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Intelligent Techniques for Processing and Management of Motion Data

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A Modern Approach to Intelligent Animation

Part of the book series: Advanced Topics in Science and Technology in China ((ATSTC))

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Abstract

Motion Capture (MoCap) systems are widely used in computer animations, simulations and video games. Recently, a large commercial MoCap database is available and it will be of great importance to the reusability of motion data as well as the efficiency of computer animations.

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References

  1. Brand ME, Kettnaker V. Discovery and segmentation of activities in video. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8): 844–851, 2000.

    Article  Google Scholar 

  2. Bradski G, Davis J. Motion segmentation and pose recognition with motion history gradients. International Journal of Machine Vision and Applications, 13(3): 174–184, 2002.

    Article  Google Scholar 

  3. Arikan O, Forsyth DA, O’Brien J. Motion synthesis from annotations. ACM Transactions on Graphics (SIGGRAPH’ 03), 33(3): 402–408, 2003.

    Article  Google Scholar 

  4. Kahol K, Tripathi P, Panchanathan S, Rikakis T. Gesture segmentation in complex motion sequences. In. ICIP’03, pp. II. 105–108, IEEE Computer Society, 2003.

    Google Scholar 

  5. Kahol K, Tripathi P, Panchanathan S. Automated gesture segmentation from dance sequences. In. AFGR’04, pp. 883–888, IEEE Computer Society, 2004.

    Google Scholar 

  6. Lu C, Ferrier JN. Repetitive motion analysis: segmentation and event classification. IEEE Transactions of Pattern Analysis and Meachine Intelligence, 26(2): 258–263, 2004.

    Article  Google Scholar 

  7. Fod A, Mataric MJ, Jenkins OC. Automated derivation of primitives for movement classification. Autonomous Robots, 12(1): 39–54, 2002.

    Article  MATH  Google Scholar 

  8. Pomplun M, Mataric MJ. Evaluation metrics and results of human arm movement imitation. In. Humanoids-2000, IEEE Computer Society, 2000.

    Google Scholar 

  9. Wang T, Shum H, Xu Y, Zheng N. Unsupervised analysis of human gestures. In. IEEE Pacific Rim Conference on Multimedia, pp. 174–181, IEEE Computer society, 2001.

    Google Scholar 

  10. Barbic J, Safonova A, Pan J, Faloutsos C, Hodgins JK, Pollard NC. Segmenting motion capture data into distinct behaviors. In: GI′04, pp. 185–194, Canadian Human-Computer Communications Society School of Computer Science, 2004.

    Google Scholar 

  11. Tenenbaum JB, de Silva V, Langford JC. A global geometric framework for nonlinear dimensionality reduction. Science, 290(5500): 2319–2323, 2000.

    Article  Google Scholar 

  12. Spath H. Cluster dissection and analysis: theory, FORTRAN programs, examples, pp. 226, Halsted Press, 1985.

    Google Scholar 

  13. Pickering MJ, Ruger S. Evaluation of key frame-based retrieval techniques for video. Computer Vision and Image Understand, 92 (2): 216–235, 2003.

    Google Scholar 

  14. Zhuang Y, Rui Y, Huang TS, Mehrotra S. Adaptive key frame extraction using unsupervised clustering. In. ICIP’98, IEEE Computer Society, 1998.

    Google Scholar 

  15. Zhuang Y, Pan Y, Wu F. Web-based multimedia information analysis and retrieval. Tsinghua University Press, 2002.

    Google Scholar 

  16. Liu F, Zhuang, Wu F, Pan Y. 3D motion retrieval with motion index tree. Computer Vision and Image Understanding, 92(2–3): 265–284, 2003.

    Article  Google Scholar 

  17. Shen J, Sun S, Pan Y. Key-frame extraction from motion capture data. Journal of Computer-Aided Design and Computer Graphics, 16 (5): 719–723, 2004.

    Google Scholar 

  18. Lim IS, Thalmann D. Key-posture extraction out of human motion data by curve simplification. In: EMBC’01, pp. 1166–1169, IEEE Computer Society, 2001.

    Google Scholar 

  19. Lee J, Chai J, Reitsma PSA, Hodgins JK, Pollard NS. Interactive control of avatars animated with human motion data. In. SIGGRAPH’ 02, pp. 491–500, ACM Press, 2002.

    Google Scholar 

  20. Chui C, Chao S, Wu M, Yang S, Lin H. Content-based retrieval for human motion data. Journal of Visual Communication and Image Representation, 16(3): 446–466, 2004.

    Article  Google Scholar 

  21. Muller M, Roder T, Clausen M. Efficient content-based retrieval of motion capture data. ACM Transactions on Graphics (SIGGRAPH’ 05), 24(3). 676–685, 2005.

    Google Scholar 

  22. Rosin PL. Techniques for assessing polygonal approximations of curves. IEEE Transactions on Pattern Recognition and Machine Intelligence, 19(6): 659–666, 1997.

    Article  Google Scholar 

  23. Fritsch FN, Carlson RE. Monotone piecewise cubic interpolation. SIAM Journal on Numerical Analysis, 17(2): 238–246, 1980.

    Article  MATH  MathSciNet  Google Scholar 

  24. Pullen K, Bregler C. Motion capture assisted animation: texturing and synthesis. In. SIGGRAPH’02, pp. 501–508, ACM Press, 2002.

    Google Scholar 

  25. Bian Z, Zhang C, Zhang X. Pattern recognition, pp. 241–244, Tsinghua University Press, 1999.

    Google Scholar 

  26. Kim C, Huang JN. Object-based video abstraction using cluster analysis. In. ICIP’01, pp. 657–660, IEEE Computer Society, 2001.

    Google Scholar 

  27. Ratakonda K, Sezan MI, Crinon R. Hierarchical video summarization. SPIE, 3653: 1531–1541, 1999.

    Article  Google Scholar 

  28. Doulamis AD, Doulamis ND, Kollias SD. A fuzzy video content representation for video summarization and content-based retrieval. Signal Process, 80(6): 1049–1067, 2000.

    Article  MATH  Google Scholar 

  29. Zhuang Y, Rui Y, Huang TS, Mchrotra S. Adaptive key frame extraction using unsupervised clustering. In. ICIP’98, pp. 886–890, IEEE Computer Society, 1998.

    Google Scholar 

  30. Zhang H, Wu J, Zhong D, Smoliar SW. An integrated system for content-based video retrieval and browsing. Pattern Recognition, 30 (4): 643–658, 1997.

    Article  Google Scholar 

  31. Zhao L, Qi W, Li SZ, Yang S, Zhang H. Key-frame extraction and shot retrieval using nearest feature line (NFL). In: Proceedings of International Workshop on Multimedia Information Retrieval, in Conjunction with ACM Multimedia Conference 2000, pp. 217–220, ACM Press, 2000.

    Google Scholar 

  32. Martens R, Claesen L. Dynamic programming optimization for online signature verification. In. International Conference on Document Analysis and Recognition, pp. 653–656, IEEE Computer Society, 1997.

    Google Scholar 

  33. Tappert CC. Adaptive on-line handwriting recognition. In: International Conference on Pattern Recognition, pp. 1004–1007, IEEE Computer Society, 1984.

    Google Scholar 

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© 2008 Zhejiang University Press, Hangzhou and Springer-Verlag GmbH Berlin Heidelberg

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(2008). Intelligent Techniques for Processing and Management of Motion Data. In: A Modern Approach to Intelligent Animation. Advanced Topics in Science and Technology in China. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73760-5_6

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  • DOI: https://doi.org/10.1007/978-3-540-73760-5_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73759-9

  • Online ISBN: 978-3-540-73760-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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