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Part 2: Direct Manipulation (Alexander Wiebel)

Abstract

Interaction with and manipulation of volumetric renderings and volumetric data are naturally non-trivial tasks when carried out on common 2D displays with mouse and keyboard input. This part will concentrate on techniques which take the provided 2D input and translate it into application-specific direct 3D actions and manipulations regarding the volume. Input types we will discuss include points (picking), lines (sketching) or regions (marking). Depending on the user task at hand, semantics of the resulting 3D actions range from simple selection of positions, lines and surfaces in 3D, to segmentation, labeling, 3D painting, and adaption of the transfer function or the data themselves. We will give a detailed description of the possibly needed additional or meta data for each technique. An overview of common applications of the mentioned techniques for imaging and simulation data from medicine and natural sciences will demonstrate the utility of the techniques.

Relevant Literature:

  1. A. Wiebel, F. M. Vos, D. Foerster, H.-C. Hege. WYSIWYP: What You See Is What You Pick. IEEE TVCG, 18(12):2236-2244, 2012. [http://forschung.awmw.org/PDF/wiebel_2012_SciVis.pdf]
  2. S. Owada, F. Nielsen, T. Igarashi. Volume catcher. In Proceedings of the 2005 Symposium on interactive 3D graphics and games, I3D ’05, p. 111–116, New York, USA, 2005. [http://dx.doi.org/10.1145/1053427.1053445]
  3. L. Yu, K. Efstathiou, P. Isenberg, T. Isenberg. Efficient structure-aware selection techniques for 3D point cloud visualizations with 2DOF input. IEEE TVCG, 18(12):2245-2254, Dec. 2012. [http://tobias.isenberg.cc/VideosAndDemos/Yu2012ESA]
  4. H. Peng, et al.. Virtual finger boosts three-dimensional imaging and microsurgery as well as terabyte volume image visualization and analysis. Nature Communications 5, Article number: 4342, 2014. [https://dx.doi.org/doi:10.1038/ncomms5342]
  5. S. Stoppel, H.-C. Hege, A. Wiebel. Visibility-Driven Depth Determination of Surface Patches in Direct Volume Rendering. EuroVis Short Papers 2014, p. 97-101, Eurographics Association, 2014. [http://dx.doi.org/10.2312/eurovisshort.20141164]
  6. K. Bürger, J. Krüger, R. Westermann. Direct Volume Editing. IEEE TVCG, 14(6):1388-1395, 2008. [http://dx.doi.org/10.1109/TVCG.2008.120]
  7. H. Guo, N. Mao, X. Yuan. WYSIWYG (What You See is What You Get) Volume Visualization. IEEE TVCG, 17(12):2106-2114, 2011. [http://dx.doi.org/10.1109/TVCG.2011.261]
  8. P. Kohlmann, S. Bruckner, A. Kanitsar, M. E. Gröller. Contextual Picking of Volumetric Structures. In Proceedings of IEEE Pacific Visualization, p. 185–192, 2009. [http://www.ii.uib.no/vis/team/bruckner/publication/Kohlmann-2009-CPV]
  9. 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]
  10. T. Ropinski, J. Praßni, F. Steinicke, K. Hinrichs. Stroke-Based Transfer Function Design. IEEE/EG International Symposium on Volume and Point-Based Graphics, page 41-48 - 2008. [http://viscg.uni-muenster.de/publications/2008/RPSH08/]
  11. L. Yu, K. Efstathiou, P. Isenberg, T. Isenberg. CAST: Effective and Efficient User Interaction for Context-Aware Selection in 3D Particle Clouds. IEEE TVCG, 22(1), Jan. 2016

Slides & Notes

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