Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1145/2578153.2578206acmconferencesArticle/Chapter ViewAbstractPublication PagesetraConference Proceedingsconference-collections
research-article

SubsMatch: scanpath similarity in dynamic scenes based on subsequence frequencies

Published: 26 March 2014 Publication History

Abstract

The analysis of visual scanpaths, i.e., series of fixations and saccades, in complex dynamic scenarios is highly challenging and usually performed manually. We propose SubsMatch, a scanpath comparison algorithm for dynamic, interactive scenarios based on the frequency of repeated gaze patterns. Instead of measuring the gaze duration towards a semantic target object (which would be hard to label in dynamic scenes), we examine the frequency of attention shifts and exploratory eye movements. SubsMatch was evaluated on highly dynamic data from a driving experiment to identify differences between scanpaths of subjects who failed a driving test and subjects who passed.

References

[1]
Brandt, S., and Stark, L. 1997. Spontaneous eye movements during visual imagery reflect the content of the visual scene. Journal of Cognitive Neuroscience.
[2]
Caldara, R., and Miellet, S. 2011. iMap: a novel method for statistical fixation mapping of eye movement data. Behavior research methods 43, 3 (Sept.), 864--78.
[3]
Cristino, F., Mathôt, S., Theeuwes, J., and Gilchrist, I. D. 2010. ScanMatch: a novel method for comparing fixation sequences. Behavior research methods 42, 3 (Aug.), 692--700.
[4]
Dewhurst, R., Nyström, M., Jarodzka, H., Foulsham, T., Johansson, R., and Holmqvist, K. 2012. It depends on how you look at it: scanpath comparison in multiple dimensions with MultiMatch, a vector-based approach. Behavior research methods 44, 4 (Dec.), 1079--100.
[5]
Duchowski, A. T., Driver, J., Jolaoso, S., Tan, W., Ramey, B. N., and Robbins, A. 2010. Scanpath comparison revisited. Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications, 219.
[6]
Heminghous, J., and Duchowski, A. T. 2006. iComp: a tool for scanpath visualization and comparison. In ACM SIGGRAPH 2006 Research posters, ACM, 186.
[7]
Jarodzka, H., Holmqvist, K., and Nyström, M. 2010. A vector-based, multidimensional scanpath similarity measure. In Proceedings of the 2010 Symposium on Eye-Tracking Research & Applications, ACM, 211--218.
[8]
Kasneci, E. 2013. Towards the Automated Recognition of Assistance Need for Drivers with Impaired Visual Field. PhD thesis, University of Tübingen, Wilhelmstr. 32, 72074 Tübingen.
[9]
Lin, J., Keogh, E., Wei, L., and Lonardi, S. 2007. Experiencing SAX: a novel symbolic representation of time series. Data Mining and Knowledge Discovery 15, 2 (Apr.), 107--144.
[10]
Marmitt, G., and Duchowski, A. T. 2002. Modeling visual attention in VR: Measuring the accuracy of predicted scanpaths. PhD thesis, Clemson University.
[11]
Mast, M., and Burmester, M. 2011. Exposing repetitive scanning in eye movement sequences with t-pattern detection. Proceedings IADIS, 137--145.
[12]
Munn, S. M., Stefano, L., and Pelz, J. B. 2008. Fixation-identification in dynamic scenes: Comparing an automated algorithm to manual coding. In Proceedings of the 5th symposium on Applied perception in graphics and visualization, ACM, 33--42.
[13]
Noton, D., and Stark, L. 1971. Scanpaths in saccadic eye movements while viewing and recognizing patterns. Vision research 11, 9 (Sept.), 929--42.
[14]
Ponsoda, V., Scott, D., and Findlay, J. 1995. A probability vector and transition matrix analysis of eye movements during visual search. Acta Psychologica 88, 167--185.
[15]
Privitera, C., and Stark, L. 2000. Algorithms for defining visual regions-of-interest: comparison with eye fixations. Transactions on Pattern Analysis and Machine Intelligence 22, 9.
[16]
Santella, A., and DeCarlo, D. 2004. Robust clustering of eye movement recordings for quantification of visual interest. Proceedings of the Eye tracking research & applications symposium on Eye tracking research & applications, 27--34.
[17]
Tafaj, E., Kübler, T., Peter, J., Schiefer, U., Bogdan, M., and Rosenstiel, W. 2011. Vishnoo - an open-source software for vision research. In Proceedings of the 24th IEEE International Symposium on Computer-Based Medical Systems, IEEE, CBMS' 11, 1--6.
[18]
Tafaj, E., Kasneci, G., Rosenstiel, W., and Bogdan, M. 2012. Bayesian online clustering of eye movement data. In Proceedings of the Symposium on Eye Tracking Research and Applications, ACM, New York, NY, USA, ETRA '12, 285--288.
[19]
Tafaj, E., Kübler, T., Kasneci, G., Rosenstiel, W., and Bogdan, M. 2013. Online classification of eye tracking data for automated analysis of traffic hazard perception. In Artificial Neural Networks and Machine Learning ICANN 2013, vol. 8131. Springer Berlin Heidelberg, 442--450.
[20]
Tatler, B. W., Wade, N. J., Kwan, H., Findlay, J. M., and Velichkovsky, B. M. 2010. Yarbus, eye movements, and vision. i-Perception 1, 1 (Jan.), 7--27.

Cited By

View all
  • (2023)Predicting choice behaviour in economic games using gaze data encoded as scanpath imagesScientific Reports10.1038/s41598-023-31536-513:1Online publication date: 23-Mar-2023
  • (2022)RETRACTED ARTICLE: Eye tracking: empirical foundations for a minimal reporting guidelineBehavior Research Methods10.3758/s13428-021-01762-855:1(364-416)Online publication date: 6-Apr-2022
  • (2022)The relationship between visual confirmation bias, belief consistency, and belief polarizationComprehensive Results in Social Psychology10.1080/23743603.2022.20262146:1-3(1-38)Online publication date: 10-May-2022
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

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
Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 March 2014

Check for updates

Author Tags

  1. driving
  2. dynamic scene
  3. scanpath comparison

Qualifiers

  • Research-article

Conference

ETRA '14
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

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)13
  • Downloads (Last 6 weeks)3
Reflects downloads up to 29 Sep 2024

Other Metrics

Citations

Cited By

View all
  • (2023)Predicting choice behaviour in economic games using gaze data encoded as scanpath imagesScientific Reports10.1038/s41598-023-31536-513:1Online publication date: 23-Mar-2023
  • (2022)RETRACTED ARTICLE: Eye tracking: empirical foundations for a minimal reporting guidelineBehavior Research Methods10.3758/s13428-021-01762-855:1(364-416)Online publication date: 6-Apr-2022
  • (2022)The relationship between visual confirmation bias, belief consistency, and belief polarizationComprehensive Results in Social Psychology10.1080/23743603.2022.20262146:1-3(1-38)Online publication date: 10-May-2022
  • (2021)55 Rides: attention annotated head and gaze data during naturalistic drivingACM Symposium on Eye Tracking Research and Applications10.1145/3448018.3457993(1-8)Online publication date: 25-May-2021
  • (2021)Inferring Goals with Gaze during Teleoperated Manipulation2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)10.1109/IROS51168.2021.9636551(7307-7314)Online publication date: 27-Sep-2021
  • (2020)A MinHash approach for fast scanpath classificationACM Symposium on Eye Tracking Research and Applications10.1145/3379155.3391325(1-9)Online publication date: 2-Jun-2020
  • (2020)Deep semantic gaze embedding and scanpath comparison for expertise classification during OPT viewingACM Symposium on Eye Tracking Research and Applications10.1145/3379155.3391320(1-10)Online publication date: 2-Jun-2020
  • (2019)Quantifying and understanding the differences in visual activities with contrast subsequencesProceedings of the 11th ACM Symposium on Eye Tracking Research & Applications10.1145/3314111.3319842(1-5)Online publication date: 25-Jun-2019
  • (2018)Director's cutProceedings of the 15th ACM SIGGRAPH European Conference on Visual Media Production10.1145/3278471.3278472(1-10)Online publication date: 13-Dec-2018
  • (2018)EyeMSAProceedings of the 2018 ACM Symposium on Eye Tracking Research & Applications10.1145/3204493.3204565(1-5)Online publication date: 14-Jun-2018
  • Show More Cited By

View Options

Get Access

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media