  Event cameras triggered a paradigm shift in the computer vision community
delineated by their asynchronous nature, low latency, and high dynamic range.
Calibration of event cameras is always essential to account for the sensor
intrinsic parameters and for 3D perception. However, conventional image-based
calibration techniques are not applicable due to the asynchronous, binary
output of the sensor. The current standard for calibrating event cameras relies
on either blinking patterns or event-based image reconstruction algorithms.
These approaches are difficult to deploy in factory settings and are affected
by noise and artifacts degrading the calibration performance. To bridge these
limitations, we present E-Calib, a novel, fast, robust, and accurate
calibration toolbox for event cameras utilizing the asymmetric circle grid, for
its robustness to out-of-focus scenes. The proposed method is tested in a
variety of rigorous experiments for different event camera models, on circle
grids with different geometric properties, and under challenging illumination
conditions. The results show that our approach outperforms the state-of-the-art
in detection success rate, reprojection error, and estimation accuracy of
extrinsic parameters.
