A Saliency Model Predicts Fixations in Web Interfaces

User interfaces are visually rich and complex. Consequently, it is difficult for designers to predict which locations will be attended to first within a display. Designers currently depend on eye tracking data to determine fixated locations, which are naturally associated with the allocation of attention. A computational saliency model can make predictions about where individuals are likely to fixate. Thus, we propose that the saliency model may facilitate successful interface development during the iterative design process by providing information about an interface’s stimulus-driven properties. To test its predictive power, the saliency model was used to render 50 web page screenshots; eye tracking data were gathered from participants on the same images. We found that the saliency model predicted fixated locations within web page interfaces. Thus, using computational models to determine regions high in visual saliency during web page development may be a cost effective alternative to eye tracking. Author