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Natural Visualization: Enhancing Understanding Through Visual Analysis

Explore the purpose, math background, and application of natural visualization theories for GUI design, highlighting the role of spatial frequencies, Fourier Transform, and image analysis for GUI studies.

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Natural Visualization: Enhancing Understanding Through Visual Analysis

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  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 can’t 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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