LIBICP - C++ Library for Iterative Closest Point Matching

LIBICP: Library for Iterative Closest Point fitting

Author: Andreas Geiger
Institute of Measurement and Control Systems
Karlsruhe Institute of Technology

Please send any feedback or bugreports to: geiger@kit.edu

Introduction

LIBICP (LIBrary for Iterative Closest Point fitting) is a cross-platfrom C++ library with MATLAB wrappers for fitting 2d or 3d point clouds with respect to each other. Currently it implements the SVD-based point-to-point algorithm as well as the linearized point-to-plane algorithm. It also supports outlier rejection and is accelerated by the use of kd trees as well as a coarse matching stage using only a subset of all points.

Changelog

21.09.2011: First version online

Prerequisites

BOOST libraries (needed by kd tree)
CMAKE (if you want to compile the c++ demo program)
MATLAB (if you want to use the MATLAB wrappers)

Downloads

LIBICP for Linux/Mac/Windows

Using this Code as part of your Software

This code is published under the GNU General Public License. If you distribute software that uses libicp, you have to distribute it under GPL with the source code.

Disclaimer

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Please send any feedback or bugreports to: geiger@kit.edu