openmvg/camerasensorsizedatabase

A list of camera model, maker and their associated camera sensor size.

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.

camerasensorsizedatabase's Issues

change csv delimiter from ; to ,

Hi there,

The current csv files use ; as the delimiter. Generally , is the default delimiter accepted in lot of places and would be helpful to use this csv files in other applications. Apart from that github also helps you render them beautifully in the webpage with search option if its delimited by ,.

Delimited by ,

Delimited by ;

Would be happy to do a pr if approved.

Any pointer on how to calculate iPhone X, XS, XR sensor?

I can see the database was kind of up to date on iPhone, but I am trying to calculate the one for iPhone X especially. Any idea? Does it correspond to certain lens, because the Plus size and iPhone X also has 2 lenses? Except for XR.

@cignoni Any idea how to calculate this? Thanks!

sensor_database.csv file is read only

Hi! I'm having a small issue trying to add my camera to the database. I have an editor that supports Unix line endings; it's just that when I try to open the sensor_database.csv file, it says read-only and it won't allow me to change the permissions on the document. I have to make a duplicate of the file to change the document, but it also won't allow me to replace the original document with my edited one. I'm working on a Mac. Does anyone have any suggestions?