T B. T U. T F. Interactive image segmentation Sara Vicente 1 ([email protected]) Supervised by Vladimir Kolmogorov 1 and Carsten Rother 2 1 University College London, 2 Microsoft Research Cambridge.
Interactive image segmentation
Sara Vicente 1([email protected])
Supervised by Vladimir Kolmogorov 1 and Carsten Rother 2
1 University College London, 2 Microsoft Research Cambridge
The aim of interactive image segmentation is to extract an object from an image by segmenting the image in two regions: background and foreground.
To minimize the problems of fully automatic segmentation, a user imposes some hard constraints: a lasso or rectangle around the object or the specification of regions that have to be part of background or foreground.
Computes segmentation using a standard minimum cut algorithm
Updates in each iteration the colour model for background and foreground based on last iteration
Colour agreement: colour of the pixel should agree with the colour model of the label assigned to it (colour models are computed for background and foreground)
Regional coherence: neighbour pixels should be assigned the same label, especially if the colour of both is similar.
Different weights can be given to the two components of the model producing very distinct results.
Assign to each pixel a label
0 – background, 1 – foreground
dividing the image in two regions
User Input Trimap:
TF – foreground
TU – unknown region
TB – background
Extreme settings: exaggerated colour agreement weight
Extreme settings: exaggerated regional coherence weight
Improving GrabCut: introducing flux
GrabCut “shrinking” effect
Results with flux
For some images, GrabCut algorithm has a shrinking effect, cutting elongated structures.
It was proven in  that it is possible to integrate the optimization of flux in the GrabCut framework. This integration should prevent this shrinking effect to happen.
The choice of the vector field for which we intend to optimize the flux should be done carefully in order to achieved the desirable results.
 Vladimir Kolmogorov and Yuri Boykov. What metrics can be approximated by geocuts, or global optimization of length/area and flux. In ICCV ’05, 2005.
 C. Rother, V. Komogorov, and A. Blake, “GrabCut” - Interactive foreground extraction using iterated graph cuts. In ACM Transactions on Graphics (SIGGRAPH'04), 2004