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Multi-Class Blue Noise Sampling

Multi-Class Blue Noise Sampling. Li-Yi Wei Microsoft Research. smart↑ → research↑. Q: not so smart?. Blue noise. random & uniform sample spacing r. 0.02 0.01 0.01 0.02. r =. r = 0.02. single class. multi class. Multi-class blue noise. class 0. class 1. total set.

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Multi-Class Blue Noise Sampling

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  1. Multi-Class Blue Noise Sampling Li-Yi Wei Microsoft Research

  2. smart↑ → research↑ • Q: not so smart?

  3. Blue noise • random & uniform • sample spacing r

  4. 0.02 0.01 0.01 0.02 r = r = 0.02 single class multi class

  5. Multi-class blue noise class 0 class 1 total set

  6. Object placement

  7. Sensor layout RGB sensors cone/rod cells

  8. Color stippling RGBCMYB dots

  9. A: smart↓ → popular↑ • simpler algorithms • less intimidating too smart # sig10 paper 6 5 5 4

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