IS = { zkontrolovano 24 Jan 2014 },
  UPDATE  = { 2013-09-19 },
  author =       {Sychrovsk{\'y}, Ond{\v r}ej and Matou{\v s}ek, Martin and 
                  {\v S}{\'a}ra, Radim},
  title =        {{FPGA}-accelerated sliding window classifier with structured features},
  institution =  {Center for Machine Perception, Czech Technical University},
  address =      {Prague, Czech Republic},
  year =         {2013},
  month =        {June},
  type =         {Research Report},
  number =       {CTU--CMP--2013--16},
  issn =         {1213-2365},
  pages =        { 13 },
  psurl =        {[Sychrovsky-TR-2013-16.pdf]},
  project =      {FP7-ICT-246587 INTERACTIVE},
  annote = { There are certain classification tasks in computer vision
    that require the classifier response to be computed in every pixel
    of an image. When combined with large, complex features, it
    becomes really challenging to implement such a classifier on a
    standard PC architecture and achieve real-time performance. We
    present an implementation of a car wheel classifier response
    computation pipeline on an FPGA, built as an instantiation of a
    generic classification system. An interesting optimization problem
    concerning processing time and classification performance is
    addressed. Our implementation is running in real-time as a part of
    a more complex system based on car-detection in video data. This
    is a long version of our paper presented at the $23^{rd}$
    International Conference on Field Programmable Logic and
    Applications, 2013, Porto, Portugal. },
  keywords = { FPGA, AdaBoost, sliding window, classifier, real-time },