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# Fun with Computer Vision

Materi kuliah umum kapita selekta di ITTelkom, 13 Oktober 2012

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 2012 Peb Ruswono Aryan http://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. Color consistency!
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!