L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event Cameras
Kevin Ta, David Bruggemann, Tim Brödermann, Christos Sakaridis, Luc Van Gool
Abstract
As neuromorphic technology is maturing, its application to robotics and autonomous vehicle systems has become an area of active research. In particular, event cameras have emerged as a compelling alternative to frame-based cameras in low-power and latency-demanding applications. To enable event cameras to operate alongside staple sensors like lidar in perception tasks, we propose a direct, temporally-decoupled extrinsic calibration method between event cameras and lidars. The high dynamic range, high temporal resolution, and low-latency operation of event cameras are exploited to directly register lidar laser returns, allowing information-based correlation methods to optimize for the 6- DoF extrinsic calibration between the two sensors. This paper presents the first direct calibration method between event cameras and lidars, removing dependencies on frame-based camera intermediaries and/or highly-accurate hand measurements. Code: https://github.com/kev-in-ta/12e
BibTeX
@inproceedings{icra2023_l2elaserstoevent,
title = {L2E: Lasers to Events for 6-DoF Extrinsic Calibration of Lidars and Event Cameras},
author = {Kevin Ta and David Bruggemann and Tim Brödermann and Christos Sakaridis and Luc Van Gool},
booktitle = {ICRA 2023},
year = {2023}
}