@BachelorThesis{Derner-TR-2012-10,
  IS = { zkontrolovano 16 Jan 2014 },
  UPDATE  = { 2012-10-01 },
author =      {Derner, Erik},
supervisor =  {Svoboda, Tom{\'a}{\v s}},
title =       {Car Detection on a Mobile Robot by Fusing Visual and {3D} 
Lidar Data},
school =      {Center for Machine Perception, K13133 FEE
                Czech Technical University},
address =     {Prague, Czech Republic},
year =        {2012},
month =       {June},
day =         {27},
type =        {{BSc Thesis CTU--CMP--2012--10}},
issn =        {1213-2365},
pages =       {50},
figures =     {20},
authorship =  {100},
psurl       = {[Derner-TR-2012-10.pdf]},
project =     {FP7-ICT-247870 NIFTi, GACR P103/10/1585},
annote =      {In this work, we focus on the combination of visual and
    depth data in object detection. We propose an algorithm for object
    detection using a sliding window technique and a Bayesian-like
    classifier based on random ferns with Haar features. We test the
    algorithm on the car detection problem using a mobile robot for
    urban search and rescue equipped with a camera and a 3D lidar. The
    detector finds cars in a scene and estimates their approximate
    orientation. We show that the fusion of the visual images and the
    3D data significantly improves the detection performance in
    comparison with utilizing only the visual data. The detector is
    able to overcome poor data quality from one of the sensors in
    harsh conditions. },
keywords =    {object detection, depth data},
}