تقرير
TurkEyes: A Web-Based Toolbox for Crowdsourcing Attention Data
| العنوان: | TurkEyes: A Web-Based Toolbox for Crowdsourcing Attention Data |
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| المؤلفون: | Newman, Anelise, McNamara, Barry, Fosco, Camilo, Zhang, Yun Bin, Sukhum, Pat, Tancik, Matthew, Kim, Nam Wook, Bylinskii, Zoya |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Human-Computer Interaction |
| الوصف: | 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. Comment: To appear in CHI 2020. Code available at http://turkeyes.mit.edu/ |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2001.04461 |
| رقم الأكسشن: | edsarx.2001.04461 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |