Comparative study of camera calibration algorithms with application to spacecraft navigation

Abstract

This paper deals with the problem of camera calibration based on 3D feature measurements. It occurs in industrial 3D measurement systems, as well as in autonomous navigation systems, where the estimation of motion parameters is required. We have selected the problem of extrinsic calibration (exterior orientation) of a camera that is looking at flat or almost flat surfaces (or terrain). This situation causes numerical and stability problems to many of the known calibration methods. To study the impact of flatness of the reference surface (or calibration target) on the calibration errors we have done a comparative study using sixteen available calibration procedures. The major emphasis was on robustness with respect to 3D measurement errors and sensitivity to flatness. A new calibration method is also investigated, which can be used independently of whether the calibration reference surface is flat, almost flat, or rugged.