IS = { zkontrolovano 06 Aug 2014 },
  UPDATE  = { 2014-07-25 },
author =      {Hrabal{\'\i}k, Ale{\v s}},
supervisor =  {Svoboda, Tom{\'a}{\v s}},
title =       {3D Point Cloud Registration, Experimental Comparison and Fusing Range and Visual Data},
school =      {Center for Machine Perception, K13133 FEE, Czech Technical University},
address =     {Prague, Czech Republic},
year =        {2014},
month =       {June},
type =        {{BSc Thesis CTU--CMP}},
pages =       {50},
figures =     {20},
authorship =  {100},
psurl       = {https://cyber.felk.cvut.cz/research/theses/papers/508.pdf},
project =     {FP7-ICT-609763 TRADR},
annote =      {Point cloud registration is an important process in
                  mobile robotics, serving as the cornerstone of
                  simultaneous localization and mapping. The
                  contribution of our work is twofold: firstly, we
                  compare local registration methods using
                  high-quality datasets and a custom protocol. In
                  terms of precision and robustness to initial pose
                  displacement, the capabilities of the methods are
                  explored in an unprecedented detail, overcoming any
                  previous work that we know of. Secondly, we propose
                  enhancements to a global, feature-based registration
                  method that take advantage of visual information,
                  specifically camera imagery. Proposed changes
                  include an extension of the feature descriptor, and
                  a modification of reference frame determination. To
                  investigate the modified methods, a dataset
                  containing visual data is created. Experimental
                  results indicate a significant improvement over the
                  original method.},
keywords =    {point clouds, robotics, registration},