We present a computational model for attention. It consists of an early parallel stage with preattentive cues followed by a later serial stage, where the cues are integrated. We base the model on disparity image flow and motion. As one of the several possibilities we choose a depth-based criterion to integrate these cues, in such a way that the attention is maintained to the closest moving object. We demonstrate the technique by experiments in which a moving observer selectively mask our different moving objects in real scenes.

We present a binocular active vision system that can attend to and fixate a moving target. Our system has an open and expandable design and it forms the first steps of a long term effort towards developing an active observer using vision to interact with the environment, in particular capable of figure-ground segmentation. We also present partial real-time implementations of this system and show their performance in real-world situations together with motor control. In pursuit we particularly focus on occlusions of other targets, both stationary and moving, and integrate three cues, ego-motion, target motion and target disparity, to obtain an overall robust behavior. An active vision system must be open, expandable, and operate with whatever data are available momentarily. It must also be equipped with means and methods to direct and change its attention. This system is therefore equipped with motion detection for changing attention and pursuit for maintaining attention, both of which run concurrently.>