Is there a shape to the attention spotlight? Computing saliency over proto-objects predicts fixations during scene viewing

Attention controls the selective routing of visual inputs for classification. This "spotlight" of attention has been assumed to be a Gaussian, but here we propose that this routing occurs in the form of a shape. We show that a model of attention control that spatially averages saliency values over proto-objects (POs), fragments of feature-similar visual space, is better able to predict the fixation density maps and scanpaths made during the free viewing of 384 natural scenes by 12 participants than comparable saliency models that do not consider shape. We further show that this image-computable PO model is nearly as good in predicting fixations (density and scanpaths) as a model of fixation prediction that uses hand-segmented object labels. We interpret these results as suggesting that the spotlight of attention has a shape, and that these shapes can be quantified as regions of space that we refer to as POs.