Windowpane Detection based on Maximum Aposteriori Labeling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F07%3A00218868" target="_blank" >RIV/68407700:21230/07:00218868 - 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 Labeling

Popis výsledku v původním jazyce

Segmentation of windowpanes in the images of facades is formulated as a task of maximum aposteriori labeling. Assuming orthographic rectification of the building facade, the windowpanes are always axis-parallel rectangles of relatively low variability inappearance. Every image pixel has one of 10 possible labels, and the adjacent pixels are interconnected via links which defines allowed label configuration, such that the labels are forced to form a set of non-overlapping rectangles. The task of findingthe most probable 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 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 does

Název v anglickém jazyce

Windowpane Detection based on Maximum Aposteriori Labeling

Popis výsledku anglicky

Segmentation of windowpanes in the images of facades is formulated as a task of maximum aposteriori labeling. Assuming orthographic rectification of the building facade, the windowpanes are always axis-parallel rectangles of relatively low variability inappearance. Every image pixel has one of 10 possible labels, and the adjacent pixels are interconnected via links which defines allowed label configuration, such that the labels are forced to form a set of non-overlapping rectangles. The task of findingthe most probable 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 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 does

Druh

V_souhrn - Souhrnná výzkumná zpráva

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2007

Kód důvěrnosti údajů

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

Počet stran výsledku

12

Místo vydání

Praha

Název nakladatele resp. objednatele

Center for Machine Perception, K13133 FEE, Czech Technical University

Verze

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