Advertisement

Management of Visual Clutter in Annotated 3D CAD Models: A Comparative Study

  • Jorge Camba
  • Manuel Contero
  • Michael Johnson
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8518)

Abstract

The use of annotations in CAD models has been an active area of research because of their ability to connect design information to specific aspects of the model’s geometry. The effectiveness of annotations is determined by the ability to clearly communicate information. However, annotations can quickly create clutter and confusion as they increase both in number and complexity. Consequently, efficient interaction and visualization mechanisms become crucial. Despite recent standardizations of procedures for the presentation of textual information in CAD models, no explicit guidelines are available as to how to make annotated models more readable and manageable. In this paper, we present the results of a comparative study of different mechanisms to manage visual clutter in annotated 3D CAD models and offer recommendations based on our findings. Our results show that even basic interaction mechanisms have a substantial impact on user’s performance.

Keywords

visual clutter annotated 3D models CAD model interaction design communication 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Kajko-Mattsson, M.: The State of Documentation Practice within Corrective Maintenance. In: IEEE International Conference on Software Maintenance, pp. 354–363. IEEE Press, New York (2001)Google Scholar
  2. 2.
    Van De Vanter, M.L.: The Documentary Structure of Source Code. Information and Software Technology 44, 767–782 (2002)CrossRefGoogle Scholar
  3. 3.
    Haouari, D., Sahraoui, H., Langlais, P.: How Good is Your Comment? A Study of Comments in Java Programs. In: International Symposium on Empirical Software Engineering and Measurement, pp. 137–146. IEEE Press, New York (2011)Google Scholar
  4. 4.
    ASME Y14.41-2012 Digital Product Definition Data Practices. The American Society of Mechanical Engineers, New York (2012)Google Scholar
  5. 5.
    ISO 16792:2006 Technical Product Documentation – Digital Product Definition Data Practices. Organisation Internationale de Normalisation, Genève, Suisse (2006)Google Scholar
  6. 6.
    Boehm, B., Bayuk, J., Desmukh, A., Graybill, R., Lane, J.A., Levin, A., et al.: Systems 2020 Strategic Initiative. DoD Systems Engineering Research Center. Technical Report, SERC-2010-TR-009 (2010)Google Scholar
  7. 7.
    Quintana, V., Rivest, L., Pellerin, R.: Measuring and Improving the Process of Engineering Change Orders in a Model-Based Definition Context. International Journal of Product Lifecycle Management 6(2), 138–160 (2012)CrossRefGoogle Scholar
  8. 8.
    Alducin-Quintero, G., Rojo, A., Plata, F., Hernández, A., Contero, M.: 3D Model Annotation as a Tool for Improving Design Intent Communication: A Case Study on its Impact in the Engineering Change Process. In: ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, pp. 349–356. ASME, New York (2012)Google Scholar
  9. 9.
    Dorribo-Camba, J., Alducin-Quintero, G., Perona, P., Contero, M.: Enhancing Model Reuse through 3D Annotations: A Theoretical Proposal for an Annotation-Centered Design Intent and Design Rationale Communication. In: ASME International Mechanical Engineering Congress & Exposition. ASME, New York (2013)Google Scholar
  10. 10.
    Ding, L., Davies, D., McMahon, C.: Sharing Information throughout a Product Lifecycle via Markup of Product Models. In: ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, pp. 1267–1275. ASME, New York (2008)Google Scholar
  11. 11.
    Ding, L., Ball, A., Patel, M., Matthews, J., Mullineux, G.: Strategies for the Collaborative Use of CAD Product Models. In: Proceedings of ICED 2009, 17th International Conference on Engineering Design, vol. 8, pp. 123–134 (2009)Google Scholar
  12. 12.
    Ding, L., Davies, D., McMahon, C.A.: The Integration of Lightweight Representation and Annotation for Collaborative Design Representation. Research in Engineering Design 20(3), 185–200 (2009)CrossRefGoogle Scholar
  13. 13.
    Boujut, J.F., Dugdale, J.: Design of a 3D Annotation Tool for Supporting Evaluation Activities in Engineering Design. Cooperative Systems Design 6, 1–8 (2006)Google Scholar
  14. 14.
    Bracewell, R.H., Wallace, K.M.: A Tool for Capturing Design Rationale. In: 14th International Conference on Engineering Design. Paper no. DS31_1437FPB (2003)Google Scholar
  15. 15.
    Patel, M., Ball, A., Ding, L.: Curation and Preservation of CAD Engineering Models in Product Lifecycle Management. In: 14th International Conference on Virtual Systems and Multimedia Dedicated to Digital Heritage, pp. 59–66 (2008)Google Scholar
  16. 16.
    Li, C., McMahon, C., Newnes, L.: Annotation in Product Lifecycle Management: A Review of Approaches. In: ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp. 797–806 (2009)Google Scholar
  17. 17.
    Ahlberg, C., Shneiderman, B.: Visual Information Seeking: Tight Coupling of Dynamic Query Filters with Starfield Displays. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 313–317 (1994)Google Scholar
  18. 18.
    Fishkin, K., Stone, M.C.: Enhanced Dynamic Queries via Movable Filters. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 415–420 (1995)Google Scholar
  19. 19.
    Noyes, L.: The Positioning of Type on Maps: The Effect of Surrounding Material on Word Recognition Time. Human Factors 22(3), 353–360 (1980)Google Scholar
  20. 20.
    Rosenholtz, R., Li, Y., Mansfield, J., Jin, Z.: Feature Congestion: A Measure of Display Clutter. In: SIGCHI Conference on Human Factors in Computing Systems, pp. 761–770 (2005)Google Scholar
  21. 21.
    Tufte, E.R.: The Visual Display of Quantitative Information. Graphics Press, Cheshire (1983)Google Scholar
  22. 22.
    Ellis, G., Dix, A.: A Taxonomy of Clutter Reduction for Information Visualisation. IEEE Transactions on Visualization and Computer Graphics 13(6), 1216–1223 (2007)CrossRefGoogle Scholar
  23. 23.
    Wolfe, J.M.: Guided Search 2.0: A Revised Model of Visual Search. Psychonomic Bulletin & Review 1(2), 202–238 (1994)CrossRefGoogle Scholar
  24. 24.
    Palmer, J.: Set-size Effects in Visual Search: the Effect of Attention is Independent of the Stimulus for Simple Tasks. Vision Research 34, 1703–1721 (1994)CrossRefGoogle Scholar
  25. 25.
    Rosenholtz, R.: Search asymmetries? What search asymmetries? Perception & Psychophysics 63(3), 476–489 (2001)CrossRefGoogle Scholar
  26. 26.
    Woodruff, A., Landay, J., Stonebraker, M.: Constant Information Density in Zoomable Interfaces. In: Working Conference on Advanced Visual Interfaces, pp. 57–65 (1998)Google Scholar
  27. 27.
    Ellis, G., Bertini, E., Dix, A.: The Sampling Lens: Making Sense of Saturated Visualisations. In: Extended Abstracts on Human Factors in Computing Systems, pp. 1351–1354 (2005)Google Scholar
  28. 28.
    Ellis, G., Dix, A.: Enabling Automatic Clutter Reduction in Parallel Coordinate Plots. IEEE Transactions on Visualization and Computer Graphics 12(5), 717–723 (2006)CrossRefGoogle Scholar
  29. 29.
    Frank, A.U., Timpf, S.: Multiple Representations for Cartographic Objects in a Multi-scale Tree – An Intelligent Graphical Zoom. Computers & Graphics 18(6), 823–829 (1994)CrossRefGoogle Scholar
  30. 30.
    Cipriano, G., Gleicher, M.: Text Scaffolds for Effective Surface Labeling. IEEE Transactions on Visualization and Computer Graphics 14(6), 1675–1682 (2008)CrossRefGoogle Scholar
  31. 31.
    Stein, T., Décoret, X.: Dynamic Label Placement for Improved Interactive Exploration. In: 6th International Symposium on Non-Photorealistic Animation and Rendering, pp. 15–21 (2008)Google Scholar
  32. 32.
    Ali, K., Hartmann, K., Strothotte, T.: Label Layout for Interactive 3D Illustrations. Journal of WSCG 13(1), 1–8 (2005)Google Scholar
  33. 33.
    Götzelmann, T., Hartmann, K., Strothotte, T.: Agent-Based Annotation of Interactive 3D Visualizations. In: Butz, A., Fisher, B., Krüger, A., Olivier, P. (eds.) SG 2006. LNCS, vol. 4073, pp. 24–35. Springer, Heidelberg (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jorge Camba
    • 1
  • Manuel Contero
    • 2
  • Michael Johnson
    • 3
  1. 1.Engineering Design GraphicsTexas A&M UniversityCollege StationUSA
  2. 2.I3BHUniversitat Politècnica de ValènciaValènciaSpain
  3. 3.Dept. of Engineering Technology and Industrial DistributionTexas A&M UniversityCollege StationUSA

Personalised recommendations