pose_calib
Efficient Pose Selection for Interactive Camera Calibration
Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org -
○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (10.3%) to scientific vocabulary
Repository
Efficient Pose Selection for Interactive Camera Calibration
Basic Info
- Host: GitHub
- Owner: paroj
- License: agpl-3.0
- Language: Python
- Default Branch: master
- Homepage: https://www.calibdb.net/
- Size: 33.2 KB
Statistics
- Stars: 72
- Watchers: 4
- Forks: 17
- Open Issues: 3
- Releases: 0
Metadata Files
README.md
Abstract
The choice of poses for camera calibration with planar patterns is only rarely considered - yet the calibration precision heavily depends on it. This work presents a pose selection method that finds a compact and robust set of calibration poses and is suitable for interactive calibration. Consequently, singular poses that would lead to an unreliable solution are avoided explicitly, while poses reducing the uncertainty of the calibration are favoured. For this, we use uncertainty propagation. Our method takes advantage of a self-identifying calibration pattern to track the camera pose in real-time. This allows to iteratively guide the user to the target poses, until the desired quality level is reached. Therefore, only a sparse set of key-frames is needed for calibration. The method is evaluated on separate training and testing sets, as well as on synthetic data. Our approach performs better than comparable solutions while requiring 30% less calibration frames. arXiv
Citing
If you use this application for scientific work, please consider citing us as
@inproceedings{rojtberg2018,
author={P. Rojtberg and A. Kuijper},
booktitle={2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)},
title={Efficient Pose Selection for Interactive Camera Calibration},
year={2018},
pages={31-36},
doi={10.1109/ISMAR.2018.00026},
ISSN={1554-7868},
month={Oct}
}
Dependencies
- Python: 3.x
- OpenCV: 3.x
- including OpenCV contrib
- compiled with Qt highui backend
Usage
Call pose_calib.py with a calibration config file as
$ ./pose_calib.py data/calib_config.yml
Press m to toggle between normal and mirrored display. You can find the default pattern image here.
After convergence, the resulting calibration properties will be written as calib_<cameraId>.yml.
Camera, image resolution and charuco settings can be changed via the calibration config file.
A pre-build package for Ubuntu is installable via the snapcraft store
Owner
- Name: Pavel Rojtberg
- Login: paroj
- Kind: user
- Location: Germany
- Website: https://www.rojtberg.net
- Twitter: paroj7
- Repositories: 91
- Profile: https://github.com/paroj
Graphics & Vision Enthusiast
Citation (CITATION.bib)
@inproceedings{rojtberg2018,
author={P. Rojtberg and A. Kuijper},
booktitle={2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)},
title={Efficient Pose Selection for Interactive Camera Calibration},
year={2018},
pages={31-36},
doi={10.1109/ISMAR.2018.00026},
ISSN={1554-7868},
month={Oct}
}
GitHub Events
Total
- Issues event: 1
- Watch event: 4
- Push event: 1
- Fork event: 1
Last Year
- Issues event: 1
- Watch event: 4
- Push event: 1
- Fork event: 1
Committers
Last synced: over 1 year ago
Top Committers
| Name | Commits | |
|---|---|---|
| Pavel Rojtberg | r****g@g****m | 5 |
Issues and Pull Requests
Last synced: 12 months ago
All Time
- Total issues: 8
- Total pull requests: 0
- Average time to close issues: 5 days
- Average time to close pull requests: N/A
- Total issue authors: 6
- Total pull request authors: 0
- Average comments per issue: 2.63
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Acwok (2)
- zbynekwinkler (2)
- DoStraTech (1)
- xumengdi123 (1)
- dbsi-pinkman (1)
- pengsongyou (1)