Počet záznamů: 1
Mathematical Methods for Signal and Image Analysis and Representation
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SYSNO ASEP 0374142 Druh ASEP M - Kapitola v monografii Zařazení RIV C - Kapitola v knize Název Visual Data Recognition and Modeling Based on Local Markovian Models Tvůrce(i) Haindl, Michal (UTIA-B) RID, ORCID Celkový počet autorů 1 Zdroj.dok. Mathematical Methods for Signal and Image Analysis and Representation, 14. - London : Springer London, 2012 / Florack Luc ; Duits Remco ; Jongbloed Geurt ; Lieshout Marie-Colette ; Davies Laurie - ISBN 978-1-4471-2353-8 Rozsah stran s. 241-259 Poč.str. 19 s. Poč.str.knihy 317 Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova Markov random fields ; image modeling ; image recognition Vědní obor RIV BD - Teorie informace CEP 1M0572 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy GAP103/11/0335 GA ČR - Grantová agentura ČR GA102/08/0593 GA ČR - Grantová agentura ČR CEZ AV0Z10750506 - UTIA-B (2005-2011) DOI 10.1007/978-1-4471-2353-8_14 Anotace 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. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2012
Počet záznamů: 1