Efficient MRF Deformation Model for Non-Rigid Image Matching

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A03150820" target="_blank" >RIV/68407700:21230/08:03150820 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Efficient MRF Deformation Model for Non-Rigid Image Matching

Original language 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

Czech name

Efficient MRF Deformation Model for Non-Rigid Image Matching

Czech 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

Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

JD - Use of computers, robotics and its application

OECD FORD branch

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Project

<a href="/en/project/7E08031" target="_blank" >7E08031: Dynamic Interactive Perception-action Learning in Cognitive Systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2008

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computer Vision and Image Understanding

ISSN

1077-3142

e-ISSN

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Volume of the periodical

112

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

9

Pages from-to

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UT code for WoS article

000260090900009

EID of the result in the Scopus database

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