Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 2 A New Framework for Approximate Labeling via Graph Cuts Beijing, China October 17-October 20 ISBN: 0-7695-2334-X
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICCV.2005.14
A new framework is presented that uses tools from duality theory of linear programming to derive graph-cut based combinatorial algorithms for approximating NP-hard classification problems. The derived algorithms include α-expansion graph cut techniques merely as a special case, have guaranteed optimality properties even in cases where ?-expansion techniques fail to do so and can provide very tight per-instance suboptimality bounds in all occasions.
Citation:
Nikos Komodakis, Georgios Tziritas, "A New Framework for Approximate Labeling via Graph Cuts," iccv, vol. 2, pp.1018-1025, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 2, 2005 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||