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