Web pages: What can you see in a single fixation?
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41235_2018_Article_99.pdf
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8.23 MB
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Author(s)
Jahanian, Ali
Keshvari, Shaiyan O
Rosenholtz, Ruth Ellen
Date Issued
May 2018
Journal
Cognitive Research: Principles and Implications
Publisher
Springer International Publishing
Citation
Jahanian, Ali, Shaiyan Keshvari and Ruth Rosenholtz. "Web pages: What can you see in a single fixation?" Cognitive Research: Principles and Implications (2018) 3:1-14.
Version
Final published version
Abstract
Research in human vision suggests that in a single fixation, humans can extract a significant amount of information from a natural scene, e.g. the semantic category, spatial layout, and object identities. This ability is useful, for example, for quickly determining location, navigating around obstacles, detecting threats, and guiding eye movements to gather more information. In this paper, we ask a new question: What can we see at a glance at a web page – an artificial yet complex “real world” stimulus? Is it possible to notice the type of website, or where the relevant elements are, with only a glimpse? We find that observers, fixating at the center of a web page shown for only 120 milliseconds, are well above chance at classifying the page into one of ten categories. Furthermore, this ability is supported in part by text that they can read at a glance. Users can also understand the spatial layout well enough to reliably localize the menu bar and to detect ads, even though the latter are often camouflaged among other graphical elements. We discuss the parallels between web page gist and scene gist, and the implications of our findings for both vision science and human-computer interaction.
Subjects
Gist, At a glance, Web page gist, Layout, Ad, Web design, Visual perception
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Department of Mechanical Engineering
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Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1186/s41235-018-0099-2
