@PhDThesis{Bakstein-TR-2006-09,
  IS = { zkontrolovano 18 Jan 2008 },
  UPDATE =       { 2006-10-31 },
  author =       {Bakstein, Hynek},
  supervisor =   {Hlav{\'a}{\v c}, V{\' a}clav},
  title =        {Non-central Cameras for {3D} Reconstruction},
  school =       {Center for Machine Perception, K13133 FEE Czech Technical
                  University},
  address =      {Prague, Czech Republic},
  year =         {2006},
  month =        {March},
  day =          {22},
  type =         {{PhD Thesis CTU--CMP--2006--09}},
  issn =         {1213-2365},
  pages =        {114},
  figures =      {87},
  authorship =   {100},
  psurl =        {[Bakstein-TR-2006-09.pdf]},
  project =      {GACR 102/01/0971, IST-1999-29017, 
                  MSMT KONTAKT 2001/09, MSMT 212300013, 
                  EIST-2001-39184, Dur IG2003-2 062, MSM6840770013},
  annote = {In this thesis, we study one example of a non-central
    mosaic camera, the $360\times360$ mosaic camera, where an
    omnidirectional camera moves on a circular path. We focus on
    geometry of this camera and we show that we can consider different
    levels of complexity of the model. The simplest model has only a
    single parameter and a 3D reconstruction in an uncalibrated case
    results in a similarity reconstruction of the scene. However, more
    complex model has to be used in many practical situations. We
    present a bundle adjustment procedure for recovery of its
    parameters. The thesis then describes a practical realization of
    the $360\times350$ mosaic camera employing a fish eye lens instead
    of a mirror, as it was previously suggested by Nayar in 2000. We
    overview calibration methods for fish eye lenses and propose a
    novel approach based on theoretical projection functions. We show
    experimentally, that this approach provides higher robustness with
    sufficient precision compared to traditional polynomial fitting
    methods and the division model. In the final chapter of this
    thesis, we introduce the concept of an omnidirectional image-based
    rendering (IBR) with X-slits geometry. We extend the concept of
    image volumes to omnidirectional image volumes and we show that
    depth information obtained by the model of the $360\times360$
    mosaic camera can be used to reduce the number of images in the
    volume while maintaining high visual fidelity of the IBR
    images. To conclude with some practical application, we
    demonstrate that X-slits IBR can be used in image-based robot
    localization.},
  keywords =     {non-central cameras, omnidirectional vision, fish eye,
                  calibration, image-based rendering},
}