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Statements

Subject Item
n2:RIV%2F67985556%3A_____%2F12%3A00374142%21RIV12-AV0-67985556
rdf:type
skos:Concept n17:Vysledek
dcterms: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.
dcterms:title
Visual Data Recognition and Modeling Based on Local Markovian Models Visual Data Recognition and Modeling Based on Local Markovian Models
skos:prefLabel
Visual Data Recognition and Modeling Based on Local Markovian Models Visual Data Recognition and Modeling Based on Local Markovian Models
skos:notation
RIV/67985556:_____/12:00374142!RIV12-AV0-67985556
n17:predkladatel
n18:ico%3A67985556
n4:aktivita
n5:P n5:Z
n4:aktivity
P(1M0572), P(GA102/08/0593), P(GAP103/11/0335), Z(AV0Z10750506)
n4:dodaniDat
n9:2012
n4:domaciTvurceVysledku
n20:2890542
n4:druhVysledku
n19:C
n4:duvernostUdaju
n10:S
n4:entitaPredkladatele
n22:predkladatel
n4:idSjednocenehoVysledku
177560
n4:idVysledku
RIV/67985556:_____/12:00374142
n4:jazykVysledku
n21:eng
n4:klicovaSlova
Markov random fields; image modeling; image recognition
n4:klicoveSlovo
n13:Markov%20random%20fields n13:image%20modeling n13:image%20recognition
n4:kontrolniKodProRIV
[1FF791F44AE3]
n4:mistoVydani
London
n4:nazevZdroje
Mathematical Methods for Signal and Image Analysis and Representation
n4:obor
n15:BD
n4:pocetDomacichTvurcuVysledku
1
n4:pocetStranKnihy
317
n4:pocetTvurcuVysledku
1
n4:projekt
n7:1M0572 n7:GA102%2F08%2F0593 n7:GAP103%2F11%2F0335
n4:rokUplatneniVysledku
n9:2012
n4:tvurceVysledku
Haindl, Michal
n4:zamer
n16:AV0Z10750506
s:numberOfPages
19
n8:doi
10.1007/978-1-4471-2353-8_14
n12:hasPublisher
Springer London
n11:isbn
978-1-4471-2353-8