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Description
  • In this paper, a new algorithm for bimodal depth segmentation is presented. The method separates the background and the planar objects of arbitrary shapes lying in a certain height above the background using the information from the stereo image pair (more exactly, the background and the objects may lie on two distinct general planes). The problem is solved as a problem of minimising a functional. A new functional is proposed for this purpose that is based on evaluating the mismatches between the images, which contrasts with the usual approaches that evaluate the matches. We explain the motivation for such an approach. The minimisation is carried out by making use of the Euler-Lagrange equation and the level-set function. The experiments show the promising results on noisy synthetic images as well as on real-life images. An example of the practical application of the method is also presented.
  • In this paper, a new algorithm for bimodal depth segmentation is presented. The method separates the background and the planar objects of arbitrary shapes lying in a certain height above the background using the information from the stereo image pair (more exactly, the background and the objects may lie on two distinct general planes). The problem is solved as a problem of minimising a functional. A new functional is proposed for this purpose that is based on evaluating the mismatches between the images, which contrasts with the usual approaches that evaluate the matches. We explain the motivation for such an approach. The minimisation is carried out by making use of the Euler-Lagrange equation and the level-set function. The experiments show the promising results on noisy synthetic images as well as on real-life images. An example of the practical application of the method is also presented. (en)
Title
  • A new level-set based algorithm for bimodal depth segmentation
  • A new level-set based algorithm for bimodal depth segmentation (en)
skos:prefLabel
  • A new level-set based algorithm for bimodal depth segmentation
  • A new level-set based algorithm for bimodal depth segmentation (en)
skos:notation
  • RIV/61989100:27240/12:86084672!RIV13-MSM-27240___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • S
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
  • 120370
http://linked.open...ai/riv/idVysledku
  • RIV/61989100:27240/12:86084672
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • stereo correspondence; level set; image segmentation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [F4AD7EDFA4D5]
http://linked.open...v/mistoKonaniAkce
  • Brno
http://linked.open...i/riv/mistoVydani
  • Berlin
http://linked.open...i/riv/nazevZdroje
  • Lecture Notes in Computer Science. Volume 7517
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Gaura, Jan
  • Krumnikl, Michal
  • Sojka, Eduard
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-642-33140-4_20
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-642-33139-8
http://localhost/t...ganizacniJednotka
  • 27240
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