IS = { zkontrolovano 20 Jan 2014 },
  UPDATE  = { 2014-01-20 },
  author =       {Albl, {\v C}en{\v e}k},
  supervisor =   {Pajdla, Tom{\'a}{\v s}},
  title =        {Bundle Adjustment -- {PhD} Thesis Proposal},
  institution =  {Center for Machine Perception, K13133 FEE Czech Technical
  address =      {Prague, Czech Republic},
  year =         {2013},
  month =        {9},
  day =          {30},
  type =         {Research Report},
  number =       {CTU--CMP--2013--30},
  issn =         {1213-2365},
  pages =        {34},
  figures =      {9},
  authorship =   {100},
  psurl =        {[Albl-TR-2013-30.pdf]},
  project =      {FP7-SME-2011-285839 De-Montes, TACR TA02011275 ATOM,
  annote =       {Bundle adjustment is an important optimization technique in
                  computer vision. It is a key part of Structure from Motion
                  computation and it is also applied in visual odometry. In
                  this work we first analyze the problem of bundle adjustment
                  and present the state of the art work on this topic,
                  pointing out their advantages and drawbacks. Next, we
                  investigate the open issues of bundle adjustment and ways to
                  address the drawbacks of existing methods. The directions in
                  which improvements can be made are precision, robustness and
                  scalability. Followingly, we present our previous work on
                  bundle adjustment. We show how we improved the precision of
                  the resulting model by incorporating constrains for
                  panoramic camera systems, utilizing their known physical
                  properties. A novel parameterization for bundle adjustment
                  is presented which removes limitations of other frequently
                  used parameterizations. Finally, we emphasize main goals of
                  the thesis which shall focus on designing a superior bundle
                  adjustment method with improved performance over current
                  state of the art methods.},
  keywords =     {Bundle Adjustment, Conjugate Gradients, Camera
                  Parameterization, Rolling Shutter},