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Description
  • 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 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 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
  • 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 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 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 (en)
Title
  • Windowpane Detection based on Maximum Aposteriori Probability Labeling
  • Windowpane Detection based on Maximum Aposteriori Probability Labeling (en)
skos:prefLabel
  • Windowpane Detection based on Maximum Aposteriori Probability Labeling
  • Windowpane Detection based on Maximum Aposteriori Probability Labeling (en)
skos:notation
  • RIV/68407700:21230/08:00144353!RIV10-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET101210407), R
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 405795
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/08:00144353
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Markov Random Field; constrained segmentation; probabilistic labeling; structure model (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [332DFA87D938]
http://linked.open...v/mistoKonaniAkce
  • Buffalo
http://linked.open...i/riv/mistoVydani
  • Singapore
http://linked.open...i/riv/nazevZdroje
  • Image Analysis - From Theory to Applications, Proceedings of the 12th International Workshop on Combinatorial Image Analysis (IWCIA'08)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Čech, Jan
  • Šára, Radim
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Research Publishing Services
https://schema.org/isbn
  • 978-3-540-78274-2
http://localhost/t...ganizacniJednotka
  • 21230
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