify trends in the general viewing behavior, including ...
An interactive web-based visual analytics tool for detecting strategic eye movement patterns
ETRA '19: Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications

In this paper we describe an interactive and web-based visual analytics tool combining linked visualization techniques and algorithmic approaches for exploring the hierarchical visual scanning behavior of a group of people when solving tasks in a static ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

ETRA '14: Proceedings of the Symposium on Eye Tracking Research and Applications

March 2014

394 pages

ISBN:9781450327510

DOI:10.1145/2578153

Conference Chairs:
Pernilla Qvarfordt
FX Palo Alto Laboratory
,
Dan Witzner Hansen
IT University, Denmark

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 March 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Deutsche Forschungsgemeinschaft

Conference

ETRA '14

Sponsor:

ETRA '14: Eye Tracking Research and Applications

March 26 - 28, 2014

Florida, Safety Harbor

Acceptance Rates

Overall Acceptance Rate 69 of 137 submissions, 50%

Upcoming Conference

ETRA '25

Sponsor:
sigchi
sigchi

2025 Symposium on Eye Tracking Research and Applications

May 26 - 29, 2025

Tokyo , Japan

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

10
Total Citations
View Citations
76
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 01 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Koch MPathmanathan NWeiskopf DKurzhals K(2024)How Deep Is Your Gaze? Leveraging Distance in Image-Based Gaze AnalysisProceedings of the 2024 Symposium on Eye Tracking Research and Applications10.1145/3649902.3653349(1-7)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3649902.3653349
Chen KNgo QKurzhals KMarriott KDwyer TSedlmair MWeiskopf D(2023)Reading Strategies for Graph Visualizations that Wrap Around in Torus TopologyProceedings of the 2023 Symposium on Eye Tracking Research and Applications10.1145/3588015.3589841(1-7)Online publication date: 30-May-2023
https://dl.acm.org/doi/10.1145/3588015.3589841
Pathmanathan NÖney SBecher MSedlmair MWeiskopf DKurzhals K(2023)Been There, Seen That: Visualization of Movement and 3D Eye Tracking Data from Real‐World EnvironmentsComputer Graphics Forum10.1111/cgf.1483842:3(385-396)Online publication date: 27-Jun-2023
https://doi.org/10.1111/cgf.14838
Zhang LLiu XChen QZhou YXu T(2022)EyeBox: A Toolbox based on Python3 for Eye Movement AnalysisProcedia Computer Science10.1016/j.procs.2022.03.024201(166-173)Online publication date: 2022
https://doi.org/10.1016/j.procs.2022.03.024
Quadar NChehri AGeon G(2020)Visual Analytics Methods for Eye Tracking DataHuman Centred Intelligent Systems10.1007/978-981-15-5784-2_1(3-12)Online publication date: 30-May-2020
https://doi.org/10.1007/978-981-15-5784-2_1
Weiskopf D(2020)Vis4Vis: Visualization for (Empirical) Visualization ResearchFoundations of Data Visualization10.1007/978-3-030-34444-3_10(209-224)Online publication date: 12-Aug-2020
https://doi.org/10.1007/978-3-030-34444-3_10
Jianu RAlam S(2018)A Data Model and Task Space for Data of Interest (DOI) Eye-Tracking AnalysesIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2017.266549824:3(1232-1245)Online publication date: 1-Mar-2018
https://doi.org/10.1109/TVCG.2017.2665498
Alam SJianu R(2017)Analyzing Eye-Tracking Information in Visualization and Data SpaceIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2016.253534023:5(1492-1505)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1109/TVCG.2016.2535340
Krueger RHeimerl FHan QKurzhals KKoch SErtl T(2015)Visual Analysis of Visitor Behavior for Indoor Event ManagementProceedings of the 2015 48th Hawaii International Conference on System Sciences10.1109/HICSS.2015.139(1148-1157)Online publication date: 5-Jan-2015
https://dl.acm.org/doi/10.1109/HICSS.2015.139
Kurzhals KBopp CBässler JEbinger FWeiskopf D(2014)Benchmark data for evaluating visualization and analysis techniques for eye tracking for video stimuliProceedings of the Fifth Workshop on Beyond Time and Errors: Novel Evaluation Methods for Visualization10.1145/2669557.2669558(54-60)Online publication date: 10-Nov-2014
https://dl.acm.org/doi/10.1145/2669557.2669558

View Options

View options

Figures

Tables

Media

View Table of Conten