@InProceedings{Cornelius-SMVP2004,
  IS = { zkontrolovano 04 Mar 2005 },
  UPDATE  = { 2004-12-08 },
author =      {Cornelius, Hugo and {\v S}{\'a}ra, Radim and Martinec, Daniel
               and Pajdla, Tom{\'a}{\v s} and Chum, Ond{\v r}ej and 
               Matas, Ji{\v r}{\'\i}},
title =       {Towards Complete Free-Form Reconstruction of Complex {3D}
               Scenes from an Unordered Set of Uncalibrated Images},
booktitle =   {Proc ECCV Workshop Statistical Methods in Video Processing},
book_pages =  {199},
isbn =        {3-540-23989-8},
issn =        {0302-9743},
publisher   = {Springer-Verlag},
address     = {Heidelberg, Germany},
editor      = {Comaniciu, D. and Mester, R. and Kanatani, K.},
pages =       {1--12},
year =        {2004},
month =       {May},
day =         {16},
venue =       {Prague, Czech Republic},
project  =    {STINT Dur IG2003-2 062, 1ET101210406, BeNoGo IST-2001-39184},
keywords =    {reconstruction, structure from motion, outlier detection, 
               wide base-line stereo, dense matching },
annote = { This paper describes a method for accurate dense
   reconstruction of a complex scene from a small set of
   high-resolution unorganized still images taken by a hand-held
   digital camera. A fully automatic data processing pipeline is
   proposed.  Highly discriminative features are first detected in all
   images.  Correspondences are then found in all image pairs by
   wide-baseline stereo matching and used in a scene structure and
   camera reconstruction step that can cope with occlusion and
   outliers.  Image pairs suitable for dense matching are
   automatically selected, rectified and used in dense binocular
   matching. The dense point cloud obtained as the union of all
   pairwise reconstructions is fused by local approximation using
   oriented geometric primitives. For texturing, every primitive is
   mapped on the image with the best resolution.
 
   The global structure reconstruction in the first step allows us to
   work with an unorganized set of images and to avoid error
   accumulation. By using object-centered geometric primitives we are
   able to preserve the flexibility of the method to describe complex
   free-form structures, preserve the possibility to build the dense
   model in an incremental way, and to retain the possibility to
   refine the cameras and the dense model by bundle adjustment.
   Results are demonstrated on partial models of a circular church and
   a Henri de Miller's sculpture. We observed spatial resolution in
   the range of centimeters on objects of about 20 m in size. },
volume      = { LNCS 3247 },
authorship  = { 25-20-25-10-10-10 },
psurl       = { [Cornelius-SMVP2004.pdf] },
}