Natural Visualization Steve Haroz & Kwan-Liu Ma University of California at Davis.

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Presentation transcript:

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 … 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 … 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 by a collage of objects occluding each other These objects have a power distribution area = 2 x

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

Linear Trend

Images Without Occlusion You cant visualize what is not visible Images with adjacent squares Same sizing applies

power exponential linear constant

Trend – no occlusion

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

InfoVis 2005 Contest

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

Outline Purpose Math Background Applying and extending existing theories InfoVis Contest Application to GUIs 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