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. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Download full-text PDF

Source
http://dx.doi.org/10.1037/xhp0000593DOI Listing

Publication Analysis

Top Keywords

shape
4
shape attention
4
attention spotlight?
4
spotlight? computing
4
computing saliency
4
saliency proto-objects
4
proto-objects predicts
4
predicts fixations
4
fixations scene
4
scene viewing
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!