E-Calib: A Fast, Robust, and Accurate Calibration Toolbox for Event Cameras

Area of Science:

• Computer Vision
• Robotics
• Sensor Technology

Background:

• Event cameras offer advantages like low latency and high dynamic range, crucial for advanced computer vision tasks.
• Traditional camera calibration methods are unsuitable for event cameras due to their unique asynchronous, binary data output.
• Current event camera calibration methods, using blinking patterns or image reconstruction, face deployment challenges and are susceptible to noise.

Purpose of the Study:

• To develop a novel, efficient, and robust calibration toolbox for event cameras.
• To address the limitations of existing calibration techniques in terms of speed, accuracy, and robustness.
• To enable reliable 3D perception and intrinsic parameter estimation for event cameras in diverse conditions.

Main Methods:

• E-Calib utilizes an asymmetric circle grid pattern, known for its robustness in out-of-focus scenarios.
• An efficient reweighted least squares (eRWLS) method is employed for sub-pixel accurate feature extraction of calibration pattern circles.
• A modified hierarchical clustering algorithm is developed to reliably detect the calibration grid amidst background noise.

Main Results:

• The proposed E-Calib method demonstrates superior performance across various event camera models and experimental conditions.
• Outperforms state-of-the-art methods in detection success rate, significantly reducing reprojection errors.
• Achieves higher accuracy in pose estimation compared to existing calibration techniques.

Conclusions:

• E-Calib provides a significant advancement in event camera calibration, offering a practical and effective solution.
• The toolbox enhances the reliability and accuracy of 3D perception for event-based systems.
• Paves the way for wider adoption of event cameras in industrial and real-world applications.