Two Compound Random Field Texture Models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00471592" target="_blank" >RIV/67985556:_____/17:00471592 - isvavai.cz</a>
Alternative codes found
RIV/61384399:31160/17:00051937
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-52277-7_6" target="_blank" >http://dx.doi.org/10.1007/978-3-319-52277-7_6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-52277-7_6" target="_blank" >10.1007/978-3-319-52277-7_6</a>
Alternative languages
Result language
angličtina
Original language name
Two Compound Random Field Texture Models
Original language description
Two novel models for texture representation using parametric compound random field models are introduced. These models consist of a set of several sub-models each having different characteristics along with an underlying structure model which controls transitions between them. The structure model is a two-dimensional probabilistic mixture model either of the Bernoulli or Gaussian mixture type. Local textures are modeled using the fully multispectral three-dimensional causal auto-regressive models. Both presented compound random field models allow to reproduce, compress, edit, and enlarge a given measured color, multispectral, or bidirectional texture function (BTF) texture so that ideally both measured and synthetic textures are visually indiscernible.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/GA14-10911S" target="_blank" >GA14-10911S: Mathematical modeling of surface material appearance</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 21st Iberoamerican Congress, CIARP 2016
ISBN
978-3-319-52276-0
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
44-51
Publisher name
Springer International Publishing
Place of publication
Cham
Event location
Lima
Event date
Nov 8, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000418399200006