OpenMVG (open Multiple View Geometry)

open Multiple View Geometry library. Basis for 3D computer vision and Structure from Motion.

Description

**Our Mission** - Develop a C++ framework to provide easy access to 3D reconstruction from images.

**Our Vision** - We enhance reproducible research in 3D reconstruction from images by providing easy-to-read and accurate implementation of state of the art "classic algorithms" that the community considers as references. Using them in libraries, samples, and pipelines help to spread the usage of computer vision techniques to the community.

**Our Credo** - "Keep it simple, keep it maintainable". [OpenMVG](https://github.com/openMVG/openMVG) is designed to be easy to learn, modify and use. Thanks to its strict test driven development and samples, the library can be used as trusted bricks to build larger systems.

Programming language: C++

License: Mozilla Public License 2.0

Tags: Graphics     Image Processing     3D     Structure From Motion     Geometry     Photogrammetry    

Latest version: v1.6

README

OpenMVG (open Multiple View Geometry)

License	Documentation	Continuous Integration (Linux/MacOs/Windows)	Build	Code Quality	Chat
	Wiki		local/docker build tutorial

Our Mission

• Extend awareness of the power of 3D reconstruction from images/photogrammetry by developing a C++ framework.

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

• See Wiki
  • OpenMVG Data Structure
  • Using OpenMVG as a library
  • Using OpenMVG on your image dataset
  • ...

More information

• Authors
• Contact
• Citations
• Acknowledgements

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={Open{MVG}: 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.