@MastersThesis{Divis-MSc2013,
  IS = { zkontrolovano 08 Aug 2014 },
  UPDATE  = { 2014-07-25 },
author =      {Divi{\v s}, Ji{\v r}{\'\i}},
supervisor =  {Svoboda, Tom{\'a}{\v s}},
title =       {Visual Odometry from Omnidirectional Camera},
school =      {Department of Theoretical Computer Science and Mathematical Logic, Faculty of Mathematics and Physics, Charles University in Prague},
address =     {Prague, Czech Republic},
year =        {2013},
month =       {May},
type =        {MSc Thesis},
pages =       {50},
figures =     {20},
authorship =  {100},
psurl       = {ftp://cmp.felk.cvut.cz/pub/cmp/articles/svoboda/Divis-MSc-2013.pdf},
project =     {FP7-ICT-247870 NIFTi},
annote =      {We present a system that estimates the motion of a
                  robot relying solely on images from onboard
                  omnidirectional camera (visual odometry). Compared
                  to other visual odometry hardware, ours is unusual
                  in utilizing high resolution, low frame-rate (1 to 3
                  Hz) omnidirectional camera mounted on a robot that
                  is propelled using continuous tracks. We focus on
                  high precision estimates in scenes, where objects
                  are far away from the camera. This is achieved by
                  utilizing omnidirectional camera that is able to
                  stabilize the motion estimates between camera frames
                  that are known to be ill-conditioned for narrow
                  field of view cam- eras. We employ feature
                  based-approach for estimation camera motion. Given
                  our hardware, possibly high ammounts of camera
                  rotation between frames can occur. Thus we use
                  techniques of feature matching rather than feature
                  tracking.},
keywords =    {robotics, visual odometry},
}