@techreport{TR-IC-09-39,
   number = {IC-09-39},
   author = {Carlos Elias Arminio {Zampieri} and Jorge {Stolfi}},
   title   =   {Image   Retrieval  by  Multi-Scale  Interval  Distance 
                   Estimation},
   month = {October},
   year = {2009},
   institution = {Institute of Computing, University of Campinas},
   note = {In English, 11 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       We  describe a general method for query-by-example retrieval in
       image   collections,   using  interval  arithmetic  to  perform 
       multi-scale  distance  estimation.  The  interval estimates are
       used  to quickly eliminate candidate images at small scales, in
       a   fashion   similar   to  the  branch-and-bound  optimization 
       paradigm.  Experiments  indicate  that  the  method can provide
       significant    speedup    relative    to   exhaustive   search;  
       nevertheless,  the  method  always returns the exact best match
       (and not merely an approximation thereof). The technique allows
       queries  with  a  wide  variety  of image similarity functions,
       without  the  need  to precompute or store specific descriptors
       for each function.
  }
}