# Cooperative Cuts for Image Segmentation

@inproceedings{Jegelka2010CooperativeCF, title={Cooperative Cuts for Image Segmentation}, author={S. Jegelka and J. Bilmes}, year={2010} }

We propose a novel framework for graph-based cooperative regularization that uses submodular costs on graph edges. We introduce an efficient iterative algorithm to solve the resulting hard discrete optimization problem, and show that it has a guaranteed approximation factor. The edge-submodular formulation is amenable to the same extensions as standard graph cut approaches, and applicable to a range of problems. We apply this method to the image segmentation problem. Specifically, Here, we… Expand

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#### References

SHOWING 1-10 OF 46 REFERENCES

Graph cut based image segmentation with connectivity priors

- Mathematics, Computer Science
- 2008 IEEE Conference on Computer Vision and Pattern Recognition
- 2008

This work forms several versions of the connectivity constraint and shows that the corresponding optimization problems are all NP-hard. Expand

Graph Cuts and Efficient N-D Image Segmentation

- Mathematics, Computer Science
- International Journal of Computer Vision
- 2006

This application epitomizes the best features of combinatorial graph cuts methods in vision: global optima, practical efficiency, numerical robustness, ability to fuse a wide range of visual cues and constraints, unrestricted topological properties of segments, and applicability to N-D problems. Expand

Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images

- Computer Science
- ICCV
- 2001

A new technique for general purpose interactive segmentation of N-dimensional images where the user marks certain pixels as “object” or “background” to provide hard constraints for segmentation. Expand

"GrabCut": interactive foreground extraction using iterated graph cuts

- Computer Science
- ACM Trans. Graph.
- 2004

A more powerful, iterative version of the optimisation of the graph-cut approach is developed and the power of the iterative algorithm is used to simplify substantially the user interaction needed for a given quality of result. Expand

Interactive Image Segmentation Using an Adaptive GMMRF Model

- Computer Science
- ECCV
- 2004

Estimation is performed by solving a graph cut problem for which very efficient algorithms have recently been developed, however the model depends on parameters which must be set by hand and the aim of this work is for those constants to be learned from image data. Expand

Image segmentation with a bounding box prior

- Mathematics, Computer Science
- 2009 IEEE 12th International Conference on Computer Vision
- 2009

This paper discusses how the bounding box can be further used to impose a powerful topological prior, which prevents the solution from excessive shrinking and ensures that the user-provided box bounds the segmentation in a sufficiently tight way. Expand

Robust Higher Order Potentials for Enforcing Label Consistency

- Mathematics, Computer Science
- 2008 IEEE Conference on Computer Vision and Pattern Recognition
- 2008

This paper proposes a novel framework for labelling problems which is able to combine multiple segmentations in a principled manner based on higher order conditional random fields and uses potentials defined on sets of pixels generated using unsupervised segmentation algorithms. Expand

Minimizing Nonsubmodular Functions with Graph Cuts-A Review

- Mathematics, Medicine
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- 2007

This survey reviews some results that show that graph cuts can be applied to a much larger class of energy functions (in particular, nonsubmodular functions) and demonstrates the relevance of these results to vision on the problem of binary texture restoration. Expand

Global connectivity potentials for random field models

- Mathematics
- 2009 IEEE Conference on Computer Vision and Pattern Recognition
- 2009

Markov random field (MRF, CRF) models are popular in computer vision. However, in order to be computationally tractable they are limited to incorporate only local interactions and cannot model global… Expand

What energy functions can be minimized via graph cuts?

- Computer Science, Medicine
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- 2004

This work gives a precise characterization of what energy functions can be minimized using graph cuts, among the energy functions that can be written as a sum of terms containing three or fewer binary variables. Expand