A Prototype for Data-Driven Visual Attention

Mounting evidence suggests that attentional mechanisms may be required to successfully perform many vision tasks. This paper presents an attentional prototype for early visual processing. Our model is composed of a processing hierarchy and an attention beam that traverses the hierarchy, passing through the regions of greatest interest and inhibiting the regions that are not relevant. The type of input to the prototype is not limited to visual stimuli. Aspects of attention such as localizing spatial regions of interest and ordering their importance are addressed; other aspects of attention such as the role of task guidance are encompassed by the model but are not detailed here. Simulations using high-resolution digitized images were conducted, with oriented edge information as the input to the model. The results connrm that this prototype is both robust and fast, and promises to be essential to any real-time vision system.