@ARTICLE{sparkison-2019a,
author={S. A. {Parkison} and M. {Ghaffari} and L. {Gan} and R. {Zhang} and A. K. {Ushani} and R. M. {Eustice}},
journal={IEEE Robotics and Automation Letters},
title={Boosting Shape Registration Algorithms via Reproducing Kernel Hilbert Space Regularizers},
year={2019},
volume={4},
number={4},
pages={4563-4570},
keywords={Hilbert spaces;image colour analysis;image registration;learning (artificial intelligence);optical radar;physical point;matched points;rigid body transformation;kernel hilbert space regularizers;shape registration algorithms;registration cost function;Kernel Hilbert Space;kernel methods;point cloud measurement;shape geometry;Three-dimensional displays;Kernel;Hilbert space;Shape;Laser radar;Image color analysis;Robot sensing systems;Range sensing;RGB-D perception;localization},
doi={10.1109/LRA.2019.2932865},
ISSN={2377-3774},
month={Oct},}