Plane Extraction using Agglomerative Clustering (PEAC)

Download source code for PEAC!

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 KinectMatlab.

If you use this package, please cite our ICRA 2014 paper:

Feng, C., Taguchi, Y., and Kamat, V. R. (2014). “Fast Plane Extraction in Organized Point Clouds Using Agglomerative Hierarchical Clustering.” Proceedings of the IEEE International Conference on Robotics and Automation, Hong Kong, China, 6218-6225.

@inproceedings{feng2014fast,
  title={Fast plane extraction in organized point clouds using agglomerative hierarchical clustering},
  author={Feng, Chen and Taguchi, Yasuhiro and Kamat, Vineet R},
  booktitle={Robotics and Automation (ICRA), 2014 IEEE International Conference on},
  pages={6218--6225},
  year={2014},
  organization={IEEE}
}

Version

1.0

Installation

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.

Feel free to email any bugs or suggestions to help us improve the code. Thank you!