@techreport{TR-IC-09-24,
   number = {IC-09-24},
   author  = {Jurandy Almeida and Rodrigo Minetto and Tiago A. Almeida
                   and Ricardo da S. Torres and Neucimar J. Leite},
   title  =  {Robust  Estimation  of  Camera Motion using Optical Flow
                   Models},
   month = {July},
   year = {2009},
   institution = {Institute of Computing, University of Campinas},
   note = {In English, 13 pages plus errata.
    \par\selectlanguage{english}\textbf{Abstract}
       The  estimation  of  camera motion is one of the most important
       aspects   for   video   processing,   analysis,  indexing,  and 
       retrieval.  Most  of  existing  techniques  to  estimate camera
       motion  are  based  on optical flow methods in the uncompressed
       domain.  However,  to decode and to analyze a video sequence is
       extremely   time-consuming.   Since   video  data  are  usually 
       available  in MPEG-compressed form, it is desirable to directly
       process  video  material  without  decoding.  In this paper, we
       present  a  novel approach for estimating camera motion in MPEG
       video sequences. Our technique relies on linear combinations of
       optical   flow   models.  The  proposed  method  first  creates 
       prototypes   of  optical  flow,  and  then  performs  a  linear 
       decomposition  on  the  MPEG  motion  vectors, which is used to
       estimate  the camera parameters. Experiments on synthesized and
       real-world   video  clips  show  that  our  technique  is  more 
       effective  than  the state-of-the-art approaches for estimating
       camera motion in MPEG video sequences.
  }
}