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Description
  • Keypoint matching in images of indoor scenes traditionally employs features like SIFT, GIST and HOG. While features work very well for two images related to each other by small camera transformations, we commonly observe a drop in performance for patches representing scene elements visualized from a very different perspective. Since increasing the space of considered local transformations for feature matching decreases their discriminative abilities, we propose a more global approach inspired by the recent success of monocular scene understanding. In particular we propose to reconstruct a box-like model of the scene from every single image and use it to rectify images before matching. We show that a monocular scene model reconstruction and rectification preceding standard feature matching significantly improves keypoint matching and dramatic ally improves reconstruction of difficult indoor scenes.
  • Keypoint matching in images of indoor scenes traditionally employs features like SIFT, GIST and HOG. While features work very well for two images related to each other by small camera transformations, we commonly observe a drop in performance for patches representing scene elements visualized from a very different perspective. Since increasing the space of considered local transformations for feature matching decreases their discriminative abilities, we propose a more global approach inspired by the recent success of monocular scene understanding. In particular we propose to reconstruct a box-like model of the scene from every single image and use it to rectify images before matching. We show that a monocular scene model reconstruction and rectification preceding standard feature matching significantly improves keypoint matching and dramatic ally improves reconstruction of difficult indoor scenes. (en)
Title
  • MatchBox: Indoor Image Matching via Box-like Scene Estimation
  • MatchBox: Indoor Image Matching via Box-like Scene Estimation (en)
skos:prefLabel
  • MatchBox: Indoor Image Matching via Box-like Scene Estimation
  • MatchBox: Indoor Image Matching via Box-like Scene Estimation (en)
skos:notation
  • RIV/68407700:21230/14:00223267!RIV15-MSM-21230___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(TA02011275), 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
  • 27529
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/14:00223267
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • image matching; indoor; scene layout (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [B87C85DB09C7]
http://linked.open...v/mistoKonaniAkce
  • Tokyo
http://linked.open...i/riv/mistoVydani
  • Los Alamitos
http://linked.open...i/riv/nazevZdroje
  • 3DV 2014: International Conference on 3D Vision
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
  • Pajdla, Tomáš
  • Šrajer, Filip
  • Pollefeys, M.
  • Schwing, A.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society Press
https://schema.org/isbn
  • 978-1-4799-7001-8
http://localhost/t...ganizacniJednotka
  • 21230
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