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GrabCut Interactive Foreground Extraction using Iterated Graph Cuts Carsten Rother Vladimir Kolmogorov Andrew Blake Microsoft Research Cambridge-UK. GrabCut – Interactive Foreground Extraction 2. Problem. Fast & Accurate ?. Foreground (source). Min Cut. Background (sink).

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Problem

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  1. GrabCutInteractive Foreground Extraction using Iterated Graph CutsCarsten RotherVladimir KolmogorovAndrew BlakeMicrosoft Research Cambridge-UK

  2. GrabCut – Interactive Foreground Extraction2 Problem Fast & Accurate ?

  3. Foreground (source) Min Cut Background(sink) Cut: separating source and sink; Energy: collection of edges Min Cut: Global minimal enegry in polynomial time GrabCut – Interactive Foreground Extraction5 Graph Cuts modelling in images Image

  4. Foreground (source) Min Cut Background(sink) GrabCut – Interactive Foreground Extraction5 Graph Cuts for foreground extraction Assume we know foreground is whiteand background is black

  5. Foreground (source) Min Cut Background(sink) GrabCut – Interactive Foreground Extraction5 Graph Cuts for foreground extraction Assume we know foreground is whiteand background is black Data term = (cost of assigning label) Regularization = (cost of separating neighbors)

  6. Foreground (source) Min Cut Background(sink) GrabCut – Interactive Foreground Extraction5 Graph Cuts for foreground extraction Assume we know foreground is whiteand background is black Data term = whiteness (cost of assigning label) Regularization = (cost of separating neighbors)

  7. Foreground (source) Min Cut Background(sink) GrabCut – Interactive Foreground Extraction5 Graph Cuts for foreground extraction Assume we know foreground is whiteand background is black Data term = whiteness (cost of assigning label) Regularization = color match (cost of separating neighbors)

  8. GrabCut – Interactive Foreground Extraction6 We are all set now ! ? User Initialisation Graph cuts to infer the foreground Learn foreground color model

  9. GrabCut – Interactive Foreground Extraction6 Iterated Graph Cuts ? User Initialisation Graph cuts to infer the foreground Learn foreground color model

  10. GrabCut – Interactive Foreground Extraction7 Iterated Graph Cuts Guaranteed toconverge 1 3 4 2 Result Energy after each Iteration

  11. GrabCut – Interactive Foreground Extraction10 Moderately straightforward examples … GrabCut completes automatically

  12. GrabCut – Interactive Foreground Extraction11 Difficult Examples Camouflage & Low Contrast Fine structure No telepathy Initial Rectangle InitialResult

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