A Point Cloud Registration Benchmark

Introduction

To facilitate the test of the registration performance of each point cloud registration baseline, a point cloud registration benchmark GUI based on PyQt5 is developed.

Point Cloud Registration Baselines Currently Supported

• ICP
• GMM
• FGR
• DGM
• DGM-Net
• RPM-Net
• RGM
• PCRNet

Data Simulation

Point cloud data modelnet40_ply_hdf5_2048 from ModelNet40 are given here.

Clean Data

You can select point cloud data files (*.hdf5/h5), which contain point clouds in the format Point-Cloud-Num x Point-Num x 3. Random rotation matrix and translation vector will be generated with the angles in $[-45\degree,45\degree]$ and translation in $[-1,1]$ of XYZ axis.

Noise Data

You can add gauss noise into the target point cloud datas with bias in XYZ axis for registration tests.

Requirements

Python3.7 is highly recommended for the compatibility of Open3D. And requirements are listed as follows:

• h5py==3.8.0
• matplotlib==3.5.3
• numpy==1.21.6
• open3d==0.16.1
• PyQt5==5.15.9
• pyqtgraph==0.12.4
• scipy==1.7.3
• torch==1.13.1

To configure the environment, simply enter this command:

pip3 install -r requirements.txt

Run

You can run the PCR.Benchmark with the command:

python3 ./src/benchmark.py