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  • Helmholtz stereopsis is a relatively recent reconstruction technique which is able to reconstruct scenes with arbitrary and unknown surface reflectance properties. Conventional implementations of the method estimate surface normal direction at each surface point via an eigenanalysis, thereby optimising an algebraic distance. We develop a more physically meaningful radiometric distance whose minimisation is shown to yield a Maximum Likelihood surface normal estimate. The proposed method produces more accurate results than algebraic methods on synthetic imagery and yields excellent reconstruction results on real data. Our analysis explains why, for some imaging configurations, a sub-optimal algebraic distance can yield good results.
  • Helmholtz stereopsis is a relatively recent reconstruction technique which is able to reconstruct scenes with arbitrary and unknown surface reflectance properties. Conventional implementations of the method estimate surface normal direction at each surface point via an eigenanalysis, thereby optimising an algebraic distance. We develop a more physically meaningful radiometric distance whose minimisation is shown to yield a Maximum Likelihood surface normal estimate. The proposed method produces more accurate results than algebraic methods on synthetic imagery and yields excellent reconstruction results on real data. Our analysis explains why, for some imaging configurations, a sub-optimal algebraic distance can yield good results. (en)
  • Helmholtz stereopsis is a relatively recent reconstruction technique which is able to reconstruct scenes with arbitrary and unknown surface reflectance properties. Conventional implementations of the method estimate surface normal direction at each surface point via an eigenanalysis, thereby optimising an algebraic distance. We develop a more physically meaningful radiometric distance whose minimisation is shown to yield a Maximum Likelihood surface normal estimate. The proposed method produces more accurate results than algebraic methods on synthetic imagery and yields excellent reconstruction results on real data. Our analysis explains why, for some imaging configurations, a sub-optimal algebraic distance can yield good results. (cs)
Title
  • A Maximum Likelihood Surface Normal Estimation Algorithm for Helmholtz Stereopsis
  • A Maximum Likelihood Surface Normal Estimation Algorithm for Helmholtz Stereopsis (en)
  • A Maximum Likelihood Surface Normal Estimation Algorithm for Helmholtz Stereopsis (cs)
skos:prefLabel
  • A Maximum Likelihood Surface Normal Estimation Algorithm for Helmholtz Stereopsis
  • A Maximum Likelihood Surface Normal Estimation Algorithm for Helmholtz Stereopsis (en)
  • A Maximum Likelihood Surface Normal Estimation Algorithm for Helmholtz Stereopsis (cs)
skos:notation
  • RIV/68407700:21230/08:03150829!RIV09-AV0-21230___
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
  • 354237
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/08:03150829
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Helmholtz stereopsis; computer vision (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [9F2D4FDDDCF5]
http://linked.open...v/mistoKonaniAkce
  • Funchal, Madeira
http://linked.open...i/riv/mistoVydani
  • Setúbal
http://linked.open...i/riv/nazevZdroje
  • VISAPP 2008: Proceedings of the Third International Conference on Computer Vision Theory and Applications
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
  • Šára, Radim
  • Drbohlav, Ondřej
  • Guillemaut, J.
  • Illingworth, J.
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000256791600059
http://linked.open.../riv/zahajeniAkce
number of pages
http://purl.org/ne...btex#hasPublisher
  • INSTICC Press
https://schema.org/isbn
  • 978-989-8111-21-0
http://localhost/t...ganizacniJednotka
  • 21230
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