  The recent development of calibration algorithms has been driven into two
major directions: (1) an increasing accuracy of mathematical approaches and (2)
an increasing flexibility in usage by reducing the dependency on calibration
objects. These two trends, however, seem to be contradictory since the overall
accuracy is directly related to the accuracy of the pose estimation of the
calibration object and therefore demanding large objects, while an increased
flexibility leads to smaller objects or noisier estimation methods.
  The method presented in this paper aims to resolves this problem in two
steps: First, we derive a simple closed-form solution with a shifted focus
towards the equation of translation that only solves for the necessary hand-eye
transformation. We show that it is superior in accuracy and robustness compared
to traditional approaches. Second, we decrease the dependency on the
calibration object to a single 3D-point by using a similar formulation based on
the equation of translation which is much less affected by the estimation error
of the calibration object's orientation. Moreover, it makes the estimation of
the orientation obsolete while taking advantage of the higher accuracy and
robustness from the first solution, resulting in a versatile method for
continuous hand-eye calibration.
