About: Joint Non-rigid Motion Estimation and Segmentation     Goto   Sponge   NotDistinct   Permalink

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Description
  • Není k dispozici (cs)
  • Usually, object segmentation and motion estimation are considered (and modelled) as different tasks. For motion estimation this leads to problems arising especially at the boundary of an object moving in front of another if e.g. prior assumptions about continuity of the motion field are made. Thus we expect that a good segmentation will improve the motion estimation and vice versa. To demonstrate this, we consider the simple task of joint segmentation and motion estimation of an arbitrary (non-rigid) object moving in front of a still background. We propose a statistical model which represents the moving object as a triangular mesh of pairs of corresponding points and introduce an provably correct iterative scheme, which simultaneously finds the optimal segmentation and corresponding motion field.
  • Usually, object segmentation and motion estimation are considered (and modelled) as different tasks. For motion estimation this leads to problems arising especially at the boundary of an object moving in front of another if e.g. prior assumptions about continuity of the motion field are made. Thus we expect that a good segmentation will improve the motion estimation and vice versa. To demonstrate this, we consider the simple task of joint segmentation and motion estimation of an arbitrary (non-rigid) object moving in front of a still background. We propose a statistical model which represents the moving object as a triangular mesh of pairs of corresponding points and introduce an provably correct iterative scheme, which simultaneously finds the optimal segmentation and corresponding motion field. (en)
Title
  • Není k dispozici (cs)
  • Joint Non-rigid Motion Estimation and Segmentation
  • Joint Non-rigid Motion Estimation and Segmentation (en)
skos:prefLabel
  • Není k dispozici (cs)
  • Joint Non-rigid Motion Estimation and Segmentation
  • Joint Non-rigid Motion Estimation and Segmentation (en)
skos:notation
  • RIV/68407700:21230/04:03103450!RIV/2005/AV0/212305/N
http://linked.open.../vavai/riv/strany
  • 631 ; 638
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • 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
  • 569508
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/04:03103450
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Computer vision; Markov random fields; motion estimation; segmentation (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [B931F0EDE44E]
http://linked.open...v/mistoKonaniAkce
  • Auckland
http://linked.open...i/riv/mistoVydani
  • Heidelberg
http://linked.open...i/riv/nazevZdroje
  • IWCIA '04: Proceedings 10th International Workshop on Combinatorial Image Analysis
http://linked.open...in/vavai/riv/obor
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http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Šára, Radim
  • Flach, B.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
http://localhost/t...ganizacniJednotka
  • 21230
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