Abstract-In this paper, we describe a new approach for the extrinsic calibration of a camera with a 3D laser range finder, that can be done on the fly. This approach does not require any calibration object. Only few point correspondences are used, which are manually selected by the user from a scene viewed by the two sensors. The proposed method relies on a novel technique to visualize the range information obtained from a 3D laser scanner. This technique converts the visually ambiguous 3D range information into a 2D map where natural features of a scene are highlighted. We show that by enhancing the features the user can easily find the corresponding points of the camera image points. Therefore, visually identifying lasercamera correspondences becomes as easy as image pairing. Once point correspondences are given, extrinsic calibration is done using the well-known PnP algorithm followed by a nonlinear refinement process. We show the performance of our approach through experimental results. In these experiments, we will use an omnidirectional camera. The implication of this method is important because it brings 3D computer vision systems out of the laboratory and into practical use.
Scaramuzza et al. REF propose to map 3D range information collected with a 3D tilting laser range finder into a 2D map (called Bearing Angle image) that highlights salient points of a scene thus the user can manually associate points between the two sensors in an easy way.
Extrinsic self calibration of a camera and a 3D laser range finder from natural scenes
2007 IEEE/RSJ International Conference on Intelligent Robots and Systems
2007 IEEE/RSJ International Conference on Intelligent Robots and Systems
Computer Science