A New Approach to Hand-Eye Calibration

Traditionally, hand-eye calibration has been done using point correspondences, reducing the problem to a matrix equation. This approach requires reliably detected and tracked points between images taken from fairly widespread locations. In this paper we present a completely new approach to performing hand-eye calibration. The novelty of the proposed method lies in the fact that instead of point correspondences, normal derivatives of the image flow field are used. Firstly, two different small translational motions are made, enabling the direction of the optical axis to be computed from image derivatives only. Secondly, two different rotational motions are made, enabling also the translational part of the hand-eye transformation to be estimated. Thus only four different motions are needed to calculate the hand-eye transformation. Finally, experiments are given using simulated data.