IS = { zkontrolovano 15 Jan 2013 },
  UPDATE  = { 2012-03-02 },
  author =      {Sedl{\'a}{\v c}ek, Filip and Svoboda, Tom{\'a}{\v s}},
  title =       {Filtering False Positives of a Visual Object Detector using {3D} Laser Data},
  institution = {Center for Machine Perception, K13133 FEE
                 Czech Technical University},
  address =     {Prague, Czech Republic},
  year =        {2012},
  month =       {February},
  type =        {Research Report},
  number =      {CTU--CMP--2012--04},
  issn =        {1213-2365},
  pages =       {17},
  figures =     {7},
  authorship =  {50-50},
  psurl = {[Sedlacek-TR-2012-04.pdf]},
  project =     {FP7-ICT-247870 NIFTi, SGS11/125/OHK3/2T/13},
  annote = {The paper describes implementation of a simple yet very
    efficient filtering step for object detection. The filter is
    implemented in ROS middle-ware and applied on a mobile
    robot. Visual detector tuned to achieve high recall yields many
    false positive detections. However, many false positives annoy the
    human operator. We suggest to apply 3D data from a rotation laser
    range-finder and the expected object dimension in order to discard
    the false detections.  Using a projection of the 3D points into
    the image, the visual detection rectangle delimits a subset of the
    3D points supposedly belonging to the target object. From that 3D
    points subset, we estimate the object distance. We compare the
    distance/size ratio and discard the tentative detection if it does
    not match the expectation. },
  keywords =    {object detection, depth data},