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Natural Visualization

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Visualization preference correlates with a property of the visual system ... Utility or aesthetics? More visual properties. Acknowledgements. Bruno Olshausen. Yue Wang ... – PowerPoint PPT presentation

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Title: Natural Visualization


1
Natural Visualization
  • Steve Haroz Kwan-Liu Ma
  • University of California at Davis

2
Outline
  • Purpose
  • Math Background
  • Applying and extending existing theories
  • InfoVis Contest
  • Application to GUIs
  • Summary and Conclusion

3
Outline
  • Purpose
  • Math Background
  • Applying and extending existing theories
  • InfoVis Contest
  • Application to GUIs
  • Summary and Conclusion

4
Purpose
  • What makes for a good Visualization?
  • Aesthetics?
  • Color?
  • Complexity?
  • Beginner or Expert? Intuitive?
  • Can understanding the process of visualization
    help?

5
The Process
0 1 0 1 1 1 0 1 1 0 1 0 0 0 1
Visualization
Complete?
6
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?
7
The Process
0 1 0 1 1 1 0 1 1 0 1 0 0 0 1
Visualization
8
The Forgotten Stage of Visualization
Hubel 1988
9
Purpose
  • Applicability of visual system knowledge
  • Retina tuned to natural images
  • Certain images more easily perceptible?
  • Is interaction aided by these natural GUIs ?

10
Outline
  • Purpose
  • Math Background
  • Applying and extending existing theories
  • InfoVis Contest
  • Application to GUIs
  • Summary and Conclusion

11
Spatial Frequencies
  • Similar to auditory frequencies
  • Varying intensity (light) over space

12
Fourier Transform
  • Sum of sin/cos waves

13
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

14
Unnatural images
15
Natural Images
16
Size Distribution
  • This pattern is explained by
  • a collage of objects occluding each other
  • These objects have a power distribution
  • area 2x

17
Outline
  • Purpose
  • Math Background
  • Applying and extending existing theories
  • InfoVis Contest
  • Application to GUIs
  • Summary and Conclusion

18
exponential
power
constant
linear
19
Plot of spatial frequencies
20
Linear Trend
21
Images Without Occlusion
  • You cant visualize what is not visible
  • Images with adjacent squares
  • Same sizing applies

22
exponential
power
constant
linear
23
Trend no occlusion
24
Outline
  • Purpose
  • Math Background
  • Applying and extending existing theories
  • InfoVis Contest
  • Application to GUIs
  • Summary and Conclusion

25
Naturalness Metric
  • Closeness to f-2
  • Linearity

26
InfoVis 2004 Contest
27
InfoVis 2005 Contest
28
Outline
  • Purpose
  • Math Background
  • Applying and extending existing theories
  • InfoVis Contest
  • Application to GUIs
  • Summary and Conclusion

29
Image Analysis for GUI Study
  • Applications with hierarchical data
  • Analyze screenshots
  • Compare with usage data (user study)
  • Use statistics to find behavioral patterns

30
Correlation with Response Time
31
Outline
  • Purpose
  • Math Background
  • Applying and extending existing theories
  • InfoVis Contest
  • Application to GUIs
  • Summary and Conclusion

32
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

33
Acknowledgements
  • Bruno Olshausen
  • Yue Wang
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