Employing a Computational Model to Reveal Stimulus-Driven Influences in Interfaces

Abstract

It is challenging to design complex interfaces that support efficient visual searches. It requires understanding how numerous sources of information contribute to attentional selection, along with an understanding of the tools and tasks used to study visual search. This work is intended to examine visual salience, a pre-attentive process often overlooked in traditional design approaches. Although the importance of visual salience in task-driven searches has been debated, recent evidence suggests this stimulus-driven property contributes to the guidance of attention. Computational modeling has proven effective in predicting the influence of salience (e.g., N-SEEV and Attentional Priority models). With advances in this area of research, continuing examination of the applications and limitations of computational salience models is warranted. Therefore, the present work also examines the predictive power of computational models in displays like web pages and mobile interfaces. Emphasis is placed on the role salience should play in optimizing interface search efficiency.