Visual servoing is a framework for achieving the tight coupling of camera movements and information from images. We consider a typical visual servoing approach that uses geometric information about image features for controlling the position and attitude of a camera. We extend the applicability of this approach by using image motion information. To this end, we present two different approaches to visual tasks that use motion information. The first one uses the focus of expansion. The second one incorporates the parameters of the 2D affine motion model in control equations. We illustrate both these approaches by means of a task to align the optical axis of the camera with the unknown direction of translational motion of the system on which it is mounted. We present results of simulation experiments, and real experiments done with a six DOF robot with a camera on its end-effector. The contributions of this work are in particular extending the visual servoing formalism beyond using just image features, and in general showing that a tight coupling between camera behavior and image motion is possible.