Extrinsic Calibration Parameter

Extrinsic calibration parameters define the spatial relationship between different sensors in a multi-sensor system, a crucial aspect for accurate data fusion and robust perception. Current research focuses on developing automated and precise calibration methods, employing techniques like keypoint-based optimization, co-planar constraints leveraging LiDAR and camera data, and deep learning architectures (including neural networks and evolution strategies) to overcome challenges posed by noisy data or dynamic environments. Accurate extrinsic calibration is essential for applications ranging from autonomous driving and robotics to augmented reality and 3D reconstruction, improving the reliability and performance of these systems.