@InProceedings{Martinec-CVPR2005,
  IS = { zkontrolovano 06 Dec 2005 },
  UPDATE  = { 2005-09-05 },
  author =       { Martinec, Daniel and Pajdla, Tom{\'a}{\v s} },
  title =        { 3D Reconstruction by Fitting Low-rank Matrices with Missing Data },
  booktitle =    { Proceedings of the Computer Vision and
                   Pattern Recognition conference (CVPR)},
  publisher =    { IEEE Computer Society },
  year =         { 2005 },
  month =        { June },
  day =          { 20-26 },
  venue =        { San Diego, CA, USA },
  project =      { 1ET101210406 },
  keywords =     { structure from motion, missing data, wide base-line stereo, factorization },
  autorship =    { 50-50 },
  annote = { A technique for building consistent 3D reconstructions
    from many wide base-line views based on fitting a low rank matrix
    to a matrix with missing data is presented.  Rank-four submatrices
    of minimal, or slightly larger, size are sampled and spans of
    their columns are combined to constrain a basis of the fitted
    matrix. The error minimized is expressed in terms of the original
    subspaces which leads to a better resistance to noise compared to
    previous methods.  More than 90% of the missing data can be
    handled while finding an acceptable solution efficiently.
    Applications to 3D reconstruction using both affine and
    perspective camera models are shown. For the perspective model, a
    new linear method based on logarithms of positive depths from
    cheirality is introduced to make the depths consistent with an
    overdetermined set of epipolar geometries.  Results are shown for
    scenes and sequences of various types. Many images in open and
    closed sequences in narrow and wide base-line setups are
    reconstructed with reprojection errors around one pixel.  It is
    shown that reconstructed cameras can be used to obtain dense
    reconstructions. },
  book_pages  = { 1224 },
  editor      = { C. Schmid and S. Soatto and C. Tomasi },
  address     = { Los Alamitos, California },
  organization = { {IEEE} Computer Society },
  pages    = { 198-205 },
  volume   = { I },
  isbn     = { 0-7695-2372-2 },
  issn     = { 1063-6919 },
  psurl       = { [Martinec-CVPR2005.pdf], [Martinec-CVPR2005-poster-A4.pdf] },
  prestige    = { important },
}