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Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization

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Presenter: Chris WeaverBELIV 2010 Workshophttp://www.beliv.org/beliv2010/

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Page 1: Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization

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Page 2: Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization

Look Before You Link: Eye Tracking inMultiple Coordinated View Visualization

Chris Weaver School of Computer Science and the Center for Spatial Analysis

University of Oklahoma

[email protected]

Page 3: Look Before You Link: Eye Tracking in Multiple Coordinated View Visualization

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compound forms of coordination are emerging

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elemental forms of coordination are established

coordinated multiple viewsare common in

visual analysis tools

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in compositions of viewsby chaining together sequences of interactions

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analytic utility arises from navigation and selectionin individual views

and

Jigsaw list view

Cross-filtered views

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how does representation shape interaction?

we’re still looking mostly at tool designs in terms of

process

representation

how does interaction reflect analytic process?

interaction

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coordination is a special kind of interaction

we act herewhile looking there

...on purpose!

(is coordinated interaction like juggling? or more like a sobriety test?)

here and there can bepixels/pointsshapes/regionsentire views

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exploit dual spatial modalities of gaze and motion to analyze interaction patterns

supplant (not replace) input tracking with eye tracking

are entire views more suitable targets for current hardware capabilities?

temporalrate (250Hz)latency (10ms)

spatialresolution (0.5°, ~10 pixels)

SMIvision RED 250

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High-dimensional drill-down into people, genres, awards, release dates, and box office characteristics of mainstream movies

Data Sources: www.imdb.com and InfoVis 2007 Contest Co-Chairs

Cinegraph (visualization)

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Cinegraph (metavisualization)

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so what are we planning to do?

beat the hardware into submission (sigh...)

implement a Java API for calibration and data collection

splice gaze data into the input event streamconsumed by views

expose gaze data to the Improvise transformation pipeline/query language

metavisualize aggregated gazes in the multiview context

precompute query ensembles for likely future paths of interaction across coordinations?

think about head-to-head collaborative coordination (we have two trackers)

how far can we go looking at the view level?

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Thanks!