@InProceedings{Martinec-CVPR2003,
  IS = { zkontrolovano 25 Mar 2004 },
  UPDATE  = { 2003-03-04 },
  author =       { Martinec, Daniel and Pajdla, Tom{\'a}{\v s} },
  title =        { Line Reconstruction from Many Perspective Images by 
                   Factorization },
  booktitle =   { CVPR 2003: Proceedings of the 2003 {IEEE} Computer
                  Society Conference on Computer Vision and Pattern
                  Recognition },
  publisher =    { IEEE Computer Society },
  year =         { 2003 },
  month =        { June },
  day =          { 16-22 },
  venue =        { Madison,  Wisconsin, USA },
  project =      { CTU 0209313, MSMT KONTAKT 2001/019, GACR 102/01/0971, 
                   GACR 102/00/1679, IST-2001-39184, Aktion 34p24, 
                   MSM 212300013 },
  keywords =     { line reconstruction, structure from motion, factorization },
  autorship =    { 50-50 },
  annote = { This paper brings a new method for line reconstruction
  from many perspective images by factorization of a matrix containing
  line correspondences.  No point correspondences are used. We
  formulate the reconstruction from line correspondences in the
  language of Pluecker line coordinates. The reconstruction is posed
  as the factorization of 3m x n matrix S into the product S = Q L of
  3m x 6 projection matrix Q and 6 x n line matrix L, both satisfying
  Klein identities. The matrix S contains coordinates of lines
  detected in perspective images.  Similarly to reconstruction from
  point correspondences in perspective images, the matrix S has to be
  properly rescaled before it can be factorized.  We propose a scaling
  of image line coordinates based on trifocal tensors that is
  analogical to the scaling proposed by Sturm and Triggs for
  points. We propose an SVD based factorization enforcing Klein
  identities on Q and L in a noise-free situation. We show experiments
  on real data that suggest that a good reconstruction may be obtained
  even if data is noisy and the identities are not enforced exactly. },
book_pages  = { 865 },
editor      = { Martin, Danielle },
address     = { Los Alamitos, USA },
organization = { {IEEE} Computer Society },
pages       = { 497-502 },
volume      = { I },
isbn        = { 0-7695-1900-8 },
psurl       = { [Martinec-CVPR2003.pdf], [Martinec-CVPR2003-poster-a4.ps.gz] },
prestige    = { important },
}