A Weak Structure Model for Regular Pattern Recognition Applied to Facade Images

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00187553" target="_blank" >RIV/68407700:21230/11:00187553 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
A Weak Structure Model for Regular Pattern Recognition Applied to Facade Images
Original language description
We propose a novel method for recognition of structured images and demonstrate it on detection of windows in facade images. Given an ability to obtain local low-level data evidence on primitive elements of a structure (like window in a facade image), wedetermine their most probable number, attribute values (location, size) and neighborhood relation. The embedded structure is weakly modeled by pair-wise attribute constraints, which allow structure and attribute constraints to mutually support each other. We use a very general framework of reversible jump MCMC, which allows simple implementation of a specific structure model and plug-in of almost arbitrary element classifiers. The MC controls the classifier by prescribing it 'where to look', without wasting too much time on unpromising locations. We have chosen the domain of window recognition in facade images to demonstrate that the result is an efficient algorithm achieving performance of other strongly informed methods for regular st
Czech name
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Czech description
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Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
ACCV 2010: Proceedings of the 10th Asian Conference on Computer Vision, Part I
ISBN
978-3-642-19314-9
ISSN
0302-9743
e-ISSN
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Number of pages
14
Pages from-to
450-463
Publisher name
Springer
Place of publication
Berlin
Event location
Queenstown
Event date
Nov 8, 2010
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000296690900035

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