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| rdf:type
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| Description
| - We propose a novel MRF-based model for deformable image matching (also known as registration). The deformation is described by a field of discrete variables, representing displacements of (blocks of) pixels. Discontinuities in the deformation are prohibited by imposing hard pairwise constraints in the model. Exact maximum a posteriori inference is intractable and we apply a linear programming relaxation technique. We show that, when reformulated in the form of two coupled fields of x- and y- displacements, the problem leads to a simpler relaxation to which we apply the TRW-S (Sequential Tree-Reweighted Message passing) algorithm [Wainwright-03, Kolmogorov-05]. This enables image registration with large displacements at a single scale. We employ fast message updates for a special type of interaction as was proposed [Felzenszwalb and Huttenlocher-04] for the max-product Belief Propagation (BP) and introduce a few independent speedups. In contrast to BP, the TRW-S allows us to compute per
- We propose a novel MRF-based model for deformable image matching (also known as registration). The deformation is described by a field of discrete variables, representing displacements of (blocks of) pixels. Discontinuities in the deformation are prohibited by imposing hard pairwise constraints in the model. Exact maximum a posteriori inference is intractable and we apply a linear programming relaxation technique. We show that, when reformulated in the form of two coupled fields of x- and y- displacements, the problem leads to a simpler relaxation to which we apply the TRW-S (Sequential Tree-Reweighted Message passing) algorithm [Wainwright-03, Kolmogorov-05]. This enables image registration with large displacements at a single scale. We employ fast message updates for a special type of interaction as was proposed [Felzenszwalb and Huttenlocher-04] for the max-product Belief Propagation (BP) and introduce a few independent speedups. In contrast to BP, the TRW-S allows us to compute per (en)
- We propose a novel MRF-based model for deformable image matching (also known as registration). The deformation is described by a field of discrete variables, representing displacements of (blocks of) pixels. Discontinuities in the deformation are prohibited by imposing hard pairwise constraints in the model. Exact maximum a posteriori inference is intractable and we apply a linear programming relaxation technique. We show that, when reformulated in the form of two coupled fields of x- and y- displacements, the problem leads to a simpler relaxation to which we apply the TRW-S (Sequential Tree-Reweighted Message passing) algorithm [Wainwright-03, Kolmogorov-05]. This enables image registration with large displacements at a single scale. We employ fast message updates for a special type of interaction as was proposed [Felzenszwalb and Huttenlocher-04] for the max-product Belief Propagation (BP) and introduce a few independent speedups. In contrast to BP, the TRW-S allows us to compute per (cs)
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| Title
| - Efficient MRF Deformation Model for Non-Rigid Image Matching
- Efficient MRF Deformation Model for Non-Rigid Image Matching (en)
- Efficient MRF Deformation Model for Non-Rigid Image Matching (cs)
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| skos:prefLabel
| - Efficient MRF Deformation Model for Non-Rigid Image Matching
- Efficient MRF Deformation Model for Non-Rigid Image Matching (en)
- Efficient MRF Deformation Model for Non-Rigid Image Matching (cs)
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| skos:notation
| - RIV/68407700:21230/08:03150820!RIV09-MSM-21230___
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| http://linked.open...avai/riv/aktivita
| |
| http://linked.open...avai/riv/aktivity
| - P(7E08031), Z(MSM6840770038)
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| http://linked.open...iv/cisloPeriodika
| |
| http://linked.open...vai/riv/dodaniDat
| |
| http://linked.open...aciTvurceVysledku
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| http://linked.open.../riv/druhVysledku
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| http://linked.open...iv/duvernostUdaju
| |
| http://linked.open...titaPredkladatele
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| http://linked.open...dnocenehoVysledku
| |
| http://linked.open...ai/riv/idVysledku
| - RIV/68407700:21230/08:03150820
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| http://linked.open...riv/jazykVysledku
| |
| http://linked.open.../riv/klicovaSlova
| - MRF; Markov random fields; energy minimization; image registration; labeling; message passing (en)
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| http://linked.open.../riv/klicoveSlovo
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| http://linked.open...odStatuVydavatele
| - US - Spojené státy americké
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| http://linked.open...ontrolniKodProRIV
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| http://linked.open...i/riv/nazevZdroje
| - Computer Vision and Image Understanding
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| http://linked.open...in/vavai/riv/obor
| |
| http://linked.open...ichTvurcuVysledku
| |
| http://linked.open...cetTvurcuVysledku
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| http://linked.open...vavai/riv/projekt
| |
| http://linked.open...UplatneniVysledku
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| http://linked.open...v/svazekPeriodika
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| http://linked.open...iv/tvurceVysledku
| - Hlaváč, Václav
- Shekhovtsov, Oleksandr
- Kovtun, I.
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| http://linked.open...ain/vavai/riv/wos
| |
| http://linked.open...n/vavai/riv/zamer
| |
| issn
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| number of pages
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| http://localhost/t...ganizacniJednotka
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| is http://linked.open...avai/riv/vysledek
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