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GrabCut Interactive Foreground Extraction using Iterated Graph Cuts Carsten Rother Vladimir Kolmogorov Andrew Blake Microsoft Research Cambridge-UK. video. GrabCut – Interactive Foreground Extraction 2. Problem. Fast & Accurate ?. GrabCut – Interactive Foreground Extraction 3.

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

  2. video

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

  4. GrabCut – Interactive Foreground Extraction3 What GrabCut does Magic Wand(198?) Intelligent ScissorsMortensen and Barrett (1995) GrabCut User Input Result Regions Regions & Boundary Boundary

  5. GrabCut – Interactive Foreground Extraction4 Framework Input: Image Output: Segmentation Parameters:Colour ,Coherence Energy: Optimization:

  6. 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 CutsBoykov and Jolly (2001) Image

  7. GrabCut – Interactive Foreground Extraction6 Iterated Graph Cut ? User Initialisation Graph cuts to infer the segmentation K-means for learning colour distributions

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

  9. GrabCut – Interactive Foreground Extraction8 Colour Model Gaussian Mixture Model (typically 5-8 components) R R Iterated graph cut Foreground &Background Foreground G Background G Background

  10. Blake et al. (2004):Learn jointly GrabCut – Interactive Foreground Extraction9 Coherence Model An object is a coherent set of pixels:

  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

  13. GrabCut – Interactive Foreground Extraction12 Evaluation – Labelled Database Available online: http://research.microsoft.com/vision/cambridge/segmentation/

  14. Error Rate: 0.72% GrabCut – Interactive Foreground Extraction13 Comparison Boykov and Jolly (2001) GrabCut User Input Result Error Rate: 1.87% Error Rate: 1.81% Error Rate: 1.32% Error Rate: 1.25% Error Rate: 0.72%

  15. GrabCut – Interactive Foreground Extraction22 Summary Intelligent Scissors Mortensen and Barrett (1995) LazySnappingLi et al. (2004) Graph Cuts Boykov and Jolly (2001) Magic Wand (198?) GrabCutRother et al. (2004)

  16. GrabCut – Interactive Foreground Extraction23 Conclusions GrabCut – powerful interactive extraction tool Iterated Graph Cut based on colour and contrast Regularized alpha matting by Dynamic Programming

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