IS = { zkontrolovano 24 Apr 2003 },
  UPDATE  = { 2003-04-07 },
author =      {K{\v r}{\'\i }{\v z}ek, Pavel and Smutn{\'y}, Vladim{\'\i }r},
language =    {czech},
title =       {Soulep panoramatick{\'y}ch sn{\'\i }mk{\accent23u}},
e_title =     {Mosaicing panoramic images},
institution = {Center for Machine Perception,  K333 FEE
               Czech Technical University},
address =     {Prague, Czech Republic},
year =        {2003},
month =       {April},
type =        {Research Report},
number =      {{CTU--CMP--2003--07}},
issn =        {1213-2365},
pages =       {63},
figures =     {52},
authorship =  {80-20},
psurl       = {[Krizek-TR-2003
project =     {IST-2001-33266, MSM 212300013, GACR 102/01/0971, CTU 0209513},
annote =      {We tried to reconstruct the pipeline inner surface texture
               like one ``infinite'' image unwarped into the plane by
               mosaicing the sequence of the panoramic images captured by
               an omnidirectional camera during sewerage system
               inspection. At first we performed a~geometric correction of
               the mirror in the camera image. Next, we defined nonlinear
               transformation for obtaining the uniform unwarped panoramic
               images when the camera was parallely displaced from the
               pipeline axis. To connect two neighbouring panoramic images
               the correlation was used. To speed up the algorithm we used
               pyramidal data structures. Since our inspection robots
               light did not shine uniformly in the whole omnidirectional
               camera view angle, we had to do brightness corrections
               before the correlation. At first, the algorithm was
               developed in the laboratory on two clayware sewerage pipes.
               Then it was tested in the real sewerage pipeline, when the
               inspection robot covered a~distance of approximately 30 m.},
keywords =    {Omnidirectional camera, catadioptric sensor, mosaicing, 
               panoramic images, correlation,  M-pyramids, 
               hierarchical data structures},