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SIMS 247: Information Visualization and Presentation Marti Hearst

SIMS 247: Information Visualization and Presentation Marti Hearst. Sept 19, 2005. C o l o r. Most of this segment taken from Colin Ware, Ch. 4. Terms. Hue The differences in color that languages assign names to Saturation: Sometimes called “vividness”, sometimes “brightness” Lightness:

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SIMS 247: Information Visualization and Presentation Marti Hearst

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  1. SIMS 247: Information Visualization and PresentationMarti Hearst Sept 19, 2005

  2. Color Most of this segment taken from Colin Ware, Ch. 4

  3. Terms • Hue • The differences in color that languages assign names to • Saturation: • Sometimes called “vividness”, sometimes “brightness” • Lightness: • A relative measure • How much light appears to reflect from an object compared to what looks like white in a scene (Brewer) • Also sometimes called “value” • Other terms • These are used inconsistently • Intensity (often used to mean Saturation + Lightness) • Luminance (physically measured amount of reflected light) • Chromaticity (hue without brightness)

  4. Color Issues • Complexity of color space • 3-dimensional • Computer vs. Print display • There are many models and standards • Color not critical for many visual tasks • Doesn’t help with determination of: • Layout of objects in space • Motion of objects • Shape of objects • Color-blind people often go for years without knowing about their condition • Color is essential for • “Breaking camouflage” • Recognizing distinctions • Picking berries out from leaves • Spoiled meat vs. good • Aesthetics

  5. CIE Color ModelCIE = Commision Internationale L’Eclairage Images from lecture by Terrance Brooke

  6. CIE Color Model Properties Slide adapted from Wolfgang Muller, http://www.iuw.fh-darmstadt.de/mueller/SS2002/VisWP/07-color-color.pdf

  7. CIE Color Model Properties Slide adapted from Wolfgang Muller, http://www.iuw.fh-darmstadt.de/mueller/SS2002/VisWP/07-color-color.pdf

  8. Small Color Patches More Difficult to Distinguish Images from lecture by Terrance Brooke

  9. Order of Appearance of Color Names across World Cultures Slide adapted from Wolfgang Muller, http://www.iuw.fh-darmstadt.de/mueller/SS2002/VisWP/07-color-color.pdf

  10. Isolating Color Names within a Computer Display Slide adapted from Wolfgang Muller, http://www.iuw.fh-darmstadt.de/mueller/SS2002/VisWP/07-color-color.pdf

  11. Background Color Contrast Slide adapted from Wolfgang Muller, http://www.iuw.fh-darmstadt.de/mueller/SS2002/VisWP/07-color-color.pdf

  12. Some Color Fun Facts • People agree strongly on what pure yellow is • There may be two unique greens • Brown is dark yellow, requires a reference white nearby

  13. Colors for Labeling • Ware recommends to take into account: • Distinctness • Unique hues • Contrast with background • Color blindness • Number • Only a small number of codes can be rapidly perceived • Field Size • Small changes in color are difficult to perceive • Conventions

  14. Ware’s Recommended Colors for Labeling Red, Green, Yellow, Blue, Black, White, Pink, Cyan, Gray, Orange, Brown, Purple. The top six colors are chosen because they are the unique colors that mark the ends of the opponent color axes. The entire set corresponds to the eleven color names found to be the most common in a cross-cultural study, plus cyan (Berlin and Kay) Slide adapted from Terrance Brooke

  15. More Color Use Guidelines • From Cynthia Brewer reading • She’s a cartographer, has a unique perspective • Geocoordinates are already taken • Four-way Guidelines: • Binary • Qualitative • Diverging • Sequential • Make combinations of these • Seq-Seq, Seq-Qual, etc. • I’m not convinced these all work

  16. Color Scheme Types (Brewer) From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  17. Binary Example From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  18. Sequential Examples From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  19. Sequential Example From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  20. Spectral SchemeNot suitable for sequential data From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  21. Qualitative Differences Example From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  22. Qualitative Color Schemes From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  23. Diverging Color Examples From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  24. Divering Color Scheme From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  25. Qualitative-Binary Example From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  26. Qualitative-Sequential Example I suspect this is too much to keep track of. From http://www.personal.psu.edu/faculty/c/a/cab38/ColorSch/Schemes.html

  27. Application to Class Projects • Map of Immigration Routes http://www.sims.berkeley.edu/~vijay/InfoViz/project/writeup/

  28. Next Time • Start Interaction Topics • Turn in A1 • Learn about A2

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