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.