GlobalSfMpy

This repo is the implementation of the paper "Revisiting Rotation Averaging: Uncertainties and Robust Losses".

If you find our code or paper useful, please cite

@inproceedings{zhang2023revisiting,
  title={Revisiting Rotation Averaging: Uncertainties and Robust Losses},
  author={Zhang, Ganlin and Larsson, Viktor and Barath, Daniel},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={17215--17224},
  year={2023}
}

Tested Environment

Ubuntu 22.04

Dependency

• TheiaSfM (Recommand version 0.7.0)
• Ceres (Recommand version 1.14.0)
• pybind11 (Recommand version 2.9.2)
• OpenCV
• (Optional) COLMAP (Recommand version 3.6)

Demo

1DSfM Madrid_Metropolis

cd script
python sfm_pipeline.py ../flags_1dsfm.yaml

ETH3D facade

First, use COLMAP extract the feature points and two-view matches. Put the COLMAP results inside the datasets/facade/colmap folder. i.e.

.
└── datasets
    └── facade
        ├── cameras.txt
        ├── colmap
        │   ├── cameras.txt
        │   ├── database.db
        │   ├── images.txt
        │   ├── points3D.txt
        │   └── project.ini
        ├── images
        │   └── *.JPG
        └── images.txt

Then, use GobalSfMpy to reconstruct the scene.

cd script
python read_colmap_database.py --dataset_path ../datasets/facade
python get_covariance_from_colmap.py
python sfm_with_colmap_feature.py

The reconstruction is stored in output folder. The format of the result is the same as what it is in TheiaSfM. The Theia application view_reconstruction can be used to visualize the result.

./view_reconstruction --reconstruction <RESULT_FILE>