Using neural field dynamics in the context of attentional control

Abstract

We present an application of dynamic neural fields for selection and tracking in the attentional control part of an active vision system. We propose a novel two-stage selection mechanism, in which the fields are used for the first selection stage. We discuss different variants, introducing 3D neural fields and systems of interconnected fields. The dynamics can be shown to achieve important goals in active vision like robust selection, multi-object tracking, and spatiotemporal integration. © Springer-Verlag Berlin Heidelberg 2002.