PCR-Pro: 3D Sparse and Different Scale Point Clouds Registration and Robust Estimation of Information Matrix For Pose Graph SLAM
If you use PCR-Pro, we appreciate it if you cite our paper:
@inproceedings{bhutta2018pcr,
title = {{PCR-Pro}: 3D Sparse and Different Scale Point Clouds Registration and Robust Estimation of Information Matrix For Pose Graph {SLAM}},
author={Bhutta, M Usman Maqbool and Liu, Ming},
booktitle={2018 IEEE 8th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems ({CYBER})},
pages={354--359},
year={2018},
organization={IEEE}
}
PCR-Pro has been tested on OpenCV 2.8.9 and Eigen 3.
Mandatory Tools:
- Libpointmatcher
- OpenGV
- Written in C++ 11
Optional:
- Paraview, for better visualization of point cloud, Please use the paraview, it will take VTK file as input.
Change Camera Intrinsic Parameters in the main file code before using this, replace this with your camera calibration results.
float KF_fx = 467.87;
float KF_fy = 514.317;
float KF_cx = 271.828;
float KF_cy = 246.906;
mkdir build && cd build
cmake ../
make
./main <img1> <img2> <pointcloud2> <pointcloud1>
# Example
./build/main data/Result_1/robot1TestImg36.jpg data/Result_1/robot2TestImg16.jpg data/Result_1/robot2pcd16.pcd data/Result_1/robot1pcd36.pcd
Paraview accepts VTK file, PCD / PLY can be converted to VTK using the PCL Library. Example has been shown below.
pcl_pcd2vtk <pointcloud.pcd> <pointcloud.vtk>
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