"The naming of eKalibr is inspired by Kalibr, but not an extension of it."
🎉 News » eKalibr Version 1.0.0 Is Released!
eKalibr is a visual calibration framework for event cameras, inspired by the well-known frame-based calibration framework Kalibr. eKalibr has the following features:
- Calibration using a circular grid pattern.
eKalibrincludes a precise circular grid pattern recognition pipeline, capable of directly extracting patterns from raw event streams. - It is open-source and free of charge. Any organization, as long as it complies with the
eKalibropen-source license, can freely useeKalibrfor secondary development without restrictions. - Currently,
eKalibrsupports intrinsic calibration of event cameras. In the future, I will extendeKalibrto support multi-event-camera and event-IMU (event-inertial) spatiotemporal calibration. Stay tuned!
For more details, please refer to our article 👇:
- S. Chen, X. Li*, L. Yuan, and Z. Liu. eKalibr: Dynamic Intrinsic Calibration for Event Cameras From First Principles of Events[J]. arXiv preprint arXiv:2501.05688, 2025. [paper-arXiv] [video]
« The Demonstration Video of eKalibr »
"Event-Based, Intrinsic, Spatial, Temporal, Multiple, Easy To Use, You Only Calibrate Once"
Tutorial: Prepare eKalibr for Calibration »
eKalibr has been tested only on Ubuntu 20.04. Generally, the key dependencies are ROS1 and CPP17. If both of these requirements are met, there should be no issues. To use eKalibr, please first follow Tutorial to configure the necessary environment and compile eKalibr, and then proceed with Tutorial for specific data collection and sensor calibration.
Access Public Datasets of eKalibr »
To facilitate the learning of those interested in eKalibr, we have made the datasets used for testing and evaluating eKalibr publicly available:
- Intrinsic calibration datasets of event cameras. These datasets can be accessed here.
- Stay tuned...
MIT License
Copyright 2025, the School of Geodesy and Geomatics (SGG), Wuhan University, China
eKalibr: Event-Based Visual Calibration Framework
GitHub: https://github.com/Unsigned-Long/eKalibr.
Author: Shuolong Chen ([email protected])
GitHub: https://github.com/Unsigned-Long
ORCID: 0000-0002-5283-9057
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