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[SIGGRAPH 2017] Sequential Line Search for Efficient Visual Design Optimization by Crowds

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Talk slide at SIGGRAPH 2017.
Project page: http://koyama.xyz/project/sequential_line_search/

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[SIGGRAPH 2017] Sequential Line Search for Efficient Visual Design Optimization by Crowds

  1. 1. Sequential Line Search for Efficient Visual Design Optimization by Crowds Takeo IgarashiIssei SatoYuki Koyama Daisuke Sakamoto
  2. 2. Motivation
  3. 3. Parameter Tweaking Based on Preference
  4. 4. Design Exploration Optimization x⇤ = arg max x2X Goodness(x)
  5. 5. Optimization x⇤ = arg max x2X Goodness(x) 
 

  6. 6. Human-in-the-Loop Optimization
  7. 7. Crowdsourced Human Computation 0110 0101 1101 Alexander J. Quinn and Benjamin B. Bederson. 2011. Human computation: a survey and taxonomy of a growing field. In Proc. CHI '11. 1403-1412.
  8. 8. Related Work on Crowdsourced Human Computation 

  9. 9. Contributions
  10. 10. Contributions
  11. 11. Microtask Design
  12. 12. 
 Microtask Design
  13. 13. 😁
  14. 14. Technical Challenges
  15. 15. Technical Background: (Standard) Bayesian Optimization
  16. 16. (Standard) Bayesian Optimization
  17. 17. New Technique: Bayesian Optimization Based on Line Search
  18. 18. Our Method
  19. 19. How to Define Slider Spaces S
  20. 20. How to Define Slider Spaces x+ = arg max x2{xi} µ(x) xEI = arg max x2X EI(x)
  21. 21. Web Interface 
 for Crowdsourcing
  22. 22. Applications #1 Photo Color Enhancement (6D)
  23. 23. Evaluation: Crowdsourced Voting
  24. 24. Applications #2 Material Appearance (3D / 7D)
  25. 25. Comparative Evaluation
  26. 26. Comparative Evaluation
  27. 27. Experiment #1: Synthetic Setting
  28. 28. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0 5 10 15 20 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0 5 10 15 20 Optimizing a 2D function
  29. 29. Optimizing a 6D function 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0.90 1.00 0 5 10 15 20 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 0 5 10 15 20
  30. 30. Optimizing a 20D function 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 0 5 10 15 20 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 0 5 10 15 20
  31. 31. Experiment #2: Crowdsourcing Setting
  32. 32. Experiment #2: Crowdsourcing Setting 0 5 10 15 20 25 30 35 0 2 4 6 8 10 12 14 16 18 20 0 5 10 15 20 25 30 35 0 2 4 6 8 10 12 14 16 18 20
  33. 33. Summary
  34. 34. Summary Concept: Strategy: Technique: Applications:
  35. 35. Limitation & Future Work
  36. 36. Sequential Line Search for Efficient Visual Design Optimization by Crowds Takeo IgarashiIssei SatoYuki Koyama Daisuke Sakamoto
  37. 37. Optimization with Different Initial Conditions
  38. 38. Task Burden (Completion Time) 0 10 20 30 40 50 60 70 80 90 SSM 2GC 4GC TaskCompletionTime[s]
  39. 39. Advantages of Involving Many Crowds
  40. 40. Assumptions on Design Domains
  41. 41. Assumptions on Crowds
  42. 42. Difficult Cases SIGGRAPH SIGGRAPH SIGGRAPH

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