iZoom: A Better Way to View Large Data Sets?

iZoom: A Better Way to View Large Data Sets?

Mike Ashmore

CPSC 462

Problem: Eye Trackers Suck.Problem: Eye Trackers Suck.

• Interactive applications reveal just how noisy and error-prone eye tracker data is

• ~1˚ tracking accuracy on a good calibration

• Up to 30-40 pixels error on a high-resolution display

• High jitter of data just makes reliable selection that much harder

Problem: Application Designers Suck.

Problem: Application Designers Suck.

• Teeny-tiny portions of the screen need to be accurately selected. Everything in WinAmp / XMMS: 6-8 pixels Microsoft Word ruler bar (tabs, etc.): 2 pixels Image editing applications / WYSIWYG print

layout tools: 1 pixel• But they’ve been offering a magnifier tool for ages

now! Perhaps there’s a lesson to be learned …

Solution #1: Make everything bigger so it’s easier to select (the DUPLO approach)

Solution #1: Make everything bigger so it’s easier to select (the DUPLO approach)

• Since it works so well for image editors, we’ll just magnify the whole screen.

• Big wins: Faster, less fatiguing selection of UI elements (c.f. Fitts’ Law)

• Lossage: Amount of information available decreases in proportion to the square of the magnification (2x magnification = 1/4 as much information)

Solution #2: Let the display slide around on a virtual desktop

Solution #2: Let the display slide around on a virtual desktop

• Big wins: You get unlimited desktop real estate. Icons can be as chunky as you want for fast selection of targets within display.

• Lossage: Very little context available for data. Again, 2x magnification of the virtual desktop leaves 3/4 of the desktop non-visible at all times.

iZoom Solution: Gaze-Contingent Fisheye Displays

iZoom Solution: Gaze-Contingent Fisheye Displays

• Big win: A portion of the screen is magnified, but context is still available in the periphery. Best of both worlds!• Possible Problem: Can people use it

without getting motion sickness?• Other Possible Problem: Curiously,

nobody else seems to have published much on this idea. Maybe it hasn’t worked for anybody else, either.

The ExperimentThe Experiment

• Simple selection task: look at the window with the “X” • Three conditions:

Non-fisheye (the control condition) Naïve fisheye• Always-on version of lens

“Smart” fisheye• Lens only appears after detecting a certain

“intentness” of fixation

ChallengesChallenges

• Bad Calibration = Frustrated test subject A Bug! Tobii never reports more than 200 calibration

data points. Are calibrations being truncated? Solution: More sophisticated calibration routine Don’t take calibration samples until we’re fairly certain

subject is fixating in the right spot Redo calibration points that deviate too far from actual

screen coordinates. Be fascist about it until every single point is near perfect

ChallengesChallenges

• The enemy of fisheye performance: the Gutwin effect (aka the oscillating lens of doom).

• Cause: Non-intuitive mapping from control to display Look one inch to the left, expect to see the lens move

exactly one inch to the left in “data space” Particularly troublesome because display and control

are so confounded together

The Gutwin EffectThe Gutwin Effect

• Techniques to address this issue: Remap control space to match distorted visual field Don’t distort visual field at all (Miniotas / 2004:

expanding target zones) Grab and hold fisheye at position of initial fixation

Data ChartData Chart

QuickTime™ and aTIFF (Uncompressed) decompressor

are needed to see this picture.

Data AnalysisData Analysis

• Use of postgreSQL for outlier analysis

• Outlier criterion: • Future work (this evening, probably):

Integrate SQL and R mathematical analysis package for instant build of results

Future WorkFuture Work

• More sophisticated data analysis. • This is clearly a non-normal distribution. What

is it, then? Gamma? Beta?

• Select-and-hold fisheye• Center fixation at start of trials• Counting task - when selection is not an

issue, does fisheye improve performance (accuracy / speed) on detailed inspection tasks?