Coarse2FineRoofPlane

This is the C++ implementation of the following publication:

Coarse2FineRoofPlane: A Coarse-to-fine Boundary Relabeling Approach for Roof Plane Segmentation

Guozheng Xu, Siyuan You, Ke Liu, Li Li, Jian Yao

This manuscript has been accepted by IEEE GRSL Journal.

Introduction

Coarse2FineRoofPlane is a C++ library for roof plane segmentation using a coarse-to-fine boundary relabeling approach. Here is the link of the paper: https://doi.org/10.1109/LGRS.2025.3577989.

Dependency

Please download and install the required dependency libraries before compiling the code:

eigen3 (3.4.0)
[boost](https://github.com/boostorg/boost) (1.80.0  program_options filesystem graph system)
[libigl](https://github.com/libigl/libigl) (2.5.0)
[pcl](https://github.com/PointCloudLibrary/pcl) (1.13.1) 

You can install eigen3 pcl boost using vcpkg:

#install vcpkg
git clone https://github.com/microsoft/vcpkg.git
cd vcpkg
./bootstrap-vcpkg.sh  # Linux/macOS
./bootstrap-vcpkg.bat # Windows
#
./vcpkg install boost
./vcpkg install eigen3
./vcpkg install pcl

Libigl is a header-only library, which has downloaded in 'include' directory.

Usage

Coarse2FineRoofPlane options
options:
  -h [ --help ]                      produce this help message
  -i [ --input ] arg (=input.txt)    filename
  -o [ --output ] arg (=../result/)  outputPath
  -l [ --level ] arg (=2)            voxel levels Number(0,1,...)default 2
  -d [ --density ] arg (=2)          multiDensity, Voxel Size=multiDensity*dens
                                     ity
  -s [ --smoothLamdaValue ] arg (=2) smoothLamdaValue default 2.0

Test

Upon downloading the code, the test data has been preconfigured and stored in the 'data' directory, ensuring immediate readiness for testing. A example of Using Coarse2FineRoofPlane:

Coarse2FineRoofPlane --i ./data/000206.txt --o ./resData/ 

Citation

If you find our work useful for your research, please consider citing our paper.

Coarse2FineRoofPlane: A Coarse-to-fine Boundary Relabeling Approach for Roof Plane Segmentation

Guozheng Xu, Siyuan You, Ke Liu, Li Li, Jian Yao

IEEE Geoscience and Remote Sensing Letters, 2025.

Contact:

Guozheng Xu (xugzh96_0508@whu.edu.cn)