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Natural Visualization

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

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Natural Visualization

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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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