About: Visual Data Recognition and Modeling Based on Local Markovian Models

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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	An exceptional 3D wide-sense Markov model which can be completely solved analytically and easily synthesised is presented. The model can be modified to faithfully represent complex local data by adaptive numerically robust recursive estimators of all its statistics. Illumination invariants can be derived from some of its recursive statistics and exploited in content based image retrieval, supervised or unsupervised image recognition. Its modelling efficiency is demonstrated on several analytical and modelling image applications, in particular on unsupervised image or range data segmentation, bidirectional texture function (BTF) synthesis and compression, dynamic texture synthesis and adaptive multispectral and multichannel image and video restoration. An exceptional 3D wide-sense Markov model which can be completely solved analytically and easily synthesised is presented. The model can be modified to faithfully represent complex local data by adaptive numerically robust recursive estimators of all its statistics. Illumination invariants can be derived from some of its recursive statistics and exploited in content based image retrieval, supervised or unsupervised image recognition. Its modelling efficiency is demonstrated on several analytical and modelling image applications, in particular on unsupervised image or range data segmentation, bidirectional texture function (BTF) synthesis and compression, dynamic texture synthesis and adaptive multispectral and multichannel image and video restoration. (en)
Title	Visual Data Recognition and Modeling Based on Local Markovian Models Visual Data Recognition and Modeling Based on Local Markovian Models (en)
skos:prefLabel	Visual Data Recognition and Modeling Based on Local Markovian Models Visual Data Recognition and Modeling Based on Local Markovian Models (en)
skos:notation	RIV/67985556:_____/12:00374142!RIV12-AV0-67985556
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(1M0572), P(GA102/08/0593), P(GAP103/11/0335), Z(AV0Z10750506)
http://linked.open...vai/riv/dodaniDat	2012
http://linked.open...aciTvurceVysledku	Haindl, Michal
http://linked.open.../riv/druhVysledku	C - Kapitola v knize
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	177560
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/12:00374142
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Markov random fields; image modeling; image recognition (en)
http://linked.open.../riv/klicoveSlovo	Markov random fields image recognition image modeling
http://linked.open...ontrolniKodProRIV	[1FF791F44AE3]
http://linked.open...i/riv/mistoVydani	London
http://linked.open...i/riv/nazevZdroje	Mathematical Methods for Signal and Image Analysis and Representation
http://linked.open...in/vavai/riv/obor	BD
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...v/pocetStranKnihy	317 (xsd:int)
http://linked.open...cetTvurcuVysledku	1 (xsd:int)
http://linked.open...vavai/riv/projekt	Data, algorithms, decision making BTF Texture Modelling Accurate material appearance measurement
http://linked.open...UplatneniVysledku	2012
http://linked.open...iv/tvurceVysledku	Haindl, Michal
http://linked.open...n/vavai/riv/zamer	Pokročilé matematické metody získávání, zpracování a využití informací a znalostí ve složitých a nedeterministických systémech
number of pages	19 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-1-4471-2353-8_14
http://purl.org/ne...btex#hasPublisher	Springer London
https://schema.org/isbn	978-1-4471-2353-8

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