Skip to main content

Automatically Constructing a Compact Concept Map of Dance Motion with Motion Captured Data

  • Conference paper
Advances in Web-Based Learning – ICWL 2010 (ICWL 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6483))

Included in the following conference series:

Abstract

In recent years, E-learning has become a popular research topic with its wide applications. As an important factor of E-learning, concept map is a powerful way to manage knowledge. In this paper, we describe our approach for determining a compact concept map of an input dance motion obtained from the 3D motion capture technology. The dance motion is analyzed to extract the repetitive patterns and then the prerequisite relations are computed as the inclusion relation among patterns. A concept map can then be constructed automatically for illustrating such relations. The transitive reduction algorithm is applied to remove the redundant edges such that the resulting concept map retains a compact representation of the dance structure. This concept map can be used to generate dance lessons such that a learner can learn the dance motion in a step-by-step and logical manner.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Thomas, B.M.: Interacting with virtual world through motion capture. In: Interaction in Virtual Inhabited 3D Worlds, ch. 11, Springer, Heidelberg (2000)

    Google Scholar 

  2. Gelberg, H.J., Brundage, B.H., Glantz, S., Parmley, W.W.: Quantitative left ventricular wall motion analysis: a comparison of area, chord and radial methods. Circulation 59, 991–1000 (1979)

    Article  Google Scholar 

  3. Mannion, A., Troke, M.: A comparison of two motion analysis devices used in the measurement of lumbar spinal mobility. Clinical Biomechanics 14(9), 612–619 (1999)

    Article  Google Scholar 

  4. Novak, J.D.: Learning, Creating, and Using Knowledge: Concept Maps As Facilitative Tools in Schools and Corporations. Lawrence Erlbaum Assoc., New Jersey (1998)

    Google Scholar 

  5. Hagiwara, M.: Self-organizing Concept Maps. In: IEEE International Conference on Systems, Man and Cybernetics, vol. 1, pp. 447–451 (1995)

    Google Scholar 

  6. Saito, H., Ohno, T., Ozaki, F.: A Semi-Automatic Construction Method of Concept Map Based on Dialog Contents. In: Sixth International Conference on Computers in Education (2001)

    Google Scholar 

  7. Sue, P.C., Weng, J.F., Su, J.M., Tseng, S.S.: A New Approach for Constructing the Concept Map. In: Fourth IEEE International Conference on Advanced Learning Technologies, pp. 76–80 (2004)

    Google Scholar 

  8. Bai, S.M., Chen, S.M.: Automatically constructing concept maps based on fuzzy rules for adapting learning systems. Expert Systems with Applications: An International Journal 35(1-2), 41–49 (2008)

    Article  Google Scholar 

  9. Lau, R.Y., Chung, A.Y., Song, D.W., Huang, Q.: Towards Fuzzy Domain Ontology Based Concept Map Generation for E-Learning. In: Leung, H., Li, F., Lau, R., Li, Q. (eds.) ICWL 2007. LNCS, vol. 4823, pp. 90–101. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  10. Xu, M., Bodik, R., Hill, M.D.: A Regulated Transitive Reduction (RTR) for Longer Memory Race Recording. In: Proceedings of the 2006 ASPLOS Conference, vol. 34(5), pp. 49–60 (2006)

    Google Scholar 

  11. Rakesh, A., Dimitrios, G., Frank, L.: Mining Process Models from Workflow Logs. In: Sixth International Conference on Extending Database Technology, pp. 469–483 (1998)

    Google Scholar 

  12. Jens, L.: Computing unique canonical covers for simple FDs via transitive reduction. Information Processing Letters 94(4), 169–174 (2004)

    MathSciNet  MATH  Google Scholar 

  13. Leung, H., Chan, J., Tang, K.T., Komura, T.: Finding Repetitive Patterns in 3D Human Motion Captured Data. In: 2nd International Conference on Ubiquitous Information Management and Communication, Korea, pp. 396–403 (2008)

    Google Scholar 

  14. Goralcikova, A., Koubek, V.: A reduct-and-closure algorithm for graphs. In: Becvar, J. (ed.) MFCS 1979. LNCS, vol. 74, Springer, Heidelberg (1979)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yang, Y., Leung, H., Yue, L., Deng, L. (2010). Automatically Constructing a Compact Concept Map of Dance Motion with Motion Captured Data. In: Luo, X., Spaniol, M., Wang, L., Li, Q., Nejdl, W., Zhang, W. (eds) Advances in Web-Based Learning – ICWL 2010. ICWL 2010. Lecture Notes in Computer Science, vol 6483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17407-0_34

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17407-0_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17406-3

  • Online ISBN: 978-3-642-17407-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics