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Fun with Computer Vision

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Materi kuliah umum kapita selekta di ITTelkom, 13 Oktober 2012

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Fun with Computer Vision

  1. 1. Kuliah Umum Kapita Selekta ITTelkom, 13 Oktober 2012Peb Ruswono Aryanhttp://about.me/peb
  2. 2.  Peb Ruswono Aryan Edu :  S1 Informatika ITB, 2002-2007  S2 Informatika ITB, 2008-2010 Work :  R & D, Digital Mark Reader (DMR), 2007-2010  Dosen, STEI ITB, 2010-present Interest :  Visualization  Image Processing and Interpretation
  3. 3. + =
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  5. 5.  Multiscale tricks If it must fail, it must fail early Iterative Reduction by (re-)Weighting
  6. 6.  Statistical Model of Shape & Appearance for constrained search [Tim Cootes] Shape : point location Appearance : image patch around point X = Xavg + StdDev  X = Xavg + Pb P : PCA , b : parameter (reduced search space) Steps :  Foreach point in shape model: ▪ Find most similar patches along normal direction ▪ Test if current shape fit with learned model ▪ Continue until convergence
  7. 7.  Hx = z, given x & z, find H Set of pair of matched points Overdetermined system of linear equation RANSAC  Pick small subset  Calculate H  Check whether H is supported by the rest of population  Select best H with biggest support (minimize error)
  8. 8. Colorconsistency!
  9. 9.  Poisson Equation Laplace(source[mask]) = Laplace(dest[mask]) Boundary Condition : destination pixels Discrete Poisson Operator Sparse Matrix Linear Solver  Direct  Iterative Relaxation http://pebbie.wordpress.com/2012/10/21/poisson-image-editing-revised/
  10. 10.  Poisson Equation where f = 0 Result : Smooth interpolation
  11. 11. This is gone
  12. 12.  Fill patches with highest information content  Structure (edge)  Boundary-patch  High variance : chaotic textures (e.g. grass)  Low variance : plain
  13. 13.  Math can also means Fun especially when it’s applied, you don’t know what you’ve missed Innovation in Research seeks the balance between pragmatic and platonic (practical vs ideal), there are still lot of areas to explore For everything one can imagine, someone is making it somewhere
  14. 14.  DO NOT Afraid! DO NOT Worry! DO NOT Hesitate!
  15. 15. Please ask me!

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