More examples and fitting problems are coming soon!
Clone the repository and its submodules:
git clone https://github.com/danini/stereoglue.git
Make sure that you have the necessary libraries installed:
sudo apt-get install libopencv-dev libopencv-contrib-dev libarpack++2-dev libarpack2-dev libsuperlu-dev libeigen3-dev libboost-all-dev pybind11
To run affine feature detection and matching with the built-in tools, install:
pip install kornia
pip install kornia-moons
git clone https://github.com/cvg/LightGlue.git && cd LightGlue
python -m pip install -e .
Install StereoGlue by running
pip install .
- Eigen 3.0 or higher
- CMake 2.8.12 or higher
- OpenCV 3.0 or higher
- A modern compiler with C++17 support
The example for essential matrix fitting with gravity-based solver is available at: notebook.
The example for fundamental matrix fitting with monodepth-based solver is available at: notebook.
When using the algorithm, please cite:
@inproceedings{StereoGlue2024,
author = {Barath, Daniel and Mishkin, Dmytro and Cavalli, Luca and Sarlin, Paul-Edouard and Hruby, Petr and Pollefeys, Marc},
title = {{StereoGlue}: Robust Estimation with Single-Point Solvers},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2024},
}
If you use it for fundamental matrix estimation, please cite:
@inproceedings{Hruby2024,
author = {Hruby, Petr and Pollefeys, Marc and Barath, Daniel},
title = {Semicalibrated Relative Pose from an Affine Correspondence and Monodepth},
booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
year = {2024},
}
If you use it with MAGSAC++ scoring, please cite:
@inproceedings{barath2020magsac++,
title={MAGSAC++, a fast, reliable and accurate robust estimator},
author={Barath, Daniel and Noskova, Jana and Ivashechkin, Maksym and Matas, Jiri},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
pages={1304--1312},
year={2020}
}