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Part 1: Visualization of volume data and the need of interaction (Timo Ropinski)

Abstract

Within this part, we lay the foundation for the rest of the tutorial. We review common classes of interaction tasks in volume visualization, whereby we delineate direct from indirect interaction paradigms. To bring previous work into a common context, we will analyze interaction techniques by considering them as the method for changing parameters of volume visualizations, whereby the domain, in which the interaction is applied, plays a central role. We will further discuss how different paradigms can be used to either modify spatial parameters or to alter global, non-spatial parameters. Based on these observations and classifications of general interaction tasks, we will derive interaction tasks in the context of volume visualization. We will show how these tasks can be investigated from a semantic point of view or a technical point of view, e.g., selection vs. picking. From a technical perspective, we will derive and discuss the common basic demands these tasks have, and address challenges related to 2D and 3D interaction. Furthermore, we will discuss discipline-related specifics of these tasks, as they occur in many areas exploiting interactive visualization.

Relevant Literature:

  1. M. Brehmer, T. Munzner. A Multi-Level Typology of Abstract Visualization Tasks. IEEE TVCG, 19(12):2376-2385, 2013. [http://www.cs.ubc.ca/labs/imager/tr/2013/MultiLevelTaskTypology/brehmer_infovis13.pdf]
  2. B. Shneiderman. The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations. IEEE Symposium on Visual Languages, p. 336-343, Washington, 1996. [https://www.cs.umd.edu/~ben/papers/Shneiderman1996eyes.pdf]
  3. K.T. Nguyen, A. Ynnerman, T. Ropinski. Analyzing and Reducing DTI Tracking Uncertainty by Combining Deterministic and Stochastic Approaches. International Symposium on Visual Computing, pages 266-279, 2013. [http://scivis.itn.liu.se/publications/2013/NYR13//NYR13.pdf]
  4. S. Diepenbrock, T. Ropinski. From Imprecise User Input to Precise Vessel Segmentations. EG Visual Computing for Biology and Medicine - 2012. [http://scivis.itn.liu.se/publications/2012/DR12//preciseVesselSeg.pdf]
  5. S. Diepenbrock, T. Ropinski, K. Hinrichs. Context-Aware Volume Navigation. IEEE Pacific Visualization, 2011. [http://scivis.itn.liu.se/publications/2011/DRH11//pavis11-navigation.pdf]
  6. T. Ropinski, I. Viola, M. Biermann, H. Hauser, K. Hinrichs. Multimodal Visualization with Interactive Closeups. EGUK Theory and Practice of Computer Graphics, p. 17-24, 2009. [http://scivis.itn.liu.se/publications/2009/RVBHH09//tpcg09.pdf]
  7. J. Mensmann, T. Ropinski, K. Hinrichs. Interactive Cutting Operations for Generating Anatomical Illustrations from Volumetric Data Sets. Journal of WSCG, 16(2): 89-96, 2008. [http://scivis.itn.liu.se/publications/2008/MRH08//wscg08-deformation.pdf]
  8. T. Ropinski, J. Pra├čni, F. Steinicke, K. Hinrichs. Stroke-Based Transfer Function Design. IEEE/EG Volume and Point-Based Graphics, p. 41-48, 2008. [http://scivis.itn.liu.se/publications/2008/RPSH08//vg08.pdf]

Slides

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