Number of the records: 1  

Probabilistic mixture-based image modelling

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    SYSNO ASEP0360244
    Document TypeJ - Journal Article
    R&D Document TypeJournal Article
    Subsidiary JČlánek ve WOS
    TitleProbabilistic mixture-based image modelling
    Author(s) Haindl, Michal (UTIA-B) RID, ORCID
    Havlíček, Vojtěch (UTIA-B) RID
    Grim, Jiří (UTIA-B) RID
    Source TitleKybernetika. - : Ústav teorie informace a automatizace AV ČR, v. v. i. - ISSN 0023-5954
    Roč. 47, č. 3 (2011), s. 482-500
    Number of pages19 s.
    Languageeng - English
    CountryCZ - Czech Republic
    KeywordsBTF texture modelling ; discrete distribution mixtures ; Bernoulli mixture ; Gaussian mixture ; multi-spectral texture modelling
    Subject RIVBD - Theory of Information
    R&D Projects1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
    GA102/08/0593 GA ČR - Czech Science Foundation (CSF)
    CEZAV0Z10750506 - UTIA-B (2005-2011)
    UT WOS000293207900011
    EID SCOPUS83455221186
    AnnotationDuring the last decade we have introduced probabilistic mixture models into image modelling area, which present highly atypical and extremely demanding applications for these models. This difficulty arises from the necessity to model tens thousands correlated data simultaneously and to reliably learn such unusually complex mixture models. Presented paper surveys these novel generative colour image models based on multivariate discrete, Gaussian or Bernoulli mixtures, respectively and demonstrates their major advantages and drawbacks on texture modelling applications. Our mixture models are restricted to represent two-dimensional visual information. Thus a measured 3D multispectral texture is spectrally factorized and corresponding multivariate mixture models are further learned from single orthogonal mono-spectral components and used to synthesise and enlarge these mono-spectral factor components.
    WorkplaceInstitute of Information Theory and Automation
    ContactMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Year of Publishing2012
Number of the records: 1  

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