OpenMVG (open Multiple View Geometry)
Our Vision
- Simplify reproducible research with easy-to-read and accurate implementation of state of the art and "classic" algorithms.
Our Credo
- "Keep it simple, keep it maintainable".
- OpenMVG is designed to be easy to read, learn, modify and use.
- Thanks to its strict test-driven development and samples, the library allows to build trusted larger systems.
Our codebase and pipeline
OpenMVG provides an end-to-end 3D reconstruction from images framework compounded of libraries, binaries, and pipelines.
- The libraries provide easy access to features like: images manipulation, features description and matching, feature tracking, camera models, multiple-view-geometry, robust-estimation, structure-from-motion algorithms, ...
- The binaries solve unit tasks that a pipeline could require: scene initialization, feature detection & matching and structure-from-motion reconstruction, export the reconstructed scene to others Multiple-View-Stereovision framework to compute dense point clouds or textured meshes.
- The pipelines are created by chaining various binaries to compute image matching relation, solve the Structure from Motion problem (reconstruction, triangulation, localization) and ...
OpenMVG is developed in C++ and runs on Android, iOS, Linux, macOS, and Windows.
Tutorials
More information
Authors
See Authors text file
Contact
openmvg-team[AT]googlegroups.com
Citations
We are recommending citing OpenMVG if you are using the whole library or the adequate paper if you use only a submodule AContrario Ransac [3], AContrario SfM [1], GlobalSfM [4] or Tracks [2]:
@inproceedings{moulon2016openmvg,
title={Openmvg: Open multiple view geometry},
author={Moulon, Pierre and Monasse, Pascal and Perrot, Romuald and Marlet, Renaud},
booktitle={International Workshop on Reproducible Research in Pattern Recognition},
pages={60--74},
year={2016},
organization={Springer}
}
[1] Moulon Pierre, Monasse Pascal and Marlet Renaud. ACCV 2012.
Adaptive Structure from Motion with a contrario model estimation.
@inproceedings{Moulon2012,
doi = {10.1007/978-3-642-37447-0_20},
year = {2012},
publisher = {Springer Berlin Heidelberg},
pages = {257--270},
author = {Pierre Moulon and Pascal Monasse and Renaud Marlet},
title = {Adaptive Structure from Motion with a~Contrario Model Estimation},
booktitle = {Proceedings of the Asian Computer Vision Conference (ACCV 2012)}
}
[2] Moulon Pierre and Monasse Pascal. CVMP 2012.
Unordered feature tracking made fast and easy.
@inproceedings{moulon2012unordered,
title={Unordered feature tracking made fast and easy},
author={Moulon, Pierre and Monasse, Pascal},
booktitle={CVMP 2012},
pages={1},
year={2012}
}
[3] Moisan Lionel, Moulon Pierre and Monasse Pascal. IPOL 2012.
Automatic Homographic Registration of a Pair of Images, with A Contrario Elimination of Outliers.
@article{moisan2012automatic,
title={Automatic homographic registration of a pair of images, with a contrario elimination of outliers},
author={Moisan, Lionel and Moulon, Pierre and Monasse, Pascal},
journal={Image Processing On Line},
volume={2},
pages={56--73},
year={2012}
}
[4] Moulon Pierre, Monasse Pascal, and Marlet Renaud. ICCV 2013.
Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion.
@inproceedings{moulon2013global,
title={Global fusion of relative motions for robust, accurate and scalable structure from motion},
author={Moulon, Pierre and Monasse, Pascal and Marlet, Renaud},
booktitle={Proceedings of the IEEE International Conference on Computer Vision},
pages={3248--3255},
year={2013}
}
Acknowledgements
openMVG authors would like to thanks libmv authors for providing an inspiring
base to design openMVG. Authors also would like to thanks Mikros Image
and LIGM-Imagine laboratory for support and authorization to make this
library an opensource project.