A Visual Selection Mechanism Based on Network of Chaotic Wilson-Cowan Oscillators

In this paper, a Visual Selection Mechanism based on a lattice of coupled chaotic Wilson-Cowan oscillators is proposed. The oscillators representing each object in a given visual scene are synchronized to produce a chaotic trajectory. Cooperation and competition mechanisms are also introduced to accelerate oscillating frequency of the salient object as well as to slow down other objects in the same scene. The model can not only discriminate each object among others in a given visual scene, but also deliver the focus of attention to the salient object. In comparison to other visual selection approaches, this model presents at least two new features. First, it is able to highlight objects in complex forms, including those that are non-linear separable. Second, oscillators representing the salient object will jump from chaotic phase to periodic phase. This behavior matches well to biological experiments on pattern recognition of rabbit. Computer simulations are performed and the results show that the proposed model is promising as a Selection Mechanism embedded in a Visual Attention System.