Issue No.12 - Dec. (2012 vol.18)
pp: 2245-2254
Lingyun Yu , Univ. of Groningen, Groningen, Netherlands
K. Efstathiou , Univ. of Groningen, Groningen, Netherlands
P. Isenberg , INRIA, Sophia Antipolis, France
T. Isenberg , DIGITEO/INRIA, France
Data selection is a fundamental task in visualization because it serves as a pre-requisite to many follow-up interactions. Efficient spatial selection in 3D point cloud datasets consisting of thousands or millions of particles can be particularly challenging. We present two new techniques, TeddySelection and CloudLasso, that support the selection of subsets in large particle 3D datasets in an interactive and visually intuitive manner. Specifically, we describe how to spatially select a subset of a 3D particle cloud by simply encircling the target particles on screen using either the mouse or direct-touch input. Based on the drawn lasso, our techniques automatically determine a bounding selection surface around the encircled particles based on their density. This kind of selection technique can be applied to particle datasets in several application domains. TeddySelection and CloudLasso reduce, and in some cases even eliminate, the need for complex multi-step selection processes involving Boolean operations. This was confirmed in a formal, controlled user study in which we compared the more flexible CloudLasso technique to the standard cylinder-based selection technique. This study showed that the former is consistently more efficient than the latter - in several cases the CloudLasso selection time was half that of the corresponding cylinder-based selection.
data visualisation, Boolean algebra, standard cylinder-based selection, efficient structure-aware selection, 3D point cloud visualizations, 2DOF input, data selection, spatial selection, 3D point cloud datasets, TeddySelection, 3D particle cloud, direct-touch input, bounding selection surface, complex multistep selection, Boolean operations, flexible CloudLasso technique, Shape analysis, Three dimensional displays, Estimation, Data visualization, direct-touch interaction, 3D interaction, spatial selection
Lingyun Yu, K. Efstathiou, P. Isenberg, T. Isenberg, "Efficient Structure-Aware Selection Techniques for 3D Point Cloud Visualizations with 2DOF Input", IEEE Transactions on Visualization & Computer Graphics, vol.18, no. 12, pp. 2245-2254, Dec. 2012, doi:10.1109/TVCG.2012.217
[1] F. Argelaguet and C. Andujar, Efficient 3D Pointing Selection in Cluttered Virtual Environments IEEE Computer Graphics and Applications, 29: 34-43, Nov./Dec. 2009. doi> 10.1109/MCG.2009.117
[2] W. Buxton., Chunking and Phrasing and the Design of Human-Computer Dialogues. In Proc. IFIP World Computer Congress, pp. 475-480, 1986.
[3] O. Daae Lampe and H. Hauser., Interactive Visualization of Streaming Data with Kernel Density Estimation. In Proc. IEEE Pacific Vis, pp. 171-178. IEEE Computer Society, Los Alamitos, 2011. doi> 10.1109/ PACIFICVIS.2011.5742387
[4] G. de Haan, M. Koutek, and F. H. Post., IntenSelect: Using Dynamic Object Rating for Assisting 3D Object Selection. In Proc. EGVE, pp. 201-209. Eurographics Association, Goslar, Germany, 2005. doi> 10.2312/ EGVE/IPT_EGVE2005/201–209
[5] G. De Lucia and J. Blaizot., The Hierarchical Formation of the Brightest Cluster Galaxies. Monthly Notices of the Royal Astronomical Society, 375(1): 2-14, Feb. 2007. doi> 10.1111/j.1365–2966.2006.11287.x
[6] H. Dehmeshki and W. Stuerzlinger., Intelligent Mouse-Based Object Group Selection. In Proc. Smart Graphics, 5166 of Lecture Notes in Computer Science, pp. 33-44. Springer-Verlag, Berlin / Heidelberg, 2008. doi> 10.1007/978–3-540–85412-8_4
[7] H. Dehmeshki and W. Stuerzlinger., GPSel: A Gestural Perceptual-Based Path Selection Technique. In Proc. Smart Graphics, 5531 of Lecture Notes in Computer Science, pp. 243-252. Springer-Verlag, Berlin / Heidelberg. 2009. doi> 10.1007/978–3-642–02115-2_21
[8] N. Elmqvist, P. Dragicevic, and J.-D. Fekete, Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation IEEE Transactions on Visualization and Computer Graphics, 14(6): 1141-1148, 2008. doi> 10.1109/TVCG.2008.153
[9] B. J Ferdosi, H. Buddelmeijer, S. C. Trager,M. H. F. Wilkinson,, and J. B., T. M. Roerdink., Comparison of Density Estimation Methods for Astronomical Datasets Astronomy & Astrophysics, 531:A114/1–16, July 2011. doi> 10.1051/0004–6361/201116878
[10] T. Grossman and R. Balakrishnan., The Design and Evaluation of Selection Techniques for 3D Volumetric Displays. In Proc. UIST, pp. 3-12. ACM, New York, 2006. doi> 10.1145/1166253.1166257
[11] T. Igarashi, S. Matsuoka, and H. Tanaka., Teddy: A Sketching Interface for 3D Freeform Design. In Proc. SIGGRAPH, pp. 409-416. ACM, New York, 1999. doi> 10.1145/311535.311602
[12] T. Isenberg and M. Hancock., Gestures vs. Postures: ‘Gestural’ Touch Interaction in 3D Environments. In Proc. 3DCHI (ACM CHI 2012 Workshop on “The 3rdDimension of CHI: Touching and Designing 3D User Interfaces”). PP. 53-61, 2012.
[13] B. Jackson, D. Coffey, and D. F. Keefe., Force Brushes: Progressive Data-Driven Haptic Selection and Filtering for Multi-Variate Flow Visualizations. In Short Paper Proc. EuroVis, pp. 7-11. Eurographics Association, Goslar, Germany, 2012. doi> 10.2312/PE/EuroVisShort/ EuroVisShort20 12/007–011
[14] D. F Keefe., Integrating Visualization and Interaction Research to Improve Scientific Workftows IEEE Computer Graphics and Applications, 30(2): 8-13, Mar./Apr. 2010. doi> 10.1109/MCG.2010.30
[15] D. F. Keefe,R. C. Zeleznik,, and D. H. Laidlaw., Tech-note: Dynamic Dragging for Input of 3D Trajectories. In Proc. 3DUI, pp. 51-54. IEEE Computer Society, Los Alamitos, 2008. doi> 10.1109/3DUI.2008. 4476591
[16] K. Kin, M. Agrawala, and T. DeRose., Determining the Benefits of Direct-Touch, Bimanual, and Multifinger Input on a Multitouch Workstation. In Proc. Graphics Interface, pp, 119-124. CIPS, Toronto, 2009.
[17] R. Kopper, F. Bacim, and D. A. Bowman., Rapid and Accurate 3D Selection by Progressive Refinement. In Proc. 3DUI, pp. 67-74. IEEE Computer Society, Los Alamitos, 2011. doi> 10.1109/3DUI.2011.5759219
[18] S. Lee, J. Seo, G. J. Kim,, and C.-M. Park., Evaluation of Pointing Techniques for Ray Casting Selection in Virtual Environments. In Proc. 3rdInt. SPIE Conf. on Virtual Reality and Its Application in Industry, pp. 38-44. SPIE. Bellingham. WA. USA. 2003. doi> 10.1117/12.497665
[19] J. Liang and M. Green, JDCAD: A Highly Interactive 3D Modeling System Computers & Graphics, 18(4): 499-506, July/Aug. 1994. doi> 10. 1016/0097–8493(94)90062–0
[20] W. E Lorensen and H. E. Cline., Marching Cubes: A High Resolution 3D Surface Construction Algorithm ACM SIGGRAPH Computer Graphics, 21(4): 163-169, July 1987. doi> 10.1145/37402.37422
[21] J. F. Lucas and D. A., Bowman. Design and Evaluation of 3D Multiple Object Selection Techniques. Report, Virginia Polytechnic Institute and State University, USA, 2005.
[22] C. D Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval. Cambridge University Press, Cambridge, 2008.
[23] K. Mühler, C. Tietjen, F. Ritter,, and B. Preim., The Medical Exploration Toolkit: An Efficient Support for Visual Computing in Surgical Planning and Training. IEEE Transactions on Visualization and Computer Graphics, 16(1): 133-146, Jan./Feb. 2010. doi> 10.1109/TVCG.2009.58
[24] S. Owada, F. Nielsen, and T. Igarashi., Volume Catcher. In Proc. I3D, pp. 111-116. ACM, New York, 2005. doi> 10.1145/1053427.1053445
[25] J. S. Pierce,A. S. Forsberg,M. J. Conway, S. Hong, R. C. Zeleznik,, and M. R. Mine., Image Plane Interaction Techniques in 3D Immersive Environments. In Proc. I3D, pp. 39-44. ACM, New York, 1997. doi> 10. 1145/253284.253303
[26] I. Poupyrev, M. Billinghurst, S. Weghorst,, and T. Ichikawa., The Go-Go Interaction Technique: Non-linear Mapping for Direct Manipulation in VR. In Proc. UIST, pp. 79-80. ACM, New York, 1996. doi> 10.1145/ 237091.237102
[27] A. J Sellen,G. P. Kurtenbach,, and W. A., S. Buxton., The Prevention of Mode Errors Through Sensory Feedback Human Computer Interaction, 7: 141-164, June 1992. doi> 10.1207/s15327051hci0702_1
[28] Smart Technologies Inc. Digital Vision Touch Technology. White paper, Feb. 2003.
[29] V. Springel, J. Wang, M. Vogelsberger, A. Ludlow, A. Jenkins, A. Helmi, J. F. Navarro,C. S. Frenk,, and S. D., M. White., The Aquarius Project: The Subhalos of Galactic Halos. Monthly Notices of the Royal Astronomical Society, 391(4): 1685-1711, Dec. 2008. doi> 10.1111/j.1365–2966.2008. 14066.x
[30] B. V. Srinivasan, Q. Hu, and R. Duraiswami., GPUML: Graphical Processors for Speeding up Kernel Machines. SIAM Data Mining 2010 Workshop on High Performance Analytics – Algorithms, Implementations, and Applications. 2010.
[31] A. Steed and C. Parker., 3D Selection Strategies for Head Tracked and Non-Head Tracked Operation of Spatially Immersive Displays. In Proc. 8thInternational Immersive Projection Technology Workshop, PP. 163-170, 2004.
[32] A. Ulinski, C. Zanbaka, Z. Wartell, P. Goolkasian, and L. Hodges., Two Handed Selection Techniques for Volumetric Data. In Proc. 3DUI, pp. 107-114. IEEE Computer Society, Los Alamitos, 2007. doi> 10.1109/ 3DUI.2007.340782
[33] A. Wiebel,F. M. Vos, D. Foerster, and H.-C. Hege, WYSIWYP: What You See Is What You Pick IEEE Transactions on Visualization and Computer Graphics. 18(12). Dec. 2012. In this issue.
[34] A. Wiebel,F. M. Vos,, and H.-C. Hege., Perception-Oriented Picking of Structures in Direct Volumetric Renderings. Technical Report 11–45, ZIB. Berlin. Germany, 2011.
[35] M. H F. Wilkinson and B. C. Meijer., DATAPLOT: A Graphical Display Package for Bacterial Morphometry and Fluorimetry Data Computer Methods and Programs Biomedicine, 47(1): 35-49, June 1995. doi> 10. 1016/0169–2607 (95)01628–7
[36] C. A. Wingrave, R. Tintner, B. N. Walker,D. A. Bowman,, and L. F. Hodges., Exploring Individual Differences in Raybased Selection: Strategies and Traits. In Proc. IEEE VR, pp. 163-170. IEEE Computer Society, Los Alamitos. 2005. doi> 10.1109/VR.2005.1492770
[37] G. Wyvill, C. McPheeters, and B. Wyvill, Data Structure for Soft Objects The Visual Computer, 2(4): 227-234, Aug. 1986. doi> 10.1007/ BF01900346
[38] L. Yu, P. Svetachov, P. Isenberg,M. H. Everts,, and T. Isenberg., FI3D: Direct-Touch Interaction for the Exploration of 3D Scientific Visualization Spaces. IEEE Transactions on Visualization and Computer Graphics, 16(6): 1613-1622, Nov./Dec. 2010. doi> 10.1109/TVCG.2010.157
[39] W. Zhou, S. Correia, and D. H. Laidlaw., Haptics-Assisted 3D Lasso Drawing for Tracts-of-interest Selection in DTI Visualization. IEEE Visualization 2008 Poster Compendium (Best Poster Nominee), 2008.