Gaze data visualization tools: opportunities and challenges

Ramloll, Rameshsharma; Trepagnier, Cheryl; Sebrechts, Marc M.; Beedasy, Jaishree

doi:10.1109/iv.2004.1320141

Cited by 18 publications

(15 citation statements)

References 34 publications

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“…This often implies a time-consuming frame-byframe video data analysis. One solution proposed by Ramloll et al [2004] is a fixation net for dynamic 3D non-stereoscopic content, for which gaze positions are mapped onto flattened objects. Representing binocular scan paths in 3D VRs has been presented by Duchowski et al [2000] for which 2D gaze positions and depths (gaze depth paths) are depicted.…”

Section: Three-dimensional Scan Pathsmentioning

confidence: 99%

“…For investigating gaze behavior, large sets of numerical data have to be collected and evaluated, such as eye positions, calculated fixations and saccades, as well as total fixation times [Ramloll et al 2004]. Consequently, gaze visualizations have helped detecting, understanding, and interpreting essential relationships in such multivariate and multidimensional data.…”

Section: Introductionmentioning

confidence: 99%

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Advanced gaze visualizations for three-dimensional virtual environments

Stellmach

Nacke

Dachselt

2010

Proceedings of the 2010 Symposium on Eye-Tracking Research &Amp; Applications - ETRA '10

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Gaze visualizations represent an effective way for gaining fast insights into eye tracking data. Current approaches do not adequately support eye tracking studies for three-dimensional (3D) virtual environments. Hence, we propose a set of advanced gaze visualization techniques for supporting gaze behavior analysis in such environments. Similar to commonly used gaze visualizations for twodimensional stimuli (e.g., images and websites), we contribute advanced 3D scan paths and 3D attentional maps. In addition, we introduce a models of interest timeline depicting viewed models, which can be used for displaying scan paths in a selected time segment. A prototype toolkit is also discussed which combines an implementation of our proposed techniques. Their potential for facilitating eye tracking studies in virtual environments was supported by a user study among eye tracking and visualization experts.

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Section: Three-dimensional Scan Pathsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Advanced gaze visualizations for three-dimensional virtual environments

Stellmach

Nacke

Dachselt

2010

Proceedings of the 2010 Symposium on Eye-Tracking Research &Amp; Applications - ETRA '10

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“…A scan path comparison framework based on string editing was presented by [Privitera and Stark 2000] and was optimized by [Duchowski et al 2010]. An alternative visualization technique for visualizing gaze data for dynamic stimuli was presented by [Ramloll et al 2004]. Stellmach et al presented a tool for the study of eye movements in three dimensional virtual environments [Stellmach et al 2010].…”

Section: Related Workmentioning

confidence: 99%

Parallel scan-path visualization

Raschke

Ertl

2012

Proceedings of the Symposium on Eye Tracking Research and Applications

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Eye tracking analysis is the state of the art technique to study questions of usability and cognition of graphical user interfaces. This paper presents a new technique for the visualization of eye tracking data, the Parallel Scan-Path Visualization. A key feature is the visualization of eye movements of many subjects on a single screen in a parallel layout. The visualization presents various properties of scan-paths, such as fixations, gaze durations and eye shift frequencies at one glance. The paper concludes with an example of use of the Parallel Scan-Path Visualization technique.

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“…Such plots are useful for detailed quantitative analyses, but not very intuitively interpreted. Other tools supporting interpretation of the data include the visualization of gaze density by means of clustered gaze samples [Heminghous and Duchowski 2006] or the visualization of other features such as fixation duration [Ramloll et al 2004]. * e-mail: dorr@inb.uni-luebeck.de † e-mail: h.jarodzka@iwm-kwmrc.de ‡ e-mail: barth@inb.uni-luebeck.de Better suited for visual inspection are approaches that use the stimulus and enrich it with eye movement data; in the classical paper of Yarbus [1967], gaze traces overlaid on the original images immediately show the regions that were preferentially looked at by the subjects.…”

Section: Introductionmentioning

confidence: 99%

Space-variant spatio-temporal filtering of video for gaze visualization and perceptual learning

Dörr¹,

Jarodzka²,

Barth³

2010

Proceedings of the 2010 Symposium on Eye-Tracking Research &Amp; Applications - ETRA '10

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We introduce an algorithm for space-variant filtering of video based on a spatio-temporal Laplacian pyramid and use this algorithm to render videos in order to visualize pre-recorded eye movements. Spatio-temporal contrast and colour saturation are reduced as a function of distance to the nearest gaze point of regard, i.e. nonfixated, distracting regions are filtered out, whereas fixated image regions remain unchanged. Results of an experiment in which the eye movements of an expert on instructional videos are visualized with this algorithm, so that the gaze of novices is guided to relevant image locations. show that this visualization technique facilitates the novices' perceptual learning.

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Gaze data visualization tools: opportunities and challenges

Cited by 18 publications

References 34 publications

Advanced gaze visualizations for three-dimensional virtual environments

Advanced gaze visualizations for three-dimensional virtual environments

Parallel scan-path visualization

Space-variant spatio-temporal filtering of video for gaze visualization and perceptual learning

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