  Eye movements provide insight into what parts of an image a viewer finds most
salient, interesting, or relevant to the task at hand. Unfortunately, eye
tracking data, a commonly-used proxy for attention, is cumbersome to collect.
Here we explore an alternative: a comprehensive web-based toolbox for
crowdsourcing visual attention. We draw from four main classes of
attention-capturing methodologies in the literature. ZoomMaps is a novel
"zoom-based" interface that captures viewing on a mobile phone. CodeCharts is a
"self-reporting" methodology that records points of interest at precise viewing
durations. ImportAnnots is an "annotation" tool for selecting important image
regions, and "cursor-based" BubbleView lets viewers click to deblur a small
area. We compare these methodologies using a common analysis framework in order
to develop appropriate use cases for each interface. This toolbox and our
analyses provide a blueprint for how to gather attention data at scale without
an eye tracker.
