research-article

Incidental Visualizations: Pre-Attentive Primitive Visual Tasks

Authors:

Daniel GonçalvesAuthors Info & Claims

AVI '20: Proceedings of the 2020 International Conference on Advanced Visual Interfaces

Article No.: 25, Pages 1 - 9

https://doi.org/10.1145/3399715.3399841

Published: 02 October 2020 Publication History

Abstract

In InfoVis design, visualizations make use of pre-attentive features to highlight visual artifacts and guide users' perception into relevant information during primitive visual tasks. These are supported by visual marks such as dots, lines, and areas. However, research assumes our pre-attentive processing only allows us to detect specific features in charts. We argue that a visualization can be completely perceived pre-attentively and still convey relevant information. In this work, by combining cognitive perception and psychophysics, we executed a user study with six primitive visual tasks to verify if they could be performed pre-attentively. The tasks were to find: horizontal and vertical positions, length and slope of lines, size of areas, and color luminance intensity. Users were presented with very simple visualizations, with one encoded value at a time, allowing us to assess the accuracy and response time. Our results showed that horizontal position identification is the most accurate and fastest task to do, and the color luminance intensity identification task is the worst. We believe our study is the first step into a fresh field called Incidental Visualizations, where visualizations are meant to be seen at-a-glance, and with little effort.

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Cited By

Patel ABaxter WPorat T(2024)Toward Guidelines for Designing Holistic Integrated Information Visualizations for Time-Critical Contexts: Systematic ReviewJournal of Medical Internet Research10.2196/5808826(e58088)Online publication date: 20-Nov-2024
https://doi.org/10.2196/58088
Palomino-Flores PCristi-López RPaul D(2024)Unraveling the Truth: Investigating the Spread of Fake News on Facebook During the COVID-19 CrisisCommunication and Applied Technologies10.1007/978-981-99-7210-4_21(223-233)Online publication date: 23-Feb-2024
https://doi.org/10.1007/978-981-99-7210-4_21
Moreira JMendes DGonçalves D(2023)Incidental graphical perception: How marks and display time influence accuracyInformation Visualization10.1177/1473871623118921823:1(3-20)Online publication date: 11-Aug-2023
https://doi.org/10.1177/14738716231189218

Index Terms

Incidental Visualizations: Pre-Attentive Primitive Visual Tasks
1. Human-centered computing
  1. Visualization

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AVI '20: Proceedings of the 2020 International Conference on Advanced Visual Interfaces

September 2020

613 pages

ISBN:9781450375351

DOI:10.1145/3399715

Copyright © 2020 ACM.

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Published: 02 October 2020

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AVI '20: International Conference on Advanced Visual Interfaces

September 28 - October 2, 2020

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Cited By

Patel ABaxter WPorat T(2024)Toward Guidelines for Designing Holistic Integrated Information Visualizations for Time-Critical Contexts: Systematic ReviewJournal of Medical Internet Research10.2196/5808826(e58088)Online publication date: 20-Nov-2024
https://doi.org/10.2196/58088
Palomino-Flores PCristi-López RPaul D(2024)Unraveling the Truth: Investigating the Spread of Fake News on Facebook During the COVID-19 CrisisCommunication and Applied Technologies10.1007/978-981-99-7210-4_21(223-233)Online publication date: 23-Feb-2024
https://doi.org/10.1007/978-981-99-7210-4_21
Moreira JMendes DGonçalves D(2023)Incidental graphical perception: How marks and display time influence accuracyInformation Visualization10.1177/1473871623118921823:1(3-20)Online publication date: 11-Aug-2023
https://doi.org/10.1177/14738716231189218

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