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Description
  • This paper presents a segmentation based multiview stereo reconstruction method. We address (i) dealing with uninformative texture in very homogeneous image areas and (ii) processing of large images in affordable time. To avoid searching for optimal surface position and orientation based on uninformative texture, we (over)segment images into segments of low variation of color and intensity and use each segment to generate a candidate 3D planar patch explaining the underlying 3D surface. Every point of the surface is explained by multiple candidate patches generated from image segments from different images. Observing that the correctly reconstructed surface is consistently generated from different images, the candidates that do not have consistent support by other candidates from other images are rejected. This approach leads to stable and good results.
  • This paper presents a segmentation based multiview stereo reconstruction method. We address (i) dealing with uninformative texture in very homogeneous image areas and (ii) processing of large images in affordable time. To avoid searching for optimal surface position and orientation based on uninformative texture, we (over)segment images into segments of low variation of color and intensity and use each segment to generate a candidate 3D planar patch explaining the underlying 3D surface. Every point of the surface is explained by multiple candidate patches generated from image segments from different images. Observing that the correctly reconstructed surface is consistently generated from different images, the candidates that do not have consistent support by other candidates from other images are rejected. This approach leads to stable and good results. (en)
Title
  • Segmentation Based Multi-View Stereo
  • Segmentation Based Multi-View Stereo (en)
skos:prefLabel
  • Segmentation Based Multi-View Stereo
  • Segmentation Based Multi-View Stereo (en)
skos:notation
  • RIV/68407700:21230/09:00163118!RIV10-MSM-21230___
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
  • 340549
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/09:00163118
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • computer vision; surface reconstruction (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [E908D27EFEA0]
http://linked.open...v/mistoKonaniAkce
  • Eibiswald
http://linked.open...i/riv/mistoVydani
  • Wien
http://linked.open...i/riv/nazevZdroje
  • CVWW 2009: Computer Vision Winter Workshop 2009
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Jančošek, Michal
  • Pajdla, Tomáš
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • Pattern Recognition & Image Processing Group, Vienna University of Technology
https://schema.org/isbn
  • 978-3-200-01390-2
http://localhost/t...ganizacniJednotka
  • 21230
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