Fast Plane Extraction Using Agglomerative Hierarchical Clustering (AHC)

Overview

This source code package contains our C++ implementation of the AHC based fast plane extraction for organized point cloud (point cloud that can be indexed as an image). There are three folders in this package:

• include

  Our C++ implementation of the algorithm with dependencies on OpenCV and shared_ptr (from C++11 or Boost).

• cpp

  Two example C++ console applications using our algorithm to extract planes from Kinect-like point cloud (depends on PCL), with a CMake script to help generating project files.

• matlab

  A matlab interface (fitAHCPlane.m) through MEX for using our algorithm in matlab. We also provide a wrapper class Kinect.m and kinect_ahc.m to do real-time plane extraction in matlab, partially depends on a 3rd-party toolbox Kinect_Matlab.

Installation

Software Dependencies:

• OpenCV (BSD-3-Clause license)
• Boost (BSL-1.0 license)
• Point Cloud Library (BSD-3-Clause license)

C++ example

1. Install OpenCV, Boost and PCL (If you install PCL using their all-in-one installer, you directly get Boost installed as well).

2. Generate project file using CMake under either Windows or Linux.

3. Compile.

4. Run the compiled process: plane_fitter (first connect a Kinect to your computer!) or plane_fitter_pcd (first modify plane_fitter_pcd.ini accordingly!).

5. Enjoy!

Matlab example

1. In matlab:

cd WHERE_YOU_EXTRACT_THE_PACKAGE/matlab/mex

2. Run makefile.m

3. Select the directories for OpenCV_Include, OpenCV_Lib, and Boost_Include respectively

4. If everything compiles smoothly:

cd ..

5. Load a single frame we've prepared for you in matlab by:

load frame

6. Run our algorithm on the point cloud:

frame.mbs=fitAHCPlane(frame.xyz);
viewSeg(frame.mbs,640,480)

7. Enjoy!

8. If you want to play with the kinect_ahc.m with a Kinect, install Kinect_Matlab first.

Citation

If you use the software, please cite the following (MERL TR2014-066):

@inproceedings{Feng2014may,
author = {Feng, C. and Taguchi, Y. and Kamat, V.},
title = {Fast Plane Extraction in Organized Point Clouds Using Agglomerative Hierarchical Clustering},
booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
year = 2014,
pages = {6218--6225},
month = may,
publisher = {IEEE},
doi = {10.1109/ICRA.2014.6907776},
url = {https://www.merl.com/publications/TR2014-066}
}

Contact

Tim Marks tmarks@merl.com

Contributing

See CONTRIBUTING.md for our policy on contributions.

License

Released under AGPL-3.0-or-later license, as found in the LICENSE.md file.

All files:

Copyright (c) 2014,2023 Mitsubishi Electric Research Laboratories (MERL).

SPDX-License-Identifier: AGPL-3.0-or-later