SceneCalib: Automatic Targetless Calibration of Cameras and Lidars in Autonomous Driving
This addresses the need for accurate sensor fusion in 3D perception for autonomous vehicles, offering an incremental improvement by automating a process that typically relies on manual calibration.
The paper tackles the problem of camera-to-lidar calibration in autonomous driving by introducing SceneCalib, a fully automatic method that calibrates extrinsic and intrinsic parameters without requiring calibration targets or human intervention, achieving robustness in outdoor environments.
Accurate camera-to-lidar calibration is a requirement for sensor data fusion in many 3D perception tasks. In this paper, we present SceneCalib, a novel method for simultaneous self-calibration of extrinsic and intrinsic parameters in a system containing multiple cameras and a lidar sensor. Existing methods typically require specially designed calibration targets and human operators, or they only attempt to solve for a subset of calibration parameters. We resolve these issues with a fully automatic method that requires no explicit correspondences between camera images and lidar point clouds, allowing for robustness to many outdoor environments. Furthermore, the full system is jointly calibrated with explicit cross-camera constraints to ensure that camera-to-camera and camera-to-lidar extrinsic parameters are consistent.