AI & SOCIETY

, Volume 25, Issue 2, pp 211–223 | Cite as

Multi-interfaces approach to situated knowledge management for complex instruments: first step toward industrial deployment

Open Forum
First Online:
Received:
Accepted:

Abstract

This paper presents an approach to managing knowledge specific to a particular location for complex instruments. The goal is to improve the knowledge communication between experts and end-users of scientific instruments. We propose a computational framework that integrates augmented reality and augmented virtuality as interface for manipulating knowledge. The augmented virtuality-based interface can be produced and distributed without extra costs. It allows knowledge dissemination at a larger scale. The prominent feature of our model is that the knowledge representation is independent from those interfaces. A preliminary version of our framework has been implemented and deployed in customers’ environments.

Keywords

Situated knowledge Mixed reality Augmented reality Augmented virtuality Texture registration Scientific instruments 
This is a preview of subscription content, log in to check access.

References

  1. Azuma R (1997) A survey of augmented reality. Presence Teleoperators Virtual Environ 6(4):355–385Google Scholar
  2. Azuma R, Baillot Y, Behringer R, Feiner S, Julier S, MacIntyre B (2001) Recent advances in augmented reality. Comput Graph Appl 25:24–35Google Scholar
  3. Barfield W, Caudell T (2000) Fundamentals of wearable computers and augmented reality. L. Erlbaum, HillsdaleGoogle Scholar
  4. Drummond T, Cipolla R (2002) Real-time visual tracking of complex structures. IEEE Trans PAMI 24(7):932–946. doi: 10.1109/TPAMI.2002.1017620 Google Scholar
  5. Feiner S, Macintyre B, Seligmann D (1993) Knowledge-based augmented reality. Commun ACM 36(7):53–62. doi: 10.1145/159544.159587 CrossRefGoogle Scholar
  6. Fischer G, Ostwald J (2001) Knowledge management: problems, promises, realities, and challenges. IEEE Intell Syst 16(1):60–72CrossRefGoogle Scholar
  7. Franken T, Dellepiane M, Ganovelli F, Cignoni P, Montani C, Scopigno R (2005) Minimizing user intervention in registering 2D images to 3D models. Vis Comput 21(8–10):619–628 special issues for pacific graphics 2005CrossRefGoogle Scholar
  8. Gao XS, Hou XR, Tang J, Cheng HF (2003) Complete solution classification for the perspective-three-point problem. IEEE Trans PAMI 25(8):930–943. doi: 10.1109/TPAMI.2003.1217599 Google Scholar
  9. Goose S, Guven S, Zhang X, Sudarsky S, Navab N (2004) PARIS: Fusing vision-based location tracking with standards-based 3D visualization and speech interaction on a PDA. In: International conference on distributed multimedia systems, San Francisco, USA, pp 75–80Google Scholar
  10. Huber PJ (1981) Robust statistics. Wiley, New YorkMATHCrossRefGoogle Scholar
  11. Huttenlocher DP, Ullman S (1990) Recognizing solid objects by alignment with an image. Int J Comput Vis 5(2):195–212. doi: 10.1007/BF00054921 CrossRefGoogle Scholar
  12. Igarashi T, Hughes JF (2001) A suggestive interface for 3D drawing. In: 14th Annual symposium on user interface software and technology, Orlando, FL, pp 173–181Google Scholar
  13. Igarashi T, Matsuoka S, Tanaka H (1999) Teddy: a sketching interface for 3D freeform design. In: The 26th annual conference on computer graphics and interactive techniques (SIGGRAPH), ACM Press, Los Angels, pp 409–416Google Scholar
  14. Lowe DG (1987) Three-dimensional object recognition from single two-dimensional images. Artif Intell 31(3):355–395CrossRefGoogle Scholar
  15. Malis E, Marchand E (2006) Experiments with robust estimation techniques in real-time robot vision. In: IEEE/RSJ IROS ‘06, Beijing, China, pp 223–228Google Scholar
  16. Masry M, Kang DJ, Lipson H (2005) A freehand sketching interface for progressive construction of 3D objects. Comput Graph 29(4):563–575CrossRefGoogle Scholar
  17. Matsushita K, Kaneko T (1999) Efficient and handy texture mapping on 3D surfaces. In: Brunet P, Scopigno R (eds) Computer graphics forum. Eurographics Association and Blackwell, vol 18(3), pp 349–358. http://www3.interscience.wiley.com/journal/119071638/abstract?CRETRY=1&SRETRY=0
  18. Merckel L, Nishida T (2008a) Accurate object recognition using orientation sensor with refinement on the lie group of spatial rigid motions. IEICE Trans Inf Syst E91-D(8):2179–2188CrossRefGoogle Scholar
  19. Merckel L, Nishida T (2008b) Evaluation of a method to solve the perspective-two-point problem using a three-axis orientation sensor. In: The 8th international conference on information technology (CIT), IEEE Computer Society, Sydney, Australia, pp 862–867Google Scholar
  20. Merckel L, Nishida T (2009) Enabling situated knowledge management for complex instruments by real-time reconstruction of surface coordinate system on a mobile device. AI Soc 24(1):85–95. doi: 10.1007/s00146-009-0200-y CrossRefGoogle Scholar
  21. Milgram P, Colquhoun H (1999) A taxonomy of real and virtual world display integration. In: Ohta Y, Tamura H (eds) Mixed reality-merging real and virtual worlds, chap 1. Ohmsha (Tokyo), Springer (Berlin), pp 5–30Google Scholar
  22. Miller G, Talmor D, Teng S, Walkington N, Wang H (1996) Control volume meshes using sphere packing: generation, refinement and coarsening. In: The 5th international meshing roundtable, Pittsburgh, PA, pp 47–61Google Scholar
  23. Mizell DW (1994) Virtual reality and augmented reality in aircraft design and manufacturing. In: IEEE WESCON, p 91Google Scholar
  24. Neugebauer P, Klein K (1999) Texturing 3D models of real world objects from multiple unregistered photographic views. Comput Graph Forum 18(13):245–256CrossRefGoogle Scholar
  25. Nishida T (2007) Social intelligence design and human computing. In: Huang TS et al. (eds) Human Comput LNAI, vol 4451, pp 190–214Google Scholar
  26. Nishida T, Terada K, Tajima T, Hatakeyama M, Ogasawara Y, Sumi Y, Xu Y, Mohammad YFO, Tarasenko K, Ohya T, Hiramatsu T (2006) Toward robots as embodied knowledge media. IEICE Trans Inf Syst E89-D(6):1768–1780CrossRefGoogle Scholar
  27. Pearson RK (2002) Outliers in process modeling and identification. IEEE Trans Control Syst Technol 10(1):55–63CrossRefGoogle Scholar
  28. Reitmayr G, Eade E, Drummond T (2007) Semi-automatic annotations in unknown environments. In: Proceedings of ISMAR 2007, Nara, Japan, pp 67–70Google Scholar
  29. Riess P, Stricker D (2006) AR-on-demand: a practicable solution for augmented reality on low-end handheld devices. In: AR/VR Workshop of the Germany Computer Science Society, Coblence, Germany, pp 119–130Google Scholar
  30. Rose E, Breen D, Ahlers KH, Crampton C, Tuceryan M, Whitaker R, Greer D (1995) Annotating real-world objects using augmented reality. In: Computer Graphics International, Leeds, UK, pp 357–370Google Scholar
  31. Shewchuk JR (1998) Tetrahedral mesh generation by Delaunay refinement. In: The 14th annual symposium on computational geometry, pp 86–95Google Scholar
  32. Si H (2006) On refinement of constrained Delaunay tetrahedralizations. In: The 15th international meshing roundtableGoogle Scholar
  33. Si H, Gaertner K (2005) Meshing piecewise linear complexes by constrained Delaunay tetrahedralizations. In: The 14th international meshing roundtable, pp 147–163Google Scholar
  34. Stuerzlinger W (1999) Imaging all visible surfaces. In: The 1999 conference on graphics interface, Morgan Kaufmann, San Francisco, CA, pp 115–122Google Scholar
  35. van Dam A (1997) Post-wimp user interfaces. Commun ACM 40(2):63–67. doi: 10.1145/253671.253708 CrossRefMathSciNetGoogle Scholar
  36. Zeleznik RC, Herndon KP, Hughes JF (1996) Sketch: an interface for sketching 3D scenes. In: The 23rd annual conference on computer graphics and interactive techniques (SIGGRAPH), ACM, New York, NY, pp 163–170Google Scholar

Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  1. 1.Department of Intelligence Science and Technology, Graduate School of InformaticsKyoto UniversityYoshida-Honmachi, Sakyo-ku, KyotoJapan
  2. 2.Department of Scientific Systems R&DHORIBA LtdKyotoJapan

Personalised recommendations