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A New Framework for Approximate Labeling via Graph Cuts
Beijing, China October 17-October 20
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICCV.2005.14Tenth IEEE International Conference o ...
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Nikos Komodakis, Georgios Tziritas, "A New Framework for Approximate Labeling via Graph Cuts," Computer Vision, IEEE International Conference on, vol. 2, pp. 1018-1025, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 2, 2005.
 
 
BibTex
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@article{ 10.1109/ICCV.2005.14,
author = {Nikos Komodakis and Georgios Tziritas},
title = {A New Framework for Approximate Labeling via Graph Cuts},
journal ={Computer Vision, IEEE International Conference on},
volume = {2},
year = {2005},
issn = {1550-5499},
pages = {1018-1025},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICCV.2005.14},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Computer Vision, IEEE International Conference on
TI - A New Framework for Approximate Labeling via Graph Cuts
SN - 1550-5499
SP1018
EP1025
A1 - Nikos Komodakis,
A1 - Georgios Tziritas,
PY - 2005
KW - null
VL - 2
JA - Computer Vision, IEEE International Conference on
ER -
 
Nikos Komodakis, University of Crete
Georgios Tziritas, University of Crete
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
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