TurkEyes: A Web-Based Toolbox for Crowdsourcing Attention Data
This provides a scalable alternative for researchers needing attention data without eye trackers, though it is incremental as it builds on existing methodologies.
The authors tackled the cumbersome collection of eye tracking data by developing TurkEyes, a web-based toolbox with four crowdsourcing methodologies for gathering visual attention data, and compared them to determine appropriate use cases.
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.