TY - GEN
T1 - Higher-order gradient descent by fusion-move graph cut
AU - Ishikawa, Hiroshi
PY - 2009/12/1
Y1 - 2009/12/1
N2 - Markov Random Field is now ubiquitous in many formulations of various vision problems. Recently, optimization of higher-order potentials became practical using higher-order graph cuts: the combination of i) the fusion move algorithm, ii) the reduction of higher-order binary energy minimization to first-order, and iii) the QPBO algorithm. In the fusion move, it is crucial for the success and efficiency of the optimization to provide proposals that fits the energies being optimized. For higher-order energies, it is even more so because they have richer class of null potentials. In this paper, we focus on the efficiency of the higher-order graph cuts and present a simple technique for generating proposal labelings that makes the algorithm much more efficient, which we empirically show using examples in stereo and image denoising.
AB - Markov Random Field is now ubiquitous in many formulations of various vision problems. Recently, optimization of higher-order potentials became practical using higher-order graph cuts: the combination of i) the fusion move algorithm, ii) the reduction of higher-order binary energy minimization to first-order, and iii) the QPBO algorithm. In the fusion move, it is crucial for the success and efficiency of the optimization to provide proposals that fits the energies being optimized. For higher-order energies, it is even more so because they have richer class of null potentials. In this paper, we focus on the efficiency of the higher-order graph cuts and present a simple technique for generating proposal labelings that makes the algorithm much more efficient, which we empirically show using examples in stereo and image denoising.
UR - http://www.scopus.com/inward/record.url?scp=77953211492&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77953211492&partnerID=8YFLogxK
U2 - 10.1109/ICCV.2009.5459187
DO - 10.1109/ICCV.2009.5459187
M3 - Conference contribution
AN - SCOPUS:77953211492
SN - 9781424444205
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 568
EP - 574
BT - 2009 IEEE 12th International Conference on Computer Vision, ICCV 2009
T2 - 12th International Conference on Computer Vision, ICCV 2009
Y2 - 29 September 2009 through 2 October 2009
ER -