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Windowpane Detection based on Maximum Aposteriori Labeling

The result's identifiers

  • Result code in 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>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Windowpane Detection based on Maximum Aposteriori Labeling

  • Original language description

    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

  • Czech name

  • Czech description

Classification

  • Type

    V<sub>souhrn</sub> - Summary research report

  • CEP classification

    JD - Use of computers, robotics and its application

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    R - Projekt Ramcoveho programu EK

Others

  • Publication year

    2007

  • Confidentiality

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

Data specific for result type

  • Number of pages

    12

  • Place of publication

    Praha

  • Publisher/client name

    Center for Machine Perception, K13133 FEE, Czech Technical University

  • Version