Conference: CHI

Date: April 2020

Presenters: Anelise Newman, Barry McNamara, Camilo Fosco, Yun Bin Zhang, Pat Sukhum, Matthew Tancik, Nam Wook Kim, Zoya Bylinskii

Partner Institution(s): Massachusetts Institute of Technology, Harvard University, University of California Berkeley, Boston College

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.