Models of Bottom-up Attention and Saliency
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
Several computational architectures subserving this bottom-up, stimulus-driven, spatiotemporal deployment of attention are reviewed in this chapter, and an unusal application is described, to the objective evaluation of advertising designs.
Abstract
Visually conspicuous, or so-called salient, stimuli often have the capability of attracting focal visual attention toward their locations. Several computational architectures subserving this bottom-up, stimulus-driven, spatiotemporal deployment of attention are reviewed in this chapter. The resulting computational models have applications not only to the prediction of visual search psychophysics, but also, in the domain of machine vision, to the rapid selection of regions of interest in complex, cluttered visual environments. We describe an unusal such application, to the objective evaluation of advertising designs.
