IS = { zkontrolovano 24 Apr 2003 },
  UPDATE  = { 2003-04-11 },
  author =    {Hanton, Karel and Smutn{\'y}, Vladim{\'\i}r and
               Franc, Vojt{\v{e}}ch and Hlav{\'a}{\v c}, V{\'a}clav },
  title =     {Alignment Of Sewerage Inspection Videos for 
               Their Easier Indexing},
  booktitle = {ICVS2003~: Proceedings of the Third International Confernece
               on Vision Systems},
  isbn =      {3-540-00921-3},
  book_pages = {543},
  pages =     {141-150},
  year =      {2003},
  editor =    {Crawley, J.L. and Piater, J.H. and Vincze, M. and Paletta, L.},
  publisher = {Springer-Verlag},
  address =   {Berlin, Germany},
  series = {Lecture Notes in Computer Science},
  volume = {2626},
  month =     {April},
  day =       {1-2},
  venue =     {Graz, Austria},
  authorship ={25-25-25-25},
  project =   {ISAAC IST-2001-33266, LN00B096},
  annote = {The paper describes a new module of the developed robotic
            sewerage inspection system. The sewerage pipe is inspected
            by a remotely controlled inspection tractor equipped by a
            camera head able to rotate and zoom. This contribution
            describes a method and a software solution which allows to
            align the new inspection video and the archived video of
            the same pipe section (typically captured ten years ago).
            The aim of the analysis is to see how the pipe defects
            develop in time.

            The alignment of videos based on correspondences sought in
            images is overambitious. We have chosen the pragmatic
            approach. The text information from odometer which is
            superimposed in the video is automatically located and
            recognized using Optical Character Recognition (OCR)
            technique. The recognized distance from man-hole of the
            pipe allows to align both videos easily. The sewerage
            rehabilitation expert can then use only one remote control
            of the VCR for video positioning.

            This contribution describes the proposed solution, briefly
            mentions its implementation and demonstrate its function on
            practical sewerage inspection videos. However, our indexing
            approach can be used with any videos with superimposed
  keywords =  {video allignmemt, sewerage inspection,
               optical character recogntion},
  psurl =     {[PDF]},