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Exploring visual prominence of multi-channel highlighting in visualizations

Authors:

Manuela Waldner,

Alexey Karimov,

Eduard GröllerAuthors Info & Claims

SCCG '17: Proceedings of the 33rd Spring Conference on Computer Graphics

Article No.: 8, Pages 1 - 10

https://doi.org/10.1145/3154353.3154369

Published: 15 May 2017 Publication History

Abstract

Visualizations make rich use of multiple visual channels so that there are few resources left to make selected focus elements visually distinct from their surrounding context. A large variety of highlighting techniques for visualizations has been presented in the past, but there has been little systematic evaluation of the design space of highlighting. We explore highlighting from the perspective of visual marks and channels - the basic building blocks of visualizations that are directly controlled by visualization designers. We present the results from two experiments, exploring the visual prominence of highlighted marks in scatterplots: First, using luminance as a single highlight channel, we found that visual prominence is mainly determined by the luminance difference between the focus mark and the brightest context mark. The brightness differences between context marks and the overall brightness level have negligible influence. Second, multi-channel highlighting using luminance and blur leads to a good trade-off between highlight effectiveness and aesthetics. From the results, we derive a simple highlight model to balance highlighting across multiple visual channels and focus and context marks, respectively.

References

[1]

Ra Baer, Friederike Adler, Daniel Lenz, and Bernhard Preim. 2009. Perception-based Evaluation of Emphasis Techniques Used in 3D Medical Visualization. In 3D Medical Visualization. In: Vision, Modeling, and Visualization Workshop. 295--304.

[2]

Stefanie I. Becker. 2010. The role of target-distractor relationships in guiding attention and the eyes in visual search. Journal of Experimental Psychology: General 139, 2 (2010), 247--265.

[3]

Ronald Van den Berg, Frans W. Cornelissen, and Jos B. T. M. Roerdink. 2008. Perceptual Dependencies in Information Visualization Assessed by Complex Visual Search. ACM Transactions on Applied Perception (TAP) 4, 4 (Feb. 2008), 3:1--3:21.

Digital Library

[4]

L. D. Bergman, B. E. Rogowitz, and L. A. Treinish. 1995. A Rule-based Tool for Assisting Colormap Selection. In Proceedings of the 6th Conference on Visualization '95. IEEE Computer Society, 118--125.

Digital Library

[5]

Jacques Bertin. 1983. Semiology of Graphics: Diagrams, Networks, Maps. University of Wisconsin Press.

Digital Library

[6]

Mike Bostock. 2016. Bubble Chart. http://bl.ocks.org/mbostock/4063269 (March 2016).

[7]

Mike Bostock. 2017a. Choropleth. http://bl.ocks.org/mbostock/4060606 (2017).

[8]

Mike Bostock. 2017b. The Wealth & Health of Nations. https://bost.ocks.org/mike/nations/ (2017).

[9]

M. Bostock, V. Ogievetsky, and J. Heer. 2011. D3: Data-Driven Documents. IEEE Transactions on Visualization and Computer Graphics 17, 12 (Dec. 2011), 2301--2309.

Digital Library

[10]

Andy Cockburn, Amy Karlson, and Benjamin B. Bederson. 2009. A review of overview+detail, zooming, and focus+context interfaces. ACM Computing Surveys (CSUR) 41, 1 (Jan. 2009), 2:1--2:31.

Digital Library

[11]

Helmut Doleisch, Martin Gasser, and Helwig Hauser. 2003. Interactive feature specification for focus+context visualization of complex simulation data. In Proceedings of the symposium on Data visualisation 2003. Eurographics Association, 239--248.

Digital Library

[12]

John Duncan and Glyn W. Humphreys. 1989. Visual search and stimulus similarity. Psychological Review 96, 3 (1989), 433--458.

[13]

G. W. Furnas. 1986. Generalized fisheye views. In Proceedings of the SIGCHI conference on Human factors in computing systems. ACM, 16--23.

Digital Library

[14]

Gapminder. 2016. Gapminder: Unveiling the beauty of statistics for a fact based world view. http://www.gapminder.org/ (2016).

[15]

W. R. Garner. 2014. The Processing of Information and Structure. Psychology Press.

[16]

Aiko Hagiwara, Akihiro Sugimoto, and Kazuhiko Kawamoto. 2011. Saliency-based Image Editing for Guiding Visual Attention. In Proceedings of the 1st International Workshop on Pervasive Eye Tracking and Mobile Eye-based Interaction. ACM, 43--48.

Digital Library

[17]

K. Wm. Hall, C. Perin, P. G. Kusalik, C. Gutwin, and S. Carpendale. 2016. Formalizing Emphasis in Information Visualization. Computer Graphics Forum 35, 3 (June 2016), 717--737.

Digital Library

[18]

S. Haroz and D. Whitney. 2012. How Capacity Limits of Attention Influence Information Visualization Effectiveness. IEEE Transactions on Visualization and Computer Graphics 18, 12 (Dec. 2012), 2402--2410.

Digital Library

[19]

Mark Harrower and Cynthia A. Brewer. 2003. ColorBrewer.org: An Online Tool for Selecting Colour Schemes for Maps. The Cartographic Journal 40, 1 (June 2003), 27--37.

[20]

Helwig Hauser. 2006. Generalizing Focus+Context Visualization. In Scientific Visualization: The Visual Extraction of Knowledge from Data. Springer Berlin Heidelberg, 305--327.

[21]

L. Itti, C. Koch, and E. Niebur. 1998. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20, 11 (1998), 1254--1259.

Digital Library

[22]

Mikael Johannesson. 2001. Combining Integral and Separable Subspaces. In Twenty-Third Annual Conference of the Cognitive Science Society. Psychology Press, 447--452.

[23]

Azam Khan, Justin Matejka, George Fitzmaurice, and Gordon Kurtenbach. 2005. Spotlight: Directing Users' Attention on Large Displays. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 791--798.

Digital Library

[24]

Youngmin Kim and A. Varshney. 2006. Saliency-guided Enhancement for Volume Visualization. IEEE Transactions on Visualization and Computer Graphics 12, 5 (Sept. 2006), 925--932.

Digital Library

[25]

Robert Kosara, Helwig Hauser, and Donna Gresh. 2003. An Interaction View on Information Visualization. In State-of-the-Art Report. Proceedings of EUROGRAPHICS (2003). 123--137.

[26]

R. Kosara, S. Miksch, and H. Hauser. 2002. Focus+context taken literally. IEEE Computer Graphics and Applications 22, 1 (Jan. 2002), 22--29.

Digital Library

[27]

Sungkil Lee, M. Sips, and H.-P. Seidel. 2013. Perceptually Driven Visibility Optimization for Categorical Data Visualization. IEEE Transactions on Visualization and Computer Graphics 19, 10 (Oct. 2013), 1746--1757.

[28]

Jie Liang and Mao Lin Huang. 2010. Highlighting in Information Visualization: A Survey. In 14th International Conference Information Visualisation (IV) 2010. 79--85.

Digital Library

[29]

V. A. Mateescu and I. V. Bajic. 2016. Visual Attention Retargeting. IEEE MultiMedia 23, 1 (Jan. 2016), 82--91.

Digital Library

[30]

Tamara Munzner. 2014. Visualization Analysis and Design. A K Peters/CRC Press.

[31]

Anthony C. Robinson. 2011. Highlighting in Geovisualization. Cartography and Geographic Information Science 38, 4 (Jan. 2011), 373--383.

[32]

E. Segel and J. Heer. 2010. Narrative Visualization: Telling Stories with Data. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1139--1148.

Digital Library

[33]

Markus Steinberger, Manuela Waldner, Alexander Lex, Marc Streit, and Dieter Schmalstieg. 2011. Context-Preserving Visual Links. IEEE Transactions on Visualization and Computer Graphics 17, 12 (2011), 2249--2258.

Digital Library

[34]

Stanley Smith Stevens. 1975. Psychophysics. Transaction Publishers.

[35]

H. Strobelt, D. Oelke, Bum Chul Kwon, T. Schreck, and H. Pfister. 2016. Guidelines for Effective Usage of Text Highlighting Techniques. IEEE Transactions on Visualization and Computer Graphics 22, 1 (Jan. 2016), 489--498.

Digital Library

[36]

Anne M. Treisman and Garry Gelade. 1980. A feature-integration theory of attention. Cognitive Psychology 12, 1 (Jan. 1980), 97--136.

[37]

Eduardo E. Veas, Erick Mendez, Steven K. Feiner, and Dieter Schmalstieg. 2011. Directing attention and influencing memory with visual saliency modulation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. ACM, 1471--1480.

Digital Library

[38]

Colin Ware. 2012. Information Visualization: Perception for Design. Elsevier.

Digital Library

[39]

Colin Ware and Robert Bobrow. 2004. Motion to Support Rapid Interactive Queries on Node-link Diagrams. ACM Transactions on Applied Perception (TAP) 1, 1 (July 2004), 3--18.

Digital Library

[40]

Shumin Zhai, Julie Wright, Ted Selker, and Sabra-Anne Kelin. 1997. Graphical Means of Directing Users' Attention in the Visual Interface. In Human-Computer Interaction INTERACT '97. Springer US, 59--66.

Digital Library

Cited By

Xie JLiu LWang LWang ZZhao KWang P(2024)Evaluating the Design Effectiveness of Radial Layout Glyph Visualizations for Multivariate Data: A Perception StudyProceedings of the 17th International Symposium on Visual Information Communication and Interaction10.1145/3678698.3678709(1-8)Online publication date: 11-Dec-2024
https://dl.acm.org/doi/10.1145/3678698.3678709
Lu KReda KDeussen OWang Y(2023)Interactive Context-Preserving Color Highlighting for Multiclass ScatterplotsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580734(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580734
Eschner JMindek PWaldner M(2023)Illustrative Motion Smoothing for Attention Guidance in Dynamic VisualizationsComputer Graphics Forum10.1111/cgf.1483642:3(361-372)Online publication date: 27-Jun-2023
https://doi.org/10.1111/cgf.14836
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Index Terms

Exploring visual prominence of multi-channel highlighting in visualizations
1. Computing methodologies
  1. Computer graphics
    1. Graphics systems and interfaces
      1. Perception
2. Human-centered computing
  1. Visualization
    1. Empirical studies in visualization

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Published In

cover image ACM Conferences

SCCG '17: Proceedings of the 33rd Spring Conference on Computer Graphics

May 2017

163 pages

ISBN:9781450351072

DOI:10.1145/3154353

Conference Chair:
Pavel Zemcik
Brno University of Technology
,
Editor:
Stephen N. Spencer
University of Washington
,
Program Chairs:
Jiri Bittner
Czech Technical University in Prague
,
Ivan Viola
Vienna University of Technology, Austria

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 15 May 2017

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Austrian Science Fund FWF
Vienna Science and Technology Fund WWTF

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SCCG '17

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SIGGRAPH

SCCG '17: Spring Conference on Computer Graphics 2017

May 15 - 17, 2017

Mikulov, Czech Republic

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Cited By

Xie JLiu LWang LWang ZZhao KWang P(2024)Evaluating the Design Effectiveness of Radial Layout Glyph Visualizations for Multivariate Data: A Perception StudyProceedings of the 17th International Symposium on Visual Information Communication and Interaction10.1145/3678698.3678709(1-8)Online publication date: 11-Dec-2024
https://dl.acm.org/doi/10.1145/3678698.3678709
Lu KReda KDeussen OWang Y(2023)Interactive Context-Preserving Color Highlighting for Multiclass ScatterplotsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580734(1-15)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580734
Eschner JMindek PWaldner M(2023)Illustrative Motion Smoothing for Attention Guidance in Dynamic VisualizationsComputer Graphics Forum10.1111/cgf.1483642:3(361-372)Online publication date: 27-Jun-2023
https://doi.org/10.1111/cgf.14836
Aigner WMiksch SSchumann HTominski CAigner WMiksch SSchumann HTominski C(2023)Crafting Visualizations of Time-Oriented DataVisualization of Time-Oriented Data10.1007/978-1-4471-7527-8_4(83-127)Online publication date: 22-Dec-2023
https://doi.org/10.1007/978-1-4471-7527-8_4
Barrera-Leon LCorno FDe Russis L(2022)How the Preattentive Process is Exploited in Practical Information Visualization Design: A ReviewInternational Journal of Human–Computer Interaction10.1080/10447318.2022.204913739:4(707-720)Online publication date: 19-Apr-2022
https://doi.org/10.1080/10447318.2022.2049137
Wu HAmirkhanov AGrossmann NKlein TKouřil DMiao HLuidolt LMindek PRaidou RViola IWaldner MGröller M(2021)Visualization working group at TU WienVisual Informatics10.1016/j.visinf.2021.02.003Online publication date: Mar-2021
https://doi.org/10.1016/j.visinf.2021.02.003

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