Windowpane Detection based on Maximum Aposteriori Probability Labeling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A00144353" target="_blank" >RIV/68407700:21230/08:00144353 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Windowpane Detection based on Maximum Aposteriori Probability Labeling

Popis výsledku v původním jazyce

Segmentation of windowpanes in images of building facades is formulated as a task of maximum aposteriori probability labeling. Assuming orthographic rectification of the image, the windowpanes are always axis-parallel rectangles of relatively low variability in appearance. Every image pixel has one of 10 possible labels, and the labels in adjacent pixels are constrained by allowed label configuration, such that the image labels represent a set of non-overlapping rectangles. The task of finding the mostprobable labeling of a given image leads to NP-hard discrete optimization problem. However, we find an approximate solution using a general solver suitable for such problems and we obtain promising results which we demonstrate on several experiments. Substantial difference between the presented paper and the state-of-the-art papers on segmentation based on Markov Random Fields is that we have a strong structure model, forcing the labels to form rectangles, while other methods do not mode

Název v anglickém jazyce

Windowpane Detection based on Maximum Aposteriori Probability Labeling

Popis výsledku anglicky

Segmentation of windowpanes in images of building facades is formulated as a task of maximum aposteriori probability labeling. Assuming orthographic rectification of the image, the windowpanes are always axis-parallel rectangles of relatively low variability in appearance. Every image pixel has one of 10 possible labels, and the labels in adjacent pixels are constrained by allowed label configuration, such that the image labels represent a set of non-overlapping rectangles. The task of finding the mostprobable labeling of a given image leads to NP-hard discrete optimization problem. However, we find an approximate solution using a general solver suitable for such problems and we obtain promising results which we demonstrate on several experiments. Substantial difference between the presented paper and the state-of-the-art papers on segmentation based on Markov Random Fields is that we have a strong structure model, forcing the labels to form rectangles, while other methods do not mode

Druh

D - Stať ve sborníku

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

<a href="/cs/project/1ET101210407" target="_blank" >1ET101210407: Multikamerový systém pro modelování a rozpoznávání událostí</a><br>

Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2008

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Image Analysis - From Theory to Applications, Proceedings of the 12th International Workshop on Combinatorial Image Analysis (IWCIA'08)

ISBN

978-3-540-78274-2

ISSN

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e-ISSN

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Počet stran výsledku

9

Strana od-do

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Název nakladatele

Research Publishing Services

Místo vydání

Singapore

Místo konání akce

Buffalo

Datum konání akce

7. 4. 2008

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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