searching for patterns in the world color survey
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Searching for patterns in the World Color Survey Gerhard J ager - PowerPoint PPT Presentation

Searching for patterns in the World Color Survey Gerhard J ager gerhard.jaeger@uni-tuebingen.de July 2, 2009 University of Frankfurt 1/115 Overview Structure of the talk the psychological color space Berlin and Kays 1969 study the


  1. PC9 brown vs. black/pink 65/115

  2. PC10 brown vs. light blue/yellow/black 66/115

  3. Projecting observed data on 10d-manifold noise removal: project observed data onto the lower-dimensional submanifold that was obtained via PCA in our case: noisy binary categories are mapped to smoothed fuzzy categories (= probability distributions over Munsell chips) some examples: 67/115

  4. Projecting observed data on 10d-manifold 68/115

  5. Projecting observed data on 10d-manifold 69/115

  6. Projecting observed data on 10d-manifold 70/115

  7. Projecting observed data on 10d-manifold 71/115

  8. Projecting observed data on 10d-manifold 72/115

  9. Projecting observed data on 10d-manifold 73/115

  10. Projecting observed data on 10d-manifold 74/115

  11. Projecting observed data on 10d-manifold 75/115

  12. Projecting observed data on 10d-manifold 76/115

  13. Projecting observed data on 10d-manifold 77/115

  14. Projecting observed data on 10d-manifold 78/115

  15. Projecting observed data on 10d-manifold 79/115

  16. Projecting observed data on 10d-manifold 80/115

  17. Projecting observed data on 10d-manifold 81/115

  18. Projecting observed data on 10d-manifold 82/115

  19. Projecting observed data on 10d-manifold 83/115

  20. Projecting observed data on 10d-manifold 84/115

  21. Projecting observed data on 10d-manifold 85/115

  22. Projecting observed data on 10d-manifold 86/115

  23. Projecting observed data on 10d-manifold 87/115

  24. Smoothed partitions of the color space vocabulary of a given language does not always form a partition many cases of (near) synonymy, hyponymy, and overlap for instance language 1 (Abidjy, Ivory Coast): 88/115

  25. Smoothed partitions of the color space 89/115

  26. Smoothed partitions of the color space if two categories of one language have a correlation of at least . 5 , they are treated as synonyms process is repeated if remaining categories are independent or negatively correlated after this process, each Munsell chip c is assigned to the category that assigns the highest probability to c for Abidji, we get 90/115

  27. Smoothed partitions of the color space some more examples: Waorani (Ecuador) 91/115

  28. Smoothed partitions of the color space some more examples: Arabela (Peru) 92/115

  29. Smoothed partitions of the color space some more examples: Camsa (Colombia) 93/115

  30. Smoothed partitions of the color space some more examples: Candoshi (Peru) 94/115

  31. Smoothed partitions of the color space some more examples: Chinanteco (Mexico) 95/115

  32. Smoothed partitions of the color space some more examples: Guarijio (Mexico) 96/115

  33. Smoothed partitions of the color space some more examples: Gunu (Cameroon) 97/115

  34. Smoothed partitions of the color space some more examples: Kalam (Papua New Guinea) 98/115

  35. Smoothed partitions of the color space some more examples: Menye (Papua New Guinea) 99/115

  36. Smoothed partitions of the color space some more examples: Tifal (Papua New Guinea) 100/115

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