HomLib
C++ library for computing homographies with support in MATLAB and Python.
Solvers
This repository contains the following solvers for computing homographies with simultaneous radial distortion correction and/or incorporating IMU data.
We further support affine-covariant and orientation-covariant solvers, requiring fewer correspondences than their point-based counterparts by leveraging the geometric information of the corresponding descriptors.
| Authors (year) | #Corrs | Minimal | Radial distortion coeff. | IMU data | General homography | Descriptor |
|---|---|---|---|---|---|---|
| Fitzgibbon (2001) | 5 | ✔️ (e) | ✔️ | P | ||
| 5 | ✔️ (1) | ✔️ | P | |||
| Kukelova et al. (2015) | 5 | ✔️ | ✔️ (2) | ✔️ | P | |
| 6 | ✔️ (2) | ✔️ | P | |||
| Valtonen Örnhag et al. (2020) | 4 | ✔️ | ✔️ | P | ||
| Valtonen Örnhag et al. (2021) | 3 | ✔️ | ✔️ | P | ||
| 4 | ✔️ | ✔️ (e) | ✔️ | P | ||
| Nakano (2024) | 5 | ✔️ | ✔️ (1) | ✔️ | P | |
| Wadenbäck et al. (2026) | 5 | ✔️ | ✔️ (1) | ✔️ | P | |
| 5 | ✔️ | ✔️ (e) | ✔️ | P | ||
| 5 | ✔️ | ✔️ (2) | ✔️ | P | ||
| Barath and Hajder (2016) | 2 | ✔️ | A | |||
| Valtonen Örnhag and Adalbjörnsson (2026) | 2 | ✔️ (1) | ✔️ | A | ||
| 3 | ✔️ | ✔️ (1) | ✔️ | O |
We use the following convention for the different distortion cases: (1) - single-sided, (e) two-sided and equal, and (2) two-sided. The following descriptor types: (P) - point-based, (A) affine-covariant, and (O) orientation-covariant.
The solvers by Valtonen Örnhag et al. and Wadenbäck et al. are original implementations, the others are re-implementations. If you use the code in your work, please cite the respective article:
@InProceedings{fitzgibbon-etal-2001-cvpr,
author = {Fitzgibbon, Andrew},
title = {Simultaneous linear estimation of multiple view geometry and lens distortion},
booktitle = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognitioni (CVPR)},
year = {2001},
}
@InProceedings{kukelova-etal-2015-cvpr,
author = {Kukelova, Zuzana and Heller, Jan and Bujnak, Martin and Pajdla, Tomas},
title = {Radial Distortion Homography},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}
@InProceedings{valtonen-ornhag-etal-2020-icpr,
author = {Valtonen~{\"O}rnhag, Marcus and Persson, Patrik and Wadenb{\"a}ck, M{\aa}rten and {\AA}str{\"o}m, Kalle and Heyden, Anders},
title = {Minimal Solvers for Indoor {UAV} Positioning},
booktitle = {Proceedings of the International Conference on Pattern Recognition (ICPR)},
month = {January},
year = {2021},
pages = {1136-1143}
}
@InProceedings{valtonen-ornhag-etal-2021-wacv,
author = {Valtonen~{\"O}rnhag, Marcus and Persson, Patrik and Wadenb{\"a}ck, M{\aa}rten and {\AA}str{\"o}m, Kalle and Heyden, Anders},
title = {Efficient Real-Time Radial Distortion Correction for {UAV}s},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
pages = {1751-1760}
}
@InProceedings{nakano-2024-icpr,
author = {Nakano, Gaku},
title = {Inverse DLT Method for One-Sided Radial Distortion Homography},
booktitle = {Proceedings of the International Conference on Pattern Recognition (ICPR)},
year = {2024},
pages = {448-462}
}
@InProceedings{wadenback-etal-2026-3dv,
author = {Wadenb{\"a}ck, M{\aa}rten and Valtonen~{\"O}rnhag, Marcus and Edstedt, Johan},
title = {Radially Distorted Homographies, Revisited},
booktitle = {Proceedings of the International Conference on 3D Vision (3DV)},
year = {2026},
}
@InProceedings{valtonen-ornhag-adalbjornsson-2026-icpr,
author = {Valtonen~{\"O}rnhag, Marcus and Adalbj{\"o}rnsson, Stefan},
title = {Radial Distortion Homography Estimation from Affine-Covariant or Orientation-Covariant Features},
booktitle = {Proceedings of the International Conference on Pattern Recognition (ICPR)},
year = {2026},
}
Dependencies
The source code depends on Eigen 3 (older versions not compatible). Installation for Ubuntu/Debian:
$ apt-get install libeigen3-dev
Furthermore, PoseLib is required. Follow the installation instruction in the repo.
If you want to use the solvers in an LOMSAC framework, we rely on RansacLib, which is included as a submodule. You can recursively clone it
git submodule update --init --recursive
Using the solver in Python
Python wheels for all standard platforms and supported Python versions are available at PyPI. To install, simply use
$ pip install homlib
Note: Solvers with known IMU data is not yet supported in the python package.
Using the solver in MATLAB
(OUTDATED)
It is possible to MEX-compile the solver and use it in MATLAB. Check the
compile_mex.m function in the MATLAB directory. You may have to change the path to Eigen,
e.g. /usr/local/include/eigen3.
About the solvers
Many of the solvers were generated using the automatic generator proposed by Larsson et al. "Efficient Solvers for Minimal Problems by Syzygy-based Reduction" (CVPR 2017)
1 maintainer
Metadata
1 maintainer
Release files for homlib 0.1.3
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Source distribution (sdist)
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