About: Texture Recognition using Robust Markovian Features

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Texture Recognition using Robust Markovian Features Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	We provide a thorough experimental evaluation of several state-of-the-art textural features on four representative and extensive image data/-bases. Each of the experimental textural databases ALOT, Bonn BTF, UEA Uncalibrated, and KTH-TIPS2 aims at specific part of realistic acquisition conditions of surface materials represented as multispectral textures. The extensive experimental evaluation proves the outstanding reliable and robust performance of efficient Markovian textural features analytically derived from a wide-sense Markov random field causal model. These features systematically outperform leading Gabor, Opponent Gabor, LBP, and LBP-HF alternatives. Moreover, they even allow successful recognition of arbitrary illuminated samples using a single training image per material. Our features are successfully applied also for the recent most advanced textural representation in the form of 7-dimensional Bidirectional Texture Function (BTF). We provide a thorough experimental evaluation of several state-of-the-art textural features on four representative and extensive image data/-bases. Each of the experimental textural databases ALOT, Bonn BTF, UEA Uncalibrated, and KTH-TIPS2 aims at specific part of realistic acquisition conditions of surface materials represented as multispectral textures. The extensive experimental evaluation proves the outstanding reliable and robust performance of efficient Markovian textural features analytically derived from a wide-sense Markov random field causal model. These features systematically outperform leading Gabor, Opponent Gabor, LBP, and LBP-HF alternatives. Moreover, they even allow successful recognition of arbitrary illuminated samples using a single training image per material. Our features are successfully applied also for the recent most advanced textural representation in the form of 7-dimensional Bidirectional Texture Function (BTF). (en)
Title	Texture Recognition using Robust Markovian Features Texture Recognition using Robust Markovian Features (en)
skos:prefLabel	Texture Recognition using Robust Markovian Features Texture Recognition using Robust Markovian Features (en)
skos:notation	RIV/67985556:_____/12:00380288!RIV13-MSM-67985556
http://linked.open...avai/predkladatel	Ústav teorie informace a automatizace AV ČR, v. v. i.
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(1M0572), P(GA102/08/0593), P(GAP103/11/0335)
http://linked.open...vai/riv/dodaniDat	2013
http://linked.open...aciTvurceVysledku	Vácha, Pavel Haindl, Michal
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
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	174151
http://linked.open...ai/riv/idVysledku	RIV/67985556:_____/12:00380288
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	texture recognition; illumination invariance; Markov random fields; Bidirectional Texture Function; textural databases (en)
http://linked.open.../riv/klicoveSlovo	illumination invariance textural databases texture recognition Markov random fields Bidirectional Texture Function
http://linked.open...ontrolniKodProRIV	[1CBBABE89424]
http://linked.open...v/mistoKonaniAkce	Pisa
http://linked.open...i/riv/mistoVydani	Berlin
http://linked.open...i/riv/nazevZdroje	Computational Intelligence for Multimedia Understanding
http://linked.open...in/vavai/riv/obor	BD
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (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 Vácha, Pavel
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2011-12-13 (xsd:date)
number of pages	12 (xsd:int)
http://bibframe.org/vocab/doi	10.1007/978-3-642-32436-9_11
http://purl.org/ne...btex#hasPublisher	Springer-Verlag
https://schema.org/isbn	978-3-642-32435-2
is http://linked.open...avai/riv/vysledek of	Texture Recognition using Robust Markovian Features

Faceted Search & Find service v1.16.116 as of Feb 22 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3239 as of Feb 22 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 82 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software