Relative Pose Estimation and Fusion of Omnidirectional and Lidar Cameras

This paper presents a novel approach for the extrinsic parameter estimation of omnidirectional cameras with respect to a 3D Lidar coordinate frame. The method works without specific setup and calibration targets, using only a pair of 2D-3D data. Pose estimation is formulated as a 2D-3D nonlinear shape registration task which is solved without point correspondences or complex similarity metrics. It relies on a set of corresponding regions, and pose parameters are obtained by solving a small system of nonlinear equations. The efficiency and robustness of the proposed method was confirmed on both synthetic and real data in urban environment.