Abstract

We propose an approach for external calibration of a 3D laser scanner with an omnidirectional camera system. The utility of an accurate calibration is that it allows for precise co-registration between the camera imagery and the 3D point cloud. This association can be used to enhance various state of the art algorithms in computer vision and robotics. The extrinsic calibration technique used here is similar to the calibration of a 2D laser range finder and a single camera as proposed by Zhang (2004), but has been extended to the case where we have a 3D laser scanner and an omnidirectional camera system. The procedure requires a planar checkerboard pattern to be observed simultaneously from the laser scanner and the camera system from a minimum of 3 views. The normal of the planar surface and 3D points lying on the surface constrain the relative position and orientation of the laser scanner and the omnidirectional camera system. These constraints can be used to form a non-linear optimization problem that is solved for the extrinsic calibration parameters and the covariance associated with the estimated parameters. Results are presented for a real world data set collected by a vehicle mounted with a 3D laser scanner and an omnidirectional camera system.

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