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Real-Time Adaptive Human Motions for Web-Based Training

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Advances in Web-Based Learning – ICWL 2005 (ICWL 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3583))

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Abstract

Web-based training offers many benefits over instructor-led training environments. It provides a time, class size and geographical location independent learning platform to students. To enable active learning and enhance the effectiveness in students’ understanding of the training materials, multimedia cues, like 3D graphics, animation and sound, have been employed in web-based training systems to achieve these goals. However, if a training system involves a large amount of 3D animation, such as crowd animation in an emergency evacuation training system, the requirements for rendering capability and network bandwidth may become too high to meet. In this paper, we propose an adaptive human motion animation method to support real-time rendering and transmission of human motions in web-based training systems. Our method offers a mechanism to extract human motion data at various levels of detail (LoD). We also propose a set of importance factors to allow a web-based training system to determine the LoD of the human motion for rendering as well as the LoD for transmission, according to the importance of the motion and the available network bandwidth, respectively. We demonstrate the effectiveness of the new method with some experimental results.

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References

  1. Canós, J., Alonso, G., Jaen, J.: A Multimedia Approach to the Efficient Implementation and Use of Emergency Plans. IEEE Multimedia 11(3), 106–110 (2004)

    Article  Google Scholar 

  2. Burtnyk, N., Wein, M.: Interactive Skeleton Techniques for Enhancing Motion Dynamics in Key Frame Animation. Communications of the ACM 19(10), 564–569 (1976)

    Article  Google Scholar 

  3. Endo, M., Yasuda, T., Yokoi, S.: A Distributed Multiuser Virtual Space System. IEEE Computer Graphics and Applications 23(1), 50–57 (2003)

    Article  Google Scholar 

  4. H-Anim Specification, Available at, http://h-anim.org/

  5. Hoppe, H.: Progressive Meshes. In: Proc. of ACM SIGGRAPH 1996, pp. 99–108 (1996)

    Google Scholar 

  6. Körner, T.: Fourier Analysis. Cambridge University Press, Cambridge (1988)

    MATH  Google Scholar 

  7. Lander, J.: Working with Motion Capture File Formats. Game Developer Magazine (January 1998)

    Google Scholar 

  8. Lau, R.W.H., To, D., Green, M.: An Adaptive Multi-Resolution Modeling Technique Based on Viewing and Animation Parameters. In: Proc. of IEEE VRAIS, pp. 20–27 (1997)

    Google Scholar 

  9. Li, F.W.B., Lau, R.W.H.: A Progressive Content Distribution Framework in Supporting Web-Based Learning. In: Liu, W., Shi, Y., Li, Q. (eds.) ICWL 2004. LNCS, vol. 3143, pp. 75–82. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  10. Meyer, K., Applewhite, H., Biocca, F.: A Survey of Position Trackers. Presence: Teleoperators and Virtual Environments 1(2), 173–200 (1992)

    Google Scholar 

  11. Naka, T., Mochizuki, Y., Hijiri, T., Cornish, T., Asahara, S.: A Compression/Decompression Method for Streaming Based Humanoid Animation. In: Proc. Of Symposium on VRML, pp. 63–70 (1999)

    Google Scholar 

  12. Piegl, L., Tiller, W.: The NURBS Book. Springer, Heidelberg (1995)

    MATH  Google Scholar 

  13. Popović, Z., Witkin, A.: Physically Based Motion Transformation. In: Proc. Of ACM SIGGRAPH 1999, pp. 11–20 (1999)

    Google Scholar 

  14. Rose, C., Guenter, B., Bodenheimer, B., Cohen, M.: Efficient Generation of Motion Transitions Using Spacetime Constraints. In: Proc. of ACM SIGGRAPH 1996, pp. 147–154 (1996)

    Google Scholar 

  15. Sims, D.: See How They Run: Modeling Evacuations in VR. IEEE Computer Graphics and Applications 15(2), 11–13 (1995)

    Article  Google Scholar 

  16. Stollnitz, E., Derose, T., Salesin, D.: Wavelets for Computer Graphics: Theory and applications. Morgan Kaufmann Publishers, San Francisco (1996)

    Google Scholar 

  17. To, D., Lau, R.W.H., Green, M.: A Method for Progressive and Selective Transmission of Multi-Resolution Models. In: Proc. of ACM VRST, pp. 88–95 (December 1999)

    Google Scholar 

  18. Treisman, A., Gelade, G.: A Feature-Integration Theory of Attention. Cognitive Psychology 12, 97–136 (1980)

    Article  Google Scholar 

  19. Wang, T., Chen, C.: A Combined Optimization Method for Solving the Inverse Kinematics Problems of Mechanical Manipulators. IEEE Trans. on Robotics and Automation 7(4), 489–499 (1991)

    Article  Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Li, F.W.B., Siu, B., Lau, R.W.H., Komura, T. (2005). Real-Time Adaptive Human Motions for Web-Based Training. In: Lau, R.W.H., Li, Q., Cheung, R., Liu, W. (eds) Advances in Web-Based Learning – ICWL 2005. ICWL 2005. Lecture Notes in Computer Science, vol 3583. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11528043_25

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  • DOI: https://doi.org/10.1007/11528043_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-27895-5

  • Online ISBN: 978-3-540-31716-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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