IS = { zkontrolovano 18 Jan 2009 },
  UPDATE  = { 2008-12-16 },
  author =	 {Guillemaut, Jean-Yves and Drbohlav, Ond{\v r}ej and
                  Illingworth, John and {\v S}{\'a}ra, Radim},
  title =	 {A Maximum Likelihood Surface Normal Estimation Algorithm for
                  Helmholtz Stereopsis},
  year =	 {2008},
  pages =	 {352-359},
  booktitle =	 {VISAPP 2008: Proceedings of the Third International
                  Conference on Computer Vision Theory and Applications },
  editor =	 {Ranchordas, A.N. and Araujo, H.J.},
  publisher =	 {INSTICC-Institute for Systems and Technologies of
                  Information, Control and Communication},
  address =	 {Set{\'u}bal, Portugal},
  isbn =	 {978-989-8111-21-0},
  volume =	 {2},
  book_pages =	 {600},
  month =	 {January},
  day =		 {22-25},
  venue =	 {Funchal, Portugal},
  annote = {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.},
  keywords =	 {computer vision, Helmholtz stereopsis },
  prestige =	 {international},
  project =	 {1ET101210406},