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TEASER++: fast & certifiable 3D registration

TEASER++ is a fast and certifiably-robust point cloud registration library written in C++, with Python and MATLAB bindings.

About

Left: correspondences generated by 3DSmoothNet (green and red lines represent the inlier and outlier correspondences according to the ground truth respectively). Right: alignment estimated by TEASER++ (green dots represent inliers found by TEASER++).

TEASER++ can solve the rigid body transformation problem between two point clouds in 3D. It performs well even if the input correspondences have an extremely large number of outliers. For a short conceptual introduction, check out our video. For more information, please refer to our papers:

If you find this library helpful or use it in your projects, please cite:

@article{Yang20tro-teaser,
  title={{TEASER: Fast and Certifiable Point Cloud Registration}},
  author={H. Yang and J. Shi and L. Carlone},
  journal={{IEEE} Trans. Robotics},
  pdf={https://arxiv.org/pdf/2001.07715.pdf},
  Year = {2020} 
}

If you are interested in more works from us, please visit our lab page here.

TL;DR

Minimal C++ example

Run the following script to show a minimal C++ example:

sudo apt install cmake libeigen3-dev libboost-all-dev
git clone https://github.com/MIT-SPARK/TEASER-plusplus.git
cd TEASER-plusplus && mkdir build && cd build
cmake .. && make
sudo make install
sudo ldconfig
cd .. && cd examples/teaser_cpp_ply && mkdir build && cd build
cmake .. && make
./teaser_cpp_ply

You should see terminal output like this:

	Read 1889 total vertices 
*** [pmc heuristic: thread 1]   current max clique = 577,  time = 0.00163579 sec
...
*** [pmc: thread 2]   current max clique = 602,  time = 0.44515 sec
-----------------------------------------------------------------------
=====================================
          TEASER++ Results           
=====================================
Expected rotation: 
  0.996927  0.0668736 -0.0406664
 -0.066129   0.997618  0.0194009
 0.0418676 -0.0166518   0.998978
Estimated rotation: 
  0.996658  0.0729647  0.0367288
-0.0740469   0.996832  0.0290182
-0.0344951 -0.0316408   0.998904
Error (deg): 0.0783556

Expected translation: 
 -0.115577
-0.0387705
  0.114875
Estimated translation: 
 -0.116132
-0.0390858
   0.11729
Error (m): 0.00249818

Number of correspondences: 1889
Number of outliers: 1700
Time taken (s): 0.786677

Minimal C++ example for MacOS with brew:

Run the following script to show a minimal C++ example:

brew install cmake
brew install boost
brew install eigen
git clone https://github.com/MIT-SPARK/TEASER-plusplus.git
cd TEASER-plusplus && mkdir build && cd build
cmake .. && make
sudo make install
cd .. && cd examples/teaser_cpp_ply && mkdir build && cd build
cmake .. && make
./teaser_cpp_ply

Getting Started

Other Publications

Other publications related to TEASER include:

  • H. Yang and L. Carlone, “A quaternion-based certifiably optimal solution to the Wahba problem with outliers,” in Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2019, pp. 1665–1674. (pdf)
  • H. Yang, P. Antonante, V. Tzoumas, and L. Carlone, “Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection,” IEEE Robotics and Automation Letters (RA-L), 2020. (pdf)

Acknowledgements

This work was partially funded by ARL DCIST CRA W911NF-17-2-0181, ONR RAIDER N00014-18-1-2828, Lincoln Laboratory “Resilient Perception in Degraded Environments”, and the Google Daydream Research Program.

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A fast and robust point cloud registration library

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