IS = { zkontrolovano 14 Dec 2007 },
  UPDATE  = { 2007-10-08 },
  author =      {Havlena, Michal},
  title =       {Automated City Modeling from Omnidirectional 
                 Image Sequences -- {PhD} Thesis Proposal},
  institution = {Center for Machine Perception, 
                 K13133 FEE Czech Technical University},
  address =     {Prague, Czech Republic},
  year =        {2007},
  month =       {September},
  type =        {Research Report},
  number =      {CTU--CMP--2007--21},
  issn =        {1213-2365},
  pages =       {37},
  figures =     {19},
  authorship =  {100},
  psurl =       {[Havlena-TR-2007-21.pdf]},
  project =     {FP6-IST-027787 DIRAC, GACR 201/07/1136, CTU0705913},
  annote = {City models are needed in many areas of human activities
    including urban planning, virtual reality, and architecture
    preservation. Aerial, ground level, and omnidirectional city
    modeling techniques are compared and their main advantages and
    disadvantages are presented. We also show several city modeling
    systems and address their novelties as well as their
    limitations. Next, we present our previous work dealing with a
    step towards a 3D reconstruction system for city modeling from
    omnidirectional video sequences using structure from motion
    together with stereo constraints. We concentrate on two
    issues. First, we show how the tracking and reconstruction
    paradigm were adapted to use omnidirectional images taken by
    lenses with 180 degrees field of view. Secondly, we compare the
    results of the reconstruction using additional stereo constraints
    to the results when these constraints are not used. Performance of
    the system is demonstrated on a sequence of 870 images acquired
    while driving in a city. Finally, scalability and other open
    problems of city modeling from image sequences are presented
    together with problems which have been solved already. The main
    goal of the thesis is to design a scalable modeling and
    localization system consisting of two mutually interacting
    modules: a structure from motion (SfM) module and a near identical
    image detection (NIID) module.},
  keywords =    {Structure from Motion, City Modeling, Omnidirectional Vision},
  comment =     {PhD Thesis Proposal},