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Abstract

Visualization enables scientists to transform data in its raw form to a visual form that will facilitate discoveries and insights. Although there are advantages for displaying inherently 3-dimensional (3D) data in immersive environments, those advantages are hampered by the challenges involved in selecting volumes of that data for exploration or analysis. Selection involves the user identifying a set of points for a specific task. This paper preliminary data collection on natural user actions for volume selection. This paper also presents a research agenda outlining an extension for volume selection classification, as well as challenges, for designing components for a direct selection of volumes of data points.

Keywords

HCI methods and theories Human Centered Design and User Centered Design Interaction design Visualization methods and techniques 

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References

  1. 1.
    Ayala, D., Pla, N., Vigo, M.: Splat representation of parametric surfaces. Computing 79, 101–108 (2007)CrossRefzbMATHMathSciNetGoogle Scholar
  2. 2.
    Becker, R.A., Cleveland, W.S.: Brushing scatterplots. Technometrics 29(2), 127–142 (1987)CrossRefMathSciNetGoogle Scholar
  3. 3.
    Laha, B., Bowman, D.A.: Volume cracker: a bimanual 3D interaction technique for analysis of raw volumetric data. In: Proceedings of the 1st Symposium on Spatial User Interaction (SUI 2013), pp. 61–68. ACM, New York (2013)CrossRefGoogle Scholar
  4. 4.
    Bowman, D., Kruijff, E., LaViola, J., Poupyrev, I.: 3D User Interfaces: Theory and Practice. Addison-Wesley, Boston (2004)Google Scholar
  5. 5.
    Elmqvist, N., Dragicevic, P., Fekete, J.: Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation. IEEE Transactions on Visualization and Computer Graphics 14(6), 1141–1148 (2008)CrossRefGoogle Scholar
  6. 6.
    Evans, F., Volz, W., Dorn, G., Frohlich, B., Roberts, D.M.: Future trends in oil and gas visualization. In: VIS 2002: Proceedings of the Conference on Visualization 2002, pp. 55–62. IEEE Computer Society, Washington, DC (2002)Google Scholar
  7. 7.
    Frohlich, B., Barrass, S., Zehner, B., Plate, J., Gobel, M.: Exploring geo-scientific data in virtual environments. In: Proceedings of IEEE Visualization, pp. 169–173 (1999)Google Scholar
  8. 8.
    Grossman, T., Balakrishnan, R.: The design and evaluation of selection techniques for 3D volumetric displays. In: UIST 2006, pp. 3–12. ACM Press (2006)Google Scholar
  9. 9.
    Grossman, T., Wigdor, D., Balakrishnan, R.: Multi-finger gestural interaction with 3d volumetric displays. In: UIST 2004, pp. 61–70. ACM Press (2004)Google Scholar
  10. 10.
    Gruchalla, K.: Immersive well-path editing: investigating the added value of immersion. IEEE Virtual Reality, 157–164 (2004)Google Scholar
  11. 11.
    Hansen, C.D., Johnson, C.R. (eds.): The Visualization Handbook, p. 120. Elsevier (2005)Google Scholar
  12. 12.
    Jang, J., Ribarsky, W., Shaw, C.D., Faust, N.: View-Dependent Multiresolution Splatting of Non-Uniform Data. In: Proceedings of the Symposium on Data Visualization. ACM International Conference Proceeding Series, vol. 22, pp. 125–ff (2002)Google Scholar
  13. 13.
    Janicke, H., Bottinger, M., Scheuermann, G.: Brushing of attribute clouds for the visualization of multivariate data. IEEE Transactions on Visualization and Computer Graphics 14(6), 1459–1466 (2008)CrossRefGoogle Scholar
  14. 14.
    Johnson, C., Moorhead, R., Munzner, T., Pfister, H., Rheingans, P., Yoo, T.S.: NIH/NSF Visualization Research Challenges Report. IEEE Press (2006)Google Scholar
  15. 15.
    Kalaiah, A., Varshney, A.: Modeling and Rendering of Points with Local Geometry. IEEE Transactions on Visualization and Computer Graphics 9(1), 30–42 (2003)Google Scholar
  16. 16.
    Kreylos, O., Bawden, G., Bernardin, T., Billen, M., Cowgill, E., Gold, R., Hamann, B., Jadamec, M., Kellogg, L., Staadt, O., Sumner, D.: Enabling scientific workflows in virtual reality. In: Proceedings of the 2006 ACM International Conference on Virtual Reality Continuum and its Applications, VRCIA 2006, pp. 155–162. ACM, New York (2006)CrossRefGoogle Scholar
  17. 17.
    Kreylos, O.: Environment-Independent VR Development. In: Bebis, G., et al. (eds.) ISVC 2008, Part I. LNCS, vol. 5358, pp. 901–912. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  18. 18.
    Kreylos, O., Bawden, G.W., Kellogg, L.H.: Immersive visualization and analysis of LiDAR data. In: Bebis, G., et al. (eds.) ISVC 2008, Part I. LNCS, vol. 5358, pp. 846–855. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  19. 19.
    Kopper, R., Bacim, F., Bowman, D.A.: Rapid and Accurate 3D Selection by Progressive Refinement. In: Proc. 3DUI, pp. 67–74. IEEE Computer Society, Los Alamitos (2011)Google Scholar
  20. 20.
    Licklider, J.C.R.: Man-computer symbiosis. IRE Transactions on Human Factors in Electronics (1), 4–11 (1960)Google Scholar
  21. 21.
    Lin, C., Loftin, R., Stark, T.: Virtual reality for geosciences visualization. In: Proceedings of 3rd Asia Pacific Computer Human Interaction Conference, pp. 196–201 (1998)Google Scholar
  22. 22.
    Lin, C., Loftin, R., Nelson, J.: Interaction with geoscience data in an immersive environment. In: Proceedings of IEEE Virtual Reality, pp. 55–62 (2000)Google Scholar
  23. 23.
    Liang, J., Green, M.: JDCAD: A Highly Interactive 3D Modeling System. Computers & Graphics 18(4), 499–506 (1994)CrossRefGoogle Scholar
  24. 24.
    Yu, L., Efstathiou, K., Isenberg, P., Isenberg, T.: Efficient Structure-Aware Selection Techniques for 3D Point Cloud Visualizations with 2DOF Input. IEEE Transactions on Visualization and Computer Graphics 18(12), 2245–2254 (2012)CrossRefGoogle Scholar
  25. 25.
    Lucas, J.F., Bowman, D.A.: Design and Evaluation of 3D Multiple Object Selection Techniques. Report, Virginia Polytechnic Institute and State University, USA (2005)Google Scholar
  26. 26.
    Olwal, A., Feiner, S.: The flexible pointer- An interaction technique for selection in augmented and virtual reality. In: UIST 2003, pp. 81–82 (2003)Google Scholar
  27. 27.
    Sherman, W.R., Craig, A.B.: Understanding Virtual Reality: Interface, Application, and Design. Morgan Kaufmann Publishers Inc. (2002)Google Scholar
  28. 28.
    Tory, M., Kirkpatrick, A., Atkins, M.S., Moller, T.: Visualization Task Performance with 2D, 3D, and Combination Displays. IEEE Transactions on Visualization and Computer Graphics 12(1), 2–13 (2006)Google Scholar
  29. 29.
    Ulinski, A., Wartell, Z., Hodges, L.F.: Bimanual Task Division Preferences for Volume Selection. In: Spencer, S.N. (ed.) Proceedings of the 2007 ACM Symposium on Virtual Reality Software and Technology, VRST 2007, pp. 217–218. ACM, New York (2007)CrossRefGoogle Scholar
  30. 30.
    Ulinski, A., Zanbaka, C., Wartell, Z., Goolkasian, P., Hodges, L.F.: Two Handed Selection Techniques for Volumetric Data. In: Proceedings of the 3D User Interfaces, 3DUI 2007, pp. 107–114. IEEE Computer Society (2007)Google Scholar
  31. 31.
    Ulinski, A.: Ph.D. Dissertation, UNC-Charlotte (2008)Google Scholar
  32. 32.
    Ware, C., Rose, J.: Rotating virtual objects with real handles. ACM Trans. Comput.-Hum. Interact. 6, 162–180 (1999)CrossRefGoogle Scholar
  33. 33.
    Yi, J.S., Kang, Y., Stasko, J.T., Jacko, J.A.: Toward a Deeper Understanding of the Role of Interaction in Information Visualization. In: Proceedings of InfoVis 2007, vol. 13, pp. 1224–1231 (2007)Google Scholar
  34. 34.
    Yu, L., Efstathiou, K., Isenberg, P., Isenberg, T.: Efficient Structure-Aware Selection Techniques for 3D Point Cloud Visualizations with 2DOF Input. IEEE Transactions on Visualization and Computer Graphics 18(12), 2245–2254 (2012)CrossRefGoogle Scholar
  35. 35.
    Zhang, J.H., Liang, C., Li, G.Q.: 3D Primitive Picking on GPU. Journal of Engineering Graphics 1, 10 (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Amy Banic
    • 1
  1. 1.University of WyomingUSA

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