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Statements

Subject Item
n2:RIV%2F00216224%3A14330%2F11%3A00067211%21RIV14-MSM-14330___
rdf:type
n18:Vysledek skos:Concept
rdfs:seeAlso
http://www.springerlink.com/content/g64286w402h4v1p6/
dcterms:description
Boykov and Kolmogorov showed that it is possible to find globally minimal contours and surfaces via graph cuts by embedding an appropriate metric approximation into the graph edge weights and derived the requisite formulas for Euclidean and Riemannian metrics. In [2] we have proposed an improved Euclidean metric approximation that is invariant under (horizontal and vertical) mirroring, applicable to grids with anisotropic resolution and with a smaller approximation error. In this paper, we extend our method to general Riemannian metrics that are essential for graph cut based image segmentation or stereo matching. It is achieved by the introduction of a transformation reducing the Riemannian case to the Euclidean one and adjusting the formulas from [9] to be able to cope with non-orthogonal grids. We demonstrate that the proposed method yields smaller approximation errors than the previous approaches both in theory and practice. Boykov and Kolmogorov showed that it is possible to find globally minimal contours and surfaces via graph cuts by embedding an appropriate metric approximation into the graph edge weights and derived the requisite formulas for Euclidean and Riemannian metrics. In [2] we have proposed an improved Euclidean metric approximation that is invariant under (horizontal and vertical) mirroring, applicable to grids with anisotropic resolution and with a smaller approximation error. In this paper, we extend our method to general Riemannian metrics that are essential for graph cut based image segmentation or stereo matching. It is achieved by the introduction of a transformation reducing the Riemannian case to the Euclidean one and adjusting the formulas from [9] to be able to cope with non-orthogonal grids. We demonstrate that the proposed method yields smaller approximation errors than the previous approaches both in theory and practice.
dcterms:title
An Improved Riemannian Metric Approximation for Graph Cuts An Improved Riemannian Metric Approximation for Graph Cuts
skos:prefLabel
An Improved Riemannian Metric Approximation for Graph Cuts An Improved Riemannian Metric Approximation for Graph Cuts
skos:notation
RIV/00216224:14330/11:00067211!RIV14-MSM-14330___
n18:predkladatel
n19:orjk%3A14330
n3:aktivita
n13:S n13:P n13:Z
n3:aktivity
P(2B06052), P(LC535), S, Z(MSM0021622419)
n3:dodaniDat
n21:2014
n3:domaciTvurceVysledku
n16:8900736 n16:9465146
n3:druhVysledku
n10:D
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n24:predkladatel
n3:idSjednocenehoVysledku
185487
n3:idVysledku
RIV/00216224:14330/11:00067211
n3:jazykVysledku
n8:eng
n3:klicovaSlova
graph cuts; metric approximation; Riemannian metrics; image segmentation
n3:klicoveSlovo
n7:graph%20cuts n7:Riemannian%20metrics n7:metric%20approximation n7:image%20segmentation
n3:kontrolniKodProRIV
[F2901D16D694]
n3:mistoKonaniAkce
Nancy
n3:mistoVydani
Berlin, Heidelberg
n3:nazevZdroje
16th International Conference on Discrete Geometry for Computer Imagery
n3:obor
n23:IN
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n6:LC535 n6:2B06052
n3:rokUplatneniVysledku
n21:2011
n3:tvurceVysledku
Daněk, Ondřej Matula, Pavel
n3:typAkce
n25:WRD
n3:wos
000297039900006
n3:zahajeniAkce
2011-01-01+01:00
n3:zamer
n22:MSM0021622419
s:issn
0302-9743
s:numberOfPages
12
n4:doi
10.1007/978-3-642-19867-0_6
n9:hasPublisher
Springer-Verlag
n11:isbn
9783642198663
n12:organizacniJednotka
14330