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COLMAP with GPS Position Prior

What's New?

Adding GPS position prior to reconstruction inspired by openMVG, the final model is the same scale with the prior position.

Note: You should firstly add pose (world to camera: qw qx qy qz tx ty tz) prior to database use scripts/python/add_db_pose_prior.py.

Before and after adding prior
before after

Two steps to use the GPS position prior: 1) estimate sim3 transformation between un-scaled model (camera positions) and corresponding priors CODE HERE; 2) add costs to the scaled positions and GPS postions CODE HERE and CODE HERE.

I used colmap (commit: 866af28746d6500a97a241f9235e2730b2b90c29) as baseline code and defined a variable ENABLE_POSITION_PRIOR to enable using position prior in src/base/reconstruction.h, please check its references. If you don't use position prior, you can comment this definition.

About

COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. It offers a wide range of features for reconstruction of ordered and unordered image collections. The software is licensed under the new BSD license. If you use this project for your research, please cite:

@misc{vincentqin2022colmapgps,
    author = {Vincent Qin},
    title = {COLMAP with GPS Position Prior},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {\url{https://github.com/Vincentqyw/colmap-gps}}
    year = {2022},
}

@inproceedings{schoenberger2016sfm,
    author={Sch\"{o}nberger, Johannes Lutz and Frahm, Jan-Michael},
    title={Structure-from-Motion Revisited},
    booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2016},
}

@inproceedings{schoenberger2016mvs,
    author={Sch\"{o}nberger, Johannes Lutz and Zheng, Enliang and Pollefeys, Marc and Frahm, Jan-Michael},
    title={Pixelwise View Selection for Unstructured Multi-View Stereo},
    booktitle={European Conference on Computer Vision (ECCV)},
    year={2016},
}

If you use the image retrieval / vocabulary tree engine, please also cite:

@inproceedings{schoenberger2016vote,
    author={Sch\"{o}nberger, Johannes Lutz and Price, True and Sattler, Torsten and Frahm, Jan-Michael and Pollefeys, Marc},
    title={A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval},
    booktitle={Asian Conference on Computer Vision (ACCV)},
    year={2016},
}

The latest source code is available at https://github.com/colmap/colmap. COLMAP builds on top of existing works and when using specific algorithms within COLMAP, please also cite the original authors, as specified in the source code.

Download

Executables for Windows and Mac and other resources can be downloaded from https://demuc.de/colmap/. Executables for Linux/Unix/BSD are available at https://repology.org/metapackage/colmap/versions. To build COLMAP from source, please see https://colmap.github.io/install.html.

Getting Started

  1. Download the pre-built binaries from https://demuc.de/colmap/ or build the library manually as described in the documentation.
  2. Download one of the provided datasets at https://demuc.de/colmap/datasets/ or use your own images.
  3. Use the automatic reconstruction to easily build models with a single click or command.

Documentation

The documentation is available at https://colmap.github.io/.

Support

Please, use the COLMAP Google Group at https://groups.google.com/forum/#!forum/colmap ([email protected]) for questions and the GitHub issue tracker at https://github.com/colmap/colmap for bug reports, feature requests/additions, etc.

Acknowledgments

The library was written by Johannes L. Schönberger (https://demuc.de/). Funding was provided by his PhD advisors Jan-Michael Frahm (http://frahm.web.unc.edu/) and Marc Pollefeys (https://people.inf.ethz.ch/pomarc/).

Contribution

Contributions (bug reports, bug fixes, improvements, etc.) are very welcome and should be submitted in the form of new issues and/or pull requests on GitHub.

License

The COLMAP library is licensed under the new BSD license. Note that this text refers only to the license for COLMAP itself, independent of its dependencies, which are separately licensed. Building COLMAP with these dependencies may affect the resulting COLMAP license.

Copyright (c) 2018, ETH Zurich and UNC Chapel Hill.
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

    * Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.

    * Redistributions in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.

    * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of
      its contributors may be used to endorse or promote products derived
      from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
POSSIBILITY OF SUCH DAMAGE.

Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)

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