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Context-Preserving Visual Links
Dec. 2011 (vol. 17 no. 12)
pp. 2249-2258
Markus Steinberger, Graz University of Technology
Manuela Waldner, Graz University of Technology
Marc Streit, Graz University of Technology
Alexander Lex, Graz University of Technology
Dieter Schmalstieg, Graz University of Technology
Evaluating, comparing, and interpreting related pieces of information are tasks that are commonly performed during visual data analysis and in many kinds of information-intensive work. Synchronized visual highlighting of related elements is a well-known technique used to assist this task. An alternative approach, which is more invasive but also more expressive is visual linking in which line connections are rendered between related elements. In this work, we present context-preserving visual links as a new method for generating visual links. The method specifically aims to fulfill the following two goals: first, visual links should minimize the occlusion of important information; second, links should visually stand out from surrounding information by minimizing visual interference. We employ an image-based analysis of visual saliency to determine the important regions in the original representation. A consequence of the image-based approach is that our technique is application-independent and can be employed in a large number of visual data analysis scenarios in which the underlying content cannot or should not be altered. We conducted a controlled experiment that indicates that users can find linked elements in complex visualizations more quickly and with greater subjective satisfaction than in complex visualizations in which plain highlighting is used. Context-preserving visual links were perceived as visually more attractive than traditional visual links that do not account for the context information.

[1] A. Cockburn, A. Karlson, and B. B. Bederson, A review of overview+detail, zooming, and focus+context interfaces. ACM Computing Surveys (CSUR), 41 (1): 1–31, 2008.
[2] C. Collins and S. Carpendale, VisLink: revealing relationships amongst visualizations. IEEE Transactions on Visualization and Computer Graphics (InfoVis '07), 13 (6): 1192–1199, 2007.
[3] C. Collins, G. Penn, and S. Carpendale, Bubble sets: Revealing set relations with isocontours over existing visualizations. IEEE Transactions on Visualization and Computer Graphics (InfoVis '09), 15 (6): 1009–1016, 2009.
[4] J. Fekete, D. Wang, N. Dang, A. Aris, and C. Plaisant, Interactive poster: Overlaying graph links on treemaps. In Proceedings of the IEEE Symposium on Information Visualization Conference Compendium (InfoVis '03), pages 82–83. IEEE Computer Society Press, 2003.
[5] M. L. Fredman and R. E. Tarjan, Fibonacci heaps and their uses in improved network optimization algorithms. Journal of the ACM (JACM), 34 (3): 596–615, 1987.
[6] E. R. Gansner, Y. Hu, S. North, and S. Carlos, Multilevel agglomerative edge bundling for visualizing large graphs. In Proceedings of the IEEE Symposium on Pacific Visualization (PacificVis '11). IEEE Computer Society Press, 2011.
[7] R. Hoffmann, P. Baudisch, and D. S. Weld, Evaluating visual cues for window switching on large screens. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '08), pages 929– 938.ACM Press, 2008.
[8] D. Holten, Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data. IEEE Transactions on Visualization and Computer Graphics (InfoVis '06), 12 (5): 741–748, 2006.
[9] D. Holten and J. van Wijk, Force-Directed edge bundling for graph visualization. Computer Graphics Forum, 28 (3): 983–990, 2009.
[10] L. Itti, C. Koch, and E. Niebur, A model of Saliency-Based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20: 1254–1259, 1998.
[11] A. Khan, J. Matejka, G. Fitzmaurice, and G. Kurtenbach, Spotlight: directing users' attention on large displays. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '05), page 791798. ACM Press, 2005.
[12] R. Kosara, S. Miksch, and H. Hauser, Semantic depth of field. In Proceedings of the IEEE Symposium on Information Visualization (InfoVis '01), pages 97–104. IEEE Computer Society Press, 2001.
[13] A. Lex, M. Streit, E. Kruijff, and D. Schmalstieg, Caleydo: Design and evaluation of a visual analysis framework for gene expression data in its biological context. In Proceeding of the IEEE Symposium on Pacific Visualization (PacificVis '10), pages 57–64. IEEE Computer Society Press, 2010.
[14] A. Lex, M. Streit, C. Partl, K. Kashofer, and D. Schmalstieg, Comparative analysis of multidimensional, quantitative data. IEEE Transactions on Visualization and Computer Graphics (InfoVis '10), 16 (6): 1027–1035, 2010.
[15] A. R. Martin and M. O. Ward, High dimensional brushing for interactive exploration of multivariate data. In Proceedings of the IEEE Conference on Visualization (Vis '95), page 271. IEEE Computer Society Press, 1995.
[16] E. Mendez, S. Feiner, and D. Schmalstieg, Focus and context in mixed reality by modulating first order salient features. In Smart Graphics, volume 6133 of Lecture Notes in Computer Science, pages 232–243. Springer, 2010.
[17] H. L. O'Brien and E. G. Toms, The development and evaluation of a survey to measure user engagement. Journal of the American Society for Information Science and Technology, 61 (1): 50–69, 2010.
[18] S. Palmer and I. Rock, Rethinking perceptual organization: the role of uniform connectedness. Psychonomic Bulletin and Review, 1 (1): 2955, 1994.
[19] C. I. E. Publication, Industrial Colour-Difference evaluation. 116-1995, CIE, 1995.
[20] J. Risch, R. May, S. Dowson, and J. Thomas, A virtual environment for multimedia intelligence data analysis. IEEE Computer Graphics and Applications, 16 (6): 33–41, 1996.
[21] R. Rosenholtz, Y. Li, and L. Nakano, Measuring visual clutter. Journal of Vision, 7 (2), 2007.
[22] J. Seo and B. Shneiderman, Interactively exploring hierarchical clustering results. Computer, 35 (7): 80–86, 2002.
[23] B. Shneiderman and A. Aris, Network visualization by semantic substrates. IEEE Transactions on Visualization and Computer Graphics (In-foVis '06), 12 (5): 733–740, 2006.
[24] M. Streit, M. Kalkusch, and D. Schmalstieg, Interactive visualization of metabolic pathways. In Poster Compendium of the IEEE Conference on Visualization (Vis '07). IEEE Computer Society Press, 2007.
[25] A. M. Treisman and G. Gelade, A feature-integration theory of attention. Cognitive Psychology, 12 (1): 97–136, 1980.
[26] E. Veas, E. Mendez, S. Feiner, and D. Schmalstieg, Directing attention and influencing memory with visual saliency modulation. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11). ACM Press, 2011.
[27] M. Waldner, W. Puff, A. Lex, M. Streit, and D. Schmalstieg, Visual links across applications. In Proceedings of the Conference on Graphics Interface (GI '10), pages 129–136. Canadian Human-Computer Communications Society, 2010.
[28] M. Waldner, M. Steinberger, R. Grasset, and D. Schmalstieg, Importance-Driven compositing window managment. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '11). ACM Press, 2011.
[29] C. Ware, Information visualization : perception for design. Morgan Kaufman, San Francisco CA, second edition, 2004.
[30] J. M. Wolfe, Visual search. In H. E. Pashler editor, Attention, pages 13–74. Psychology Press, 1998.
[31] J. M. Wolfe, What can million trials tell us about visual search? Psychological Science, 9 (1): 33–39, 1998.
[32] S. Zhai, J. Wright, T. Selker, and S. Kelin, Graphical means of directing user's attention in the visual interface. In Proceedings of the Conference on Human-Computer Interaction (INTERACT '97), pages 59–66. Chapman & Hall, 1997.
[33] C. Ziemkiewicz and R. Kosara, Laws of attraction: From perceptual forces to conceptual similarity. IEEE Transactions on Visualization and Computer Graphics (InfoVis '10), 16 (6): 1009–1016, 2010.

Index Terms:
Visual links, highlighting, connectedness, routing, image-based, saliency.
Citation:
Markus Steinberger, Manuela Waldner, Marc Streit, Alexander Lex, Dieter Schmalstieg, "Context-Preserving Visual Links," IEEE Transactions on Visualization and Computer Graphics, vol. 17, no. 12, pp. 2249-2258, Dec. 2011, doi:10.1109/TVCG.2011.183
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