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GLOMAP: Global Structure-from-Motion Revisited

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About

GLOMAP is a general purpose global structure-from-motion pipeline for image-based reconstruction. GLOMAP requires a COLMAP database as input and outputs a COLMAP sparse reconstruction. As compared to COLMAP, this project provides a much more efficient and scalable reconstruction process, typically 1-2 orders of magnitude faster, with on-par or superior reconstruction quality.

If you use this project for your research, please cite

@inproceedings{pan2024glomap,
    author={Pan, Linfei and Barath, Daniel and Pollefeys, Marc and Sch\"{o}nberger, Johannes Lutz},
    title={{Global Structure-from-Motion Revisited}},
    booktitle={European Conference on Computer Vision (ECCV)},
    year={2024},
}

Getting Started

To build GLOMAP, first install COLMAP dependencies and then build GLOMAP using the following commands:

mkdir build
cd build
cmake .. -GNinja
ninja && ninja install

Pre-compiled Windows binaries can be downloaded from the official release page.

After installation, one can run GLOMAP by (starting from a database)

glomap mapper --database_path DATABASE_PATH --output_path OUTPUT_PATH --image_path IMAGE_PATH

For more details on the command line interface, one can type glomap -h or glomap mapper -h for help.

We also provide a guide on improving the obtained reconstruction, which can be found here

Note:

End-to-End Example

In this section, we will use datasets from this link as examples. Download the datasets and put them under data folder.

From database

If a COLMAP database already exists, GLOMAP can directly use it to perform mapping:

glomap mapper \
    --database_path ./data/gerrard-hall/database.db \
    --image_path    ./data/gerrard-hall/images \
    --output_path   ./output/gerrard-hall/sparse

From images

To obtain a reconstruction from images, the database needs to be established first. Here, we utilize the functions from COLMAP:

colmap feature_extractor \
    --image_path    ./data/south-building/images \
    --database_path ./data/south-building/database.db
colmap exhaustive_matcher \
    --database_path ./data/south-building/database.db 
glomap mapper \
    --database_path ./data/south-building/database.db \
    --image_path    ./data/south-building/images \
    --output_path   ./output/south-building/sparse

Visualize and use the results

The results are written out in the COLMAP sparse reconstruction format. Please refer to COLMAP for more details.

The reconstruction can be visualized using the COLMAP GUI, for example:

colmap gui --import_path ./output/south-building/sparse/0

Alternatives like rerun.io also enable visualization of COLMAP and GLOMAP outputs.

If you want to inspect the reconstruction programmatically, you can use pycolmap in Python or link against COLMAP's C++ library interface.

Notes

colmap sequential_matcher --database_path DATABASE_PATH
colmap vocab_tree_matcher --database_path DATABASE_PATH --VocabTreeMatching.vocab_tree_path VOCAB_TREE_PATH

Acknowledgement

We are highly inspired by COLMAP, PoseLib, Theia. Please consider also citing them, if using GLOMAP in your work.

Support

Please, use GitHub Discussions at https://github.com/colmap/glomap/discussions for questions and the GitHub issue tracker at https://github.com/colmap/glomap for bug reports, feature requests/additions, etc.

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

Copyright (c) 2024, ETH Zurich.
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 nor the names of its contributors may
      be used to endorse or promote products derived from this software
      without specific prior written permission.

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AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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