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Modeling Timing Structure in Multimedia Signals

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Articulated Motion and Deformable Objects (AMDO 2006)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4069))

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Abstract

Modeling and describing temporal structure in multimedia signals, which are captured simultaneously by multiple sensors, is important for realizing human machine interaction and motion generation. This paper proposes a method for modeling temporal structure in multimedia signals based on temporal intervals of primitive signal patterns. Using temporal difference between beginning points and the difference between ending points of the intervals, we can explicitly express timing structure; that is, synchronization and mutual dependency among media signals. We applied the model to video signal generation from an audio signal to verify the effectiveness.

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References

  1. Allen, J.F.: Maintaining knowledge about temporal interval. Commun. of the ACM 26(11), 832–843 (1983)

    Article  MATH  Google Scholar 

  2. Brand, M.: Voice puppetry. In: Proc. SIGGRAPH, pp. 21–28 (1999)

    Google Scholar 

  3. Brand, M., Oliver, N., Pentland, A.: Coupled hidden Markov models for complex action recognition. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 994–999 (1997)

    Google Scholar 

  4. Bregler, C.: Learning and recognizing human dynamics in video sequences. In: Proc. Int. Conference on Computer Vision and Pattern Recognition, pp. 568–574 (1997)

    Google Scholar 

  5. Cootes, T.F., Edwards, G.J., Taylor, C.J.: Active appearance models. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, pp. 484–498. Springer, Heidelberg (1998)

    Chapter  Google Scholar 

  6. Kawashima, H., Matsuyama, T.: Multiphase learning for an interval-based hybrid dynamical system. IEICE Trans. Fundamentals E88-A(11), 3022–3035 (2005)

    Article  Google Scholar 

  7. Levinson, S.E.: Continuously variable duration hidden Markov models for automatic speech recognition. Computer Speech and Language 1, 29–45 (1986)

    Article  Google Scholar 

  8. Li, Y., Wang, T., Shum, H.-Y.: Motion texture: A two-level statistical model for character motion synthesis. In: Proc. SIGGRAPH, pp. 465–472 (2002)

    Google Scholar 

  9. McGurk, H., MacDonald, J.: Hearing lips and seeing voices. Nature, 746–748 (1976)

    Google Scholar 

  10. Murphy, K.P.: Hidden semi-Markov models (HSMMs). Informal Notes (2002)

    Google Scholar 

  11. Nefian, A.V., Liang, L., Pi, X., Liu, X., Murphy, K.: Dynamic Bayesian networks for audio-visual speech recognition. EURASIP Journal on Applied Signal Processing 2002(11), 1–15 (2002)

    Google Scholar 

  12. Nishiyama, M., Kawashima, H., Hirayama, T., Matsuyama, T.: Facial expression representation based on timing structures in faces. In: Zhao, W., Gong, S., Tang, X. (eds.) AMFG 2005. LNCS, vol. 3723, pp. 140–154. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  13. Ostendorf, M., Digalakis, V., Kimball, O.A.: From HMMs to segment models: A unified view of stochastic modeling for speech recognition. IEEE Trans. Speech and Audio Process 4(5), 360–378 (1996)

    Article  Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Kawashima, H., Tsutsumi, K., Matsuyama, T. (2006). Modeling Timing Structure in Multimedia Signals. In: Perales, F.J., Fisher, R.B. (eds) Articulated Motion and Deformable Objects. AMDO 2006. Lecture Notes in Computer Science, vol 4069. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11789239_47

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  • DOI: https://doi.org/10.1007/11789239_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36031-5

  • Online ISBN: 978-3-540-36032-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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