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research-article

Fixation-image charts

Authors:

Marcel Hlawatsch,

Daniel WeiskopfAuthors Info & Claims

ETRA '16: Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications

Pages 11 - 18

https://doi.org/10.1145/2857491.2857507

Published: 14 March 2016 Publication History

Abstract

We facilitate the comparative visual analysis of eye tracking data from multiple participants with a visualization that represents the temporal changes of viewing behavior. Common approaches to visually analyze eye tracking data either occlude or ignore the underlying visual stimulus, impairing the interpretation of displayed measures. We introduce fixation-image charts: a new technique to display the temporal changes of fixations in the context of the stimulus without visual overlap between participants. Fixation durations, the distance and direction of saccades between consecutive fixations, as well as the stimulus context can be interpreted in one visual representation. Our technique is not limited to static stimuli, but can be applied to dynamic stimuli as well. Using fixation metrics and the visual similarity of stimulus regions, we complement our visualization technique with an interactive filter concept that allows for the identification of interesting fixation sequences without the time-consuming annotation of areas of interest. We demonstrate how our technique can be applied to different types of stimuli to perform a range of analysis tasks. Furthermore, we discuss advantages and shortcomings derived from a preliminary user study.

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References

[1]

Andrienko, G. L., Andrienko, N. V., 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

[2]

Bhattacharyya, A. 1946. On a measure of divergence between two multinomial populations. Sankhyā: The Indian Journal of Statistics 7, 401--406.

[3]

Blascheck, T., Kurzhals, K., Raschke, M., Burch, M., Weiskopf, D., and Ertl, T. 2014. State-of-the-Art of Visualization for Eye Tracking Data. In EuroVis - STARs, 63--82.

[4]

Blascheck, T., John, M., Kurzhals, K., Koch, S., and Ertl, T. 2016. VA²: A visual analytics approach for evaluating visual analytics applications. IEEE Transactions on Visualization and Computer Graphics 22, 1, 61--70.

Digital Library

[5]

Burch, M., Kull, A., and Weiskopf, D. 2013. AOI rivers for visualizing dynamic eye gaze frequencies. Computer Graphics Forum 32, 3, 281--290.

Digital Library

[6]

Campbell, C. S., and Maglio, P. P. 2001. A robust algorithm for reading detection. In Proceedings of the Workshop on Perceptive User Interfaces, 1--7.

Digital Library

[7]

Duchowski, A., and McCormick, B. H. 1998. Gaze-contingent video resolution degradation. In Proceedings of SPIE, vol. 3299, 318--329.

Digital Library

[8]

Duchowski, A. T., Driver, J., Jolaoso, S., Tan, W., Ramey, B. N., and Robbins, A. 2010. Scanpath comparison revisited. In Proceedings of the Symposium on Eye Tracking Research & Applications, 219--226.

Digital Library

[9]

Duchowski, A. T., Price, M. M., Meyer, M., and Orero, P. 2012. Aggregate gaze visualization with real-time heatmaps. In Proceedings of the Symposium on Eye Tracking Research & Applications, 13--20.

Digital Library

[10]

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

[11]

Goldberg, J. H., and Helfman, J. I. 2010. Visual scanpath representation. In Proceedings of the Symposium on Eye Tracking Research & Applications, 203--210.

Digital Library

[12]

Hlawatsch, M., Burch, M., and Weiskopf, D. 2015. Visual analysis of eye movements by hierarchical filter wheels. In Proceedings of the 19th International Conference on Information Visualisation IV, 107--113.

Digital Library

[13]

Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., and Van de Weijer, J. 2011. Eye Tracking: A Comprehensive Guide to Methods and Measures. Oxford University Press.

[14]

Hurter, C., Ersoy, O., Fabrikant, S., Klein, T., and Telea, A. 2014. Bundled visualization of dynamic graph and trail data. IEEE Transactions on Visualization and Computer Graphics 20, 8, 1141--1157.

Digital Library

[15]

Kurzhals, K., Bopp, C. F., Bässler, J., Ebinger, F., and Weiskopf, D. 2014. Benchmark data for evaluating visualization and analysis techniques for eye tracking for video stimuli. In Proceedings of the Workshop Beyond Time and Errors: Novel Evaluation Methods for Visualization, 54--60.

Digital Library

[16]

Kurzhals, K., Heimerl, F., and Weiskopf, D. 2014. ISeeCube: Visual analysis of gaze data for video. In Proceedings of the Symposium on Eye Tracking Research & Applications, 43--50.

Digital Library

[17]

Kurzhals, K., Hlawatsch, M., Heimerl, F., Burch, M., and Weiskopf, D. 2016. Gaze stripes: Image-based visualization of eye tracking data. IEEE Transactions on Visualization and Computer Graphics 22, 1, 1005--1014.

Digital Library

[18]

Lowe, D. G. 1999. Object recognition from local scale-invariant features. In Proceedings of IEEE International Conference on Computer Vision, vol. 2, 1150--1157.

Digital Library

[19]

Nyström, M., and Holmqvist, K. 2010. Effect of compressed offline foveated video on viewing behavior and subjective quality. ACM Transactions on Multimedia Computing, Communications, and Applications 6, 1, 4:1--4:14.

Digital Library

[20]

Pontillo, D. F., Kinsman, T. B., and Pelz, J. B. 2010. SemantiCode: Using content similarity and database-driven matching to code wearable eyetracker gaze data. In Proceedings of the Symposium on Eye-Tracking Research & Applications, 267--270.

Digital Library

[21]

Rajashekar, U., Cormack, L. K., and Bovik, A. C. 2004. Point-of-gaze analysis reveals visual search strategies. In Proceedings of SPIE, vol. 5292, 296--306.

[22]

Rayner, K. 1998. Eye movements in reading and information processing: 20 years of research. Psychological Bulletin 124, 3, 372--422.

[23]

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.

[24]

West, J., Haake, A., Rozanski, E. P., and Karn, K. 2006. eyePatterns: software for identifying patterns and similarities across fixation sequences. In Proceedings of the 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
Koch MWeiskopf DKurzhals K(2022)A Spiral into the MindProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/35307955:2(1-16)Online publication date: 17-May-2022
https://dl.acm.org/doi/10.1145/3530795
Tupikovskaja-Omovie Z(2022)Enhancing User Experience in Fashion m-Retail: Mapping Shopping User Journey Using Google Analytics, Eye Tracking Technology and Retrospective Think Aloud InterviewFashion Practice10.1080/17569370.2022.212946614:3(352-375)Online publication date: 11-Nov-2022
https://doi.org/10.1080/17569370.2022.2129466
Show More Cited By

Index Terms

Fixation-image charts
1. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Visual analytics
    2. Visualization systems and tools

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cover image ACM Conferences

ETRA '16: Proceedings of the Ninth Biennial ACM Symposium on Eye Tracking Research & Applications

March 2016

378 pages

ISBN:9781450341257

DOI:10.1145/2857491

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

Copyright © 2016 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 the author(s) 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].

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Published: 14 March 2016

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March 14 - 17, 2016

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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
Koch MWeiskopf DKurzhals K(2022)A Spiral into the MindProceedings of the ACM on Computer Graphics and Interactive Techniques10.1145/35307955:2(1-16)Online publication date: 17-May-2022
https://dl.acm.org/doi/10.1145/3530795
Tupikovskaja-Omovie Z(2022)Enhancing User Experience in Fashion m-Retail: Mapping Shopping User Journey Using Google Analytics, Eye Tracking Technology and Retrospective Think Aloud InterviewFashion Practice10.1080/17569370.2022.212946614:3(352-375)Online publication date: 11-Nov-2022
https://doi.org/10.1080/17569370.2022.2129466
Geisler DWeber DCastner NKasneci E(2020)Exploiting the GBVS for Saliency aware Gaze HeatmapsACM Symposium on Eye Tracking Research and Applications10.1145/3379156.3391367(1-5)Online publication date: 2-Jun-2020
https://dl.acm.org/doi/10.1145/3379156.3391367
Burch MVeneri ASun B(2020)Exploring eye movement data with image-based clusteringJournal of Visualization10.1007/s12650-020-00656-923:4(677-694)Online publication date: 5-Jul-2020
https://dl.acm.org/doi/10.1007/s12650-020-00656-9
Burch MKumar ATimmermans NKrejtz KSharif B(2019)An interactive web-based visual analytics tool for detecting strategic eye movement patternsProceedings of the 11th ACM Symposium on Eye Tracking Research & Applications10.1145/3317960.3321615(1-5)Online publication date: 25-Jun-2019
https://dl.acm.org/doi/10.1145/3317960.3321615
Kumar ATimmermans NBurch MMueller KKrejtz KSharif B(2019)Clustered eye movement similarity matricesProceedings of the 11th ACM Symposium on Eye Tracking Research & Applications10.1145/3317958.3319811(1-9)Online publication date: 25-Jun-2019
https://dl.acm.org/doi/10.1145/3317958.3319811
Kumar ABurch MMueller KKrejtz KSharif B(2019)Visually comparing eye movements over space and timeProceedings of the 11th ACM Symposium on Eye Tracking Research & Applications10.1145/3317958.3319810(1-9)Online publication date: 25-Jun-2019
https://dl.acm.org/doi/10.1145/3317958.3319810
Menges RTamimi HKumar CWalber TSchaefer CStaab SSharif BKrejtz K(2018)Enhanced representation of web pages for usability analysis with eye trackingProceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications10.1145/3204493.3214308(1-9)Online publication date: 14-Jun-2018
https://dl.acm.org/doi/10.1145/3204493.3214308
Koch MKurzhals KWeiskopf DSharif BKrejtz K(2018)Image-based scanpath comparison with slit-scan visualizationProceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications10.1145/3204493.3204581(1-5)Online publication date: 14-Jun-2018
https://dl.acm.org/doi/10.1145/3204493.3204581
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