@inproceedings{ekekrantz2013iros-ppniv,
  author =       {Ekekrantz, Johan and Pronobis, Andrzej and Folkesson, John and Jensfelt, Patric},
  title =        {Enabling Efficient Registration using Adaptive Iterative Closest Keypoint},
  booktitle =    {IROS 2013 Workshop on Planning, Perception and Navigation for Intelligent Vehicles},
  year =         2013,
  address =      {Tokyo, Japan},
  month =        nov,
  url =          {http://www.pronobis.pro/publications/ekekrantz2013iros-ppniv},
  abstract =     {Registering frames of 3D sensor data is a key functionality in many robot applications, from multi-view 3D object recognition to SLAM. With the advent of cheap and widely available, so called, RGB-D sensors acquiring such data has become possible also from small robots or other mobile devices. Such robots and devices typically have limited resources and being able to perform registration in a computationally efficient manner is therefore very important. In our recent work, we proposed a fast and simple method for registering RGB-D data, building on the principle of the Iterative Closest Point (ICP) algorithm. This paper outlines this new method and shows how it can facilitate a significant reduction in computational cost while maintaining or even improving performance in terms of accuracy and convergence properties. As a contribution we present a method to efficiently measure the quality of a found registration.}
}