About: A Discrete Search Method for Multi-modal Non-Rigid Image Registration

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	We consider the problem of image matching under the unknown statistical dependence of the signals, i.e. a signal in one image may correspond to one or more signals in the other image with different probabilities. This problem is widely known as multimodal image registration and is commonly solved by the maximization of the empirical mutual information between the images. The deformation is typically represented in a parametric form and optimization w.r.t. it is performed using gradient-based methods. In contrast, we represent the deformation as a field of discretized displacements and optimize w.r.t. it using pairwise Gibbs energy minimization technique. This has potential advantage of finding good solutions even for problems having many local minima. We consider the problem of image matching under the unknown statistical dependence of the signals, i.e. a signal in one image may correspond to one or more signals in the other image with different probabilities. This problem is widely known as multimodal image registration and is commonly solved by the maximization of the empirical mutual information between the images. The deformation is typically represented in a parametric form and optimization w.r.t. it is performed using gradient-based methods. In contrast, we represent the deformation as a field of discretized displacements and optimize w.r.t. it using pairwise Gibbs energy minimization technique. This has potential advantage of finding good solutions even for problems having many local minima. (en) We consider the problem of image matching under the unknown statistical dependence of the signals, i.e. a signal in one image may correspond to one or more signals in the other image with different probabilities. This problem is widely known as multimodal image registration and is commonly solved by the maximization of the empirical mutual information between the images. The deformation is typically represented in a parametric form and optimization w.r.t. it is performed using gradient-based methods. In contrast, we represent the deformation as a field of discretized displacements and optimize w.r.t. it using pairwise Gibbs energy minimization technique. This has potential advantage of finding good solutions even for problems having many local minima. (cs)
Title	A Discrete Search Method for Multi-modal Non-Rigid Image Registration A Discrete Search Method for Multi-modal Non-Rigid Image Registration (en) A Discrete Search Method for Multi-modal Non-Rigid Image Registration (cs)
skos:prefLabel	A Discrete Search Method for Multi-modal Non-Rigid Image Registration A Discrete Search Method for Multi-modal Non-Rigid Image Registration (en) A Discrete Search Method for Multi-modal Non-Rigid Image Registration (cs)
skos:notation	RIV/68407700:21230/08:03150872!RIV09-MSM-21230___
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(7E08031), P(GA102/07/1317), Z(MSM6840770038)
http://linked.open...vai/riv/dodaniDat	2009
http://linked.open...aciTvurceVysledku	Shekhovtsov, Oleksandr Garcia Arteaga, Juan David Werner, Tomáš
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	České vysoké učení technické v Praze / Fakulta elektrotechnická
http://linked.open...dnocenehoVysledku	354163
http://linked.open...ai/riv/idVysledku	RIV/68407700:21230/08:03150872
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	MRF; energy; matching; mutual information; registration (en)
http://linked.open.../riv/klicoveSlovo	mutual information registration energy matching MRF
http://linked.open...ontrolniKodProRIV	[52AED2B2855F]
http://linked.open...v/mistoKonaniAkce	Anchorage, Alaska
http://linked.open...i/riv/mistoVydani	Los Alamitos
http://linked.open...i/riv/nazevZdroje	NORDIA 2008: Proceedings of the 2008 IEEE CVPR Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	Methods for Visual Recognition of Large Collections of Non-rigid Objects Dynamic Interactive Perception-action Learning in Cognitive Systems
http://linked.open...UplatneniVysledku	2008
http://linked.open...iv/tvurceVysledku	Garcia Arteaga, Juan David Shekhovtsov, Oleksandr Werner, Tomáš
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open...ain/vavai/riv/wos	000260371900123
http://linked.open.../riv/zahajeniAkce	2008-07-27 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Decision Making and Control for Manufacturing III
issn	1063-6919
number of pages	6 (xsd:int)
http://purl.org/ne...btex#hasPublisher	IEEE Computer Society Press
https://schema.org/isbn	978-1-4244-2339-2
http://localhost/t...ganizacniJednotka	21230

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