Collimator-assisted high-precision calibration method for event cameras
This addresses the problem of precise calibration for event cameras in applications like robotics or surveillance, though it appears incremental as it builds on existing calibration techniques.
The paper tackles the challenge of geometric calibration for event cameras in long-range measurement scenarios by proposing a collimator-assisted method using flickering star-based patterns, demonstrating superior accuracy and reliability compared to existing methods in real-world experiments.
Event cameras are a new type of brain-inspired visual sensor with advantages such as high dynamic range and high temporal resolution. The geometric calibration of event cameras, which involves determining their intrinsic and extrinsic parameters, particularly in long-range measurement scenarios, remains a significant challenge. To address the dual requirements of long-distance and high-precision measurement, we propose an event camera calibration method utilizing a collimator with flickering star-based patterns. The proposed method first linearly solves camera parameters using the sphere motion model of the collimator, followed by nonlinear optimization to refine these parameters with high precision. Through comprehensive real-world experiments across varying conditions, we demonstrate that the proposed method consistently outperforms existing event camera calibration methods in terms of accuracy and reliability.