The Reflection Layer Extension to the Stereoscopic Highlight Technique for Node-Link Diagrams: An Empirical Study

  • Ragaad AlTarawneh
  • Jens Bauer
  • Shah Rukh Humayoun
  • Patric Keller
  • Achim Ebert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8034)

Abstract

The stereoscopic highlighting technique is a new emerging technique that supports using the depth cue in 3D devices to encode some attributes in general node-link diagrams. In this paper, we extend the original stereoscopic highlighting technique by adding an extra reflection layer at the bottom of the graph to help users detecting the highlighted nodes faster and more accurate. We measure the accuracy of this extension in the technique by evaluating the users’ ability of reading the variation of nodes depth values using the proposed reflection layer. We carried out a controlled user-study. The results show that using the depth cue in stereoscopic devices is readable for medium data sizes with at most three or four different layers without the reflection layer, while they were able to read more complicated configurations through the support of the reflection layer with higher accuracy.

Keywords

Stereoscopic Highlighting Technique Node-Link Diagrams Information Visualization 

References

  1. 1.
    Alper, B., Hllerer, T., Kuchera-Morin, J., Forbes, A.: Stereoscopic highlighting: 2d graph visualization on stereo displays. IEEE Trans. Vis. Comput. Graph. 17, 2325–2333 (2011)CrossRefGoogle Scholar
  2. 2.
    Ware, C., Franck, G.: Evaluating stereo and motion cues for visualizing information nets in three dimensions. ACM Trans. Graph. 15, 121–140 (1996)CrossRefGoogle Scholar
  3. 3.
    Ware, C., Bobrow, R.: Supporting visual queries on medium-sized nodelink diagrams. Information Visualization 4, 49–58 (2005)CrossRefGoogle Scholar
  4. 4.
    Ware, C.: Information Visualization: Perception for Design (Interactive Technologies), 1st edn. Morgan Kaufmann (2000)Google Scholar
  5. 5.
    AlTarawneh, R., Bauer, J., Humayoun, S.R., Keller, P., Ebert, A.: The extended stereoscopic highlighting technique for node-link diagrams: An empirical study. In: Proceedings of the 14th IASTED International Conference on Computer Graphics and Imaging (CGIM 2013), Innsbruck, Austria (2013)Google Scholar
  6. 6.
    Munzner, T.: H3: laying out large directed graphs in 3d hyperbolic space. In: Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis 1997), p. 2. IEEE Computer Society, Washington, DC (1997)Google Scholar
  7. 7.
    Robertson, G.G., Mackinlay, J.D., Card, S.K.: Cone trees: animated 3d visualizations of hierarchical information. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI 1991), pp. 189–194. ACM, New York (1991)Google Scholar
  8. 8.
    Tanaka, Y., Okada, Y., Niijima, K.: Treecube: Visualization tool for browsing 3d multimedia data. In: International Conference on Information Visualisation, p. 427 (2003)Google Scholar
  9. 9.
    van Wijk, J.J., van de Wetering, H.: Cushion treemaps: Visualization of hierarchical information (1999)Google Scholar
  10. 10.
    Cockburn, A., McKenzie, B.: Evaluating the effectiveness of spatial memory in 2d and 3d physical and virtual environments. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Changing our World, Changing Ourselves (CHI 2002), pp. 203–210. ACM, New York (2002)CrossRefGoogle Scholar
  11. 11.
    Grossman, T., Balakrishnan, R.: An evaluation of depth perception on volumetric displays. In: Proceedings of the Working Conference on Advanced Visual Interfaces (AVI 2006), pp. 193–200. ACM, New York (2006)CrossRefGoogle Scholar
  12. 12.
    Peterson, S.D., Axholt, M., Ellis, S.R.: Technical section: Objective and subjective assessment of stereoscopically separated labels in augmented reality. Comput. Graph. 33, 23–33 (2009)CrossRefGoogle Scholar
  13. 13.
    Robertson, G.G., Mackinlay, J.D., Card, S.K.: Cone Trees: animated 3D visualizations of hierarchical information. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems: Reaching Through Technology, CHI 1991, pp. 189–194. ACM, New York (1991)CrossRefGoogle Scholar
  14. 14.
    Deller, M., Ebert, A., Agne, S., Steffen, D.: Guiding attention in information-rich virtual environments. In: International Association of Science and Technology for Development (IASTED), pp. 310–315. ACTA Press (2008)Google Scholar
  15. 15.
    Collins, C., Carpendale, S.: Carpendale s: Vislink: revealing relationships amongst visualizations. IEEE Trans. Vis. Comput. Graph. (2007)Google Scholar
  16. 16.
    Eades, P., Feng, Q.W.: Multilevel Visualization of Clustered Graphs. In: North, S.C. (ed.) GD 1996. LNCS, vol. 1190, pp. 101–112. Springer, Heidelberg (1997)CrossRefGoogle Scholar
  17. 17.
    Brandes, U., Dwyer, T., Schreiber, F.: Visualizing related metabolic pathways in two and a half dimensions (2003)Google Scholar
  18. 18.
    Marr, D.: Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. Henry Holt and Co., Inc., New York (1982)Google Scholar
  19. 19.
    Dix, A., Finlay, J.E., Abowd, G.D., Beale, R.: Human-Computer Interaction, 3rd edn. Prentice-Hall, Inc., Upper Saddle River (2003)Google Scholar
  20. 20.

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ragaad AlTarawneh
    • 1
  • Jens Bauer
    • 1
  • Shah Rukh Humayoun
    • 1
  • Patric Keller
    • 2
  • Achim Ebert
    • 1
  1. 1.Computer Graphics and HCI GroupUniversity of KaiserslauternGermany
  2. 2.Software Engineering: Dependability GroupUniversity of KaiserslauternGermany

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