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Description
  • Není k dispozici (cs)
  • We introduce a new robust framework suitable for the task of finding correspondences in computer vision. If the problem domain is general enough, the correspondence problem can seldom employ any well-structured prior knowledge. This leads to tasks that have to find maximum cardinality solutions satisfying some weak optimality condition and a set of constraints. To avoid artifacts, robustness is required to cope with decision under occlusion, uncertainty or insufficiency of data and local violations of prior model. The proposed framework is based on a robust modification of graph-theoretic notion known as digraph kernel.
  • We introduce a new robust framework suitable for the task of finding correspondences in computer vision. If the problem domain is general enough, the correspondence problem can seldom employ any well-structured prior knowledge. This leads to tasks that have to find maximum cardinality solutions satisfying some weak optimality condition and a set of constraints. To avoid artifacts, robustness is required to cope with decision under occlusion, uncertainty or insufficiency of data and local violations of prior model. The proposed framework is based on a robust modification of graph-theoretic notion known as digraph kernel. (en)
Title
  • Robust Correspondence Recognition for Computer Vision
  • Není k dispozici (cs)
  • Robust Correspondence Recognition for Computer Vision (en)
skos:prefLabel
  • Robust Correspondence Recognition for Computer Vision
  • Není k dispozici (cs)
  • Robust Correspondence Recognition for Computer Vision (en)
skos:notation
  • RIV/68407700:21230/06:03124635!RIV07-AV0-21230___
http://linked.open.../vavai/riv/strany
  • 119 ; 131
http://linked.open...avai/riv/aktivita
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  • P(1ET101210406)
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
  • 497763
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/06:03124635
http://linked.open...riv/jazykVysledku
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  • computer vision; digraph kernel; robust matching (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [15F2EF91F2A7]
http://linked.open...v/mistoKonaniAkce
  • Rome
http://linked.open...i/riv/mistoVydani
  • Heidelberg
http://linked.open...i/riv/nazevZdroje
  • COMPSTAT 2006: Proceedings in Computational Statistics of 17th ERS-IASC Symposium
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http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Šára, Radim
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
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  • Physica-verlag
https://schema.org/isbn
  • 3-7908-1708-2
http://localhost/t...ganizacniJednotka
  • 21230
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