“Illustrating how mechanical assemblies work” by Mitra, Yang, Yan, Li and Agrawala

  • ©

Conference:


Type(s):


Title:

    Illustrating how mechanical assemblies work

Presenter(s)/Author(s):



Abstract:


    How things work visualizations use a variety of visual techniques to depict the operation of complex mechanical assemblies. We present an automated approach for generating such visualizations. Starting with a 3D CAD model of an assembly, we first infer the motions of individual parts and the interactions between parts based on their geometry and a few user specified constraints. We then use this information to generate visualizations that incorporate motion arrows, frame sequences and animation to convey the causal chain of motions and mechanical interactions between parts. We present results for a wide variety of assemblies.

References:


    1. Agrawala, M., Phan, D., Heiser, J., Haymaker, J., Klingner, J., Hanrahan, P., and Tversky, B. 2003. Designing effective step-by-step assembly instructions. Proc. ACM SIGGRAPH, 828–837. Google ScholarDigital Library
    2. Amerongen, C. V. 1967. The Way Things Work: An Illustrated Encyclopedia of Technology. Simon and Schuster.Google Scholar
    3. Assa, J., Caspi, Y., and Cohen-Or, D. 2005. Action synopsis: pose selection and illustration. ACM Trans. on Graphics (Proc. SIGGRAPH) 24, 3, 667–676. Google ScholarDigital Library
    4. Benkö, P., Martin, R. R., and Várady, T. 2001. Algorithms for reverse engineering boundary representation models. Computer Aided Design 33, 11, 839–851.Google ScholarCross Ref
    5. Bouvier-Zappa, S., Ostromoukhov, V., and Poulin, P. 2007. Motion cues for illustration of skeletal motion capture data. In Proceedings of the 5th international symposium on Non-photorealistic animation and rendering, 140. Google ScholarDigital Library
    6. Brain, M. 2001. How stuff works. Hungry Minds New York.Google Scholar
    7. Bruckner, S., and Groller, M. E. 2006. Exploded views for volume data. IEEE Transactions on Visualization and Computer Graphics 12, 5, 1077–1084. Google ScholarDigital Library
    8. Burns, M., and Finkelstein, A. 2008. Adaptive cutaways for comprehensible rendering of polygonal scenes. In SIGGRAPH Asia ’08: ACM SIGGRAPH Asia 2008 papers, ACM, New York, NY, USA, 1–7. Google ScholarDigital Library
    9. Cohen-Steiner, D., Alliez, P., and Desbrun, M. 2004. Variational shape approximation. In Proc. ACM SIGGRAPH, 905–914. Google ScholarDigital Library
    10. Collomosse, J., Rowntree, D., and Hall, P. 2005. Rendering cartoon-style motion cues in post-production video. Graphical Models 67, 549–564. Google ScholarDigital Library
    11. Cutting, J. E. 2002. Representing motion in a static image: constraints and parallels in art, science, and popular culture. Perception 31, 1165–1193.Google ScholarCross Ref
    12. Davidson, J. K., and Hunt, K. H. 2004. Robots and Screw Theory: Applications of Kinematics and Statics to Robotics. Oxford University Press.Google Scholar
    13. Davis, R. 2007. Magic paper: Sketch-understanding research. Computer 40, 9, 34–41. Google ScholarDigital Library
    14. Demarsin, K., Vanderstraeten, D., Volodine, T., and Roose, D. 2007. Detection of closed sharp edges in point clouds using normal estimation and graph theory. Computer Aided Design 39, 4, 276–283. Google ScholarDigital Library
    15. Dony, R., Mateer, J., Robinson, J., and Day, M. 2005. Iconic versus naturalistic motion cues in automated reverse storyboarding. In Conf. on Visual Media Production, 17–25.Google Scholar
    16. Feiner, S., and Seligmann, D. 1992. Cutaways and ghosting: satisfying visibility constraints in dynamic 3D illustrations. The Visual Computer 8, 5, 292–302.Google ScholarCross Ref
    17. Fu, H., Cohen-Or, D., Dror, G., and Sheffer, A. 2008. Upright orientation of man-made objects. In ACM Trans. on Graphics (Proc. SIGGRAPH), 1–7. Google ScholarDigital Library
    18. Gal, R., Sorkine, O., Mitra, N. J., and Cohen-Or, D. 2009. iWIRES: An analyze-and-edit approach to shape manipulation. ACM Trans. on Graphics (Proc. SIGGRAPH) 28, 3, #33, 1–10. Google ScholarDigital Library
    19. Gelfand, N., and Guibas, L. J. 2004. Shape segmentation using local slippage analysis. In Proc. of Symp. of Geometry Processing, 214–223. Google ScholarDigital Library
    20. Goldman, D. B., Curless, B., Salesin, D., and Seitz, S. M. 2006. Schematic storyboarding for video visualization and editing. ACM Trans. on Graphics (Proc. SIGGRAPH) 25, 3, 862–871. Google ScholarDigital Library
    21. Hegarty, M., Kriz, S., and Cate, C. 2003. The roles of mental animations and external animations in understanding mechanical systems. Cognition and Instruction 21, 4, 325–360.Google ScholarCross Ref
    22. Hegarty, M. 1992. Mental animation: Inferring motion from static displays of mechanical systems. Journal of Experimental Psychology: Learning, Memory, and Cognition 18, 5, 1084–1102.Google ScholarCross Ref
    23. Hegarty, M. 2000. Capacity limits in diagrammatic reasoning. In Theory and Application of Diagrams. 335–348. Google ScholarDigital Library
    24. Heiser, J., and Tversky, B. 2006. Arrows in comprehending and producing mechanical diagrams. Cognitive Science 30, 581–592.Google ScholarCross Ref
    25. Joshi, A., and Rheingans, P. 2005. Illustration-inspired techniques for visualizing time-varying data. In IEEE Visualization, 679–686.Google Scholar
    26. Kawagishi, Y., Hatsuyama, K., and Kondo, K. 2003. Cartoon blur: Non-photorealistic motion blur. In Proc. of Computer Graphics International, 276–281.Google Scholar
    27. Kim, B., and Essa, I. 2005. Video-based nonphotorealistic and expressive illustration of motion. Proceedings of Computer Graphics International (CGI 05), 32–35. Google ScholarDigital Library
    28. Klein, F., and (translator), M. W. H. 1893. A comparative review of recent researches in geometry. Bull. New York Math. Soc., 215–249.Google Scholar
    29. Kriz, S., and Hegarty, M. 2007. Top-down and bottom-up influences on learning from animations. International Journal of Human-Computer Studies 65, 11, 911–930. Google ScholarDigital Library
    30. Langone, J. 1999. National Geographic’s how things work: everyday technology explained. National Geographic.Google Scholar
    31. Li, W., Ritter, L., Agrawala, M., Curless, B., and Salesin, D. 2007. Interactive cutaway illustrations of complex 3d models. ACM Trans. on Graphics (Proc. SIGGRAPH) 26, 3, #31, 1–11. Google ScholarDigital Library
    32. Li, W., Agrawala, M., Curless, B., and Salesin, D. 2008. Automated generation of interactive 3d exploded view diagrams. ACM Trans. on Graphics (Proc. SIGGRAPH) 27, 3. Google ScholarDigital Library
    33. Macaulay, D. 1998. The New Way Things Work.Google Scholar
    34. Masuch, M., Schlechtweg, S., and Schulz, R. 1999. Speedlines: depicting motion in motionless pictures. In SIGGRAPH Conference abstracts. Google ScholarDigital Library
    35. Mayer, R. 2001. Multimedia learning. Cambridge Univ Pr. Google ScholarDigital Library
    36. McCloud, S., 1993. Understanding Comics. 1993.Google Scholar
    37. McGuffin, M. J., Tancau, L., and Balakrishnan, R. 2003. Using deformations for browsing volumetric data. In Proceedings of the 14th IEEE Visualization, 53. Google ScholarDigital Library
    38. Mehra, R., Zhou, Q., Long, J., Sheffer, A., Gooch, A., and Mitra, N. J. 2009. Abstraction of man-made shapes. In ACM Trans. on Graphics (Proc. SIGGRAPH Asia), 1–10. Google ScholarDigital Library
    39. Mitra, N. J., Guibas, L., and Pauly, M. 2006. Partial and approximate symmetry detection for 3D geometry. 560–568. Google ScholarDigital Library
    40. Narayanan, N., and Hegarty, M. 1998. On designing comprehensible interactive hypermedia manuals. International Journal of Human-Computers Studies 48, 2, 267–301. Google ScholarDigital Library
    41. Narayanan, N., and Hegarty, M. 2002. Multimedia design for communication of dynamic information. International journal of human-computer studies 57, 4, 279–315. Google ScholarDigital Library
    42. Nienhaus, M., and Döllner, J. 2005. Depicting dynamics using principles of visual art and narrations. IEEE Comput. Graph. Appl. 25, 3, 40–51. Google ScholarDigital Library
    43. Seligmann, D., and Feiner, S. 1991. Automated generation of intent-based 3D illustrations. In Proc. ACM SIGGRAPH, ACM, 132. Google ScholarDigital Library
    44. Thompson, D. W. 1917. On Growth and Form. Dover Publications.Google Scholar
    45. Tversky, B., Morrison, J. B., and Betrancourt, M. 2002. Animation: Can it facilitate? International Journal of Human Computer Studies 5, 247–262. Google ScholarDigital Library
    46. Viola, I., Kanitsar, A., and Gröller, M. E. 2004. Importance-driven volume rendering. In Proceedings of IEEE Visualization 2004, H. Rushmeier, G. Turk, J. van Wijk, 139–145. Google ScholarDigital Library
    47. Whiting, E., Ochsendorf, J., and Durand, F. 2009. Procedural modeling of structurally-sound masonry buildings. ACM Transactions on Graphics 28, 5, 112. Google ScholarDigital Library
    48. Xu, W., Wang, J., Yin, K., Zhou, K., van de Panne, M., Chen, F., and Guo, B. 2009. Joint-aware manipulation of deformable models. ACM Trans. on Graphics (Proc. SIGGRAPH) 28, 3, #33, 1–10. Google ScholarDigital Library


ACM Digital Library Publication:



Overview Page: