Natural Visualization

Steve Haroz & Kwan-Liu Ma

University of California at Davis

Outline

• Purpose

• Math Background

• Applying and extending existing theories

• InfoVis Contest

• Application to GUIs

• Summary and Conclusion

Outline

• Purpose

• Math Background

• Applying and extending existing theories

• InfoVis Contest

• Application to GUIs

• Summary and Conclusion

Purpose

• What makes for a good Visualization?– Aesthetics?– Color?– Complexity?– Beginner or Expert? Intuitive?

• Can understanding the process of visualization help?

The Process

0 1 0 1 1

1 0 1 1 0

1 0 0 0 1

…

Visualization

Complete?

Which Representation Is Best?

“Who can prove by experience the non-existence of a cause when all that experience tells us is that we do not perceive it?”

The Process

0 1 0 1 1

1 0 1 1 0

1 0 0 0 1

…

Visualization

Hubel 1988

The Forgotten Stage of Visualization

Purpose

• Applicability of visual system knowledge– Retina “tuned” to natural images

• Certain images more easily perceptible?

• Is interaction aided by these “natural GUIs” ?

Outline

• Purpose

• Math Background

• Applying and extending existing theories

• InfoVis Contest

• Application to GUIs

• Summary and Conclusion

Spatial Frequencies

• Similar to auditory frequencies

• Varying intensity (light) over space

Fourier Transform

• Sum of sin/cos waves

Spatial Frequencies of Natural Images

• Take Fourier transform along each orientation and average

• f -2 pattern

• Pattern is prevalent in all natural scenes

• Plot on log-log scale

Unnatural images

Natural Images

Size Distribution

• This pattern is explained bya ‘collage’ of objects occluding each other

• These objects have a power distributionarea = 2x

Outline

• Purpose

• Math Background

• Applying and extending existing theories

• InfoVis Contest

• Application to GUIs

• Summary and Conclusion

power exponential

linear constant

Plot of spatial frequencies

Const

Exponential

Linear

Power

Linear Trend

-2.67

-2.66

-2.65

-2.64

-2.63

-2.62

-2.61

-2.6

-2.59

Constant Linear Exponential Power

Images Without Occlusion

You can’t visualize what is not visible

• Images with adjacent squares

• Same sizing applies

power exponential

linear constant

Trend – no occlusion

-2.79

-2.77

-2.75

-2.73

-2.71

-2.69

-2.67

Constant Linear Exponential Power

Outline

• Purpose

• Math Background

• Applying and extending existing theories

• InfoVis Contest

• Application to GUIs

• Summary and Conclusion

Naturalness Metric

1. Closeness to f-2

2. Linearity

InfoVis 2004 Contest

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0.2

0.3

0.4

0.5

1st Place 2nd Place

InfoVis 2005 Contest

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0.1

0.2

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0.5

0.6

1st Place 2nd Place 3rd Place

Outline

• Purpose

• Math Background

• Applying and extending existing theories

• InfoVis Contest

• Application to GUIs

• Summary and Conclusion

Image Analysis for GUI Study

• Applications with hierarchical data

• Analyze screenshots

• Compare with usage data (user study)

• Use statistics to find behavioral patterns

Correlation with Response Time

0

0.2

0.4

0.6

0.8

1

1.2

1 2 3 4 5 6

|Slope+2||Avg Dev|

Outline

• Purpose

• Math Background

• Applying and extending existing theories

• InfoVis Contest

• Application to GUIs

• Summary and Conclusion

Summary and Conclusion

• Visualization preference correlates with a property of the visual system

• Bias-free metric may help vis generation

• Utility or aesthetics?

• More visual properties

Acknowledgements

• Bruno Olshausen

• Yue Wang