“Style translation for human motion” by Hsu, Pulli and Popović

  • ©Eugene Hsu, Kari Pulli, and Jovan Popović

Conference:


Type:


Title:

    Style translation for human motion

Presenter(s)/Author(s):



Abstract:


    Style translation is the process of transforming an input motion into a new style while preserving its original content. This problem is motivated by the needs of interactive applications, which require rapid processing of captured performances. Our solution learns to translate by analyzing differences between performances of the same content in input and output styles. It relies on a novel correspondence algorithm to align motions, and a linear time-invariant model to represent stylistic differences. Once the model is estimated with system identification, our system is capable of translating streaming input with simple linear operations at each frame.

References:


    1. Amaya, K., Bruderlin, A., and Calvert, T. 1996. Emotion from motion. In Graphics Interface ’96, 222–229.]] Google ScholarDigital Library
    2. Arikan, O., and Forsyth, D. A. 2002. Synthesizing constrained motions from examples. ACM Transactions on Graphics 21, 3 (July), 483–490.]] Google ScholarDigital Library
    3. Arikan, O., Forsyth, D. A., and O’Brien, J. F. 2003. Motion synthesis from annotations. ACM Transactions on Graphics 22, 3 (July), 402–408.]] Google ScholarDigital Library
    4. Brand, M., and Hertzmann, A. 2000. Style machines. In Computer Graphics (Proceedings of ACM SIGGRAPH 2000), ACM SIGGRAPH, Annual Conference Series, 183–192.]] Google ScholarDigital Library
    5. Brockwell, P. J., and Davis, R. A. 2002. Introduction to Time Series and Forecasting, 2nd ed. Springer-Verlag.]]Google Scholar
    6. Bruderlin, A., and Williams, L. 1995. Motion signal processing. In Computer Graphics (Proceedings of SIGGRAPH 95), ACM SIGGRAPH, Annual Conference Series, 97–104.]] Google ScholarDigital Library
    7. De La Torre, F., and Black, M. 2001. Dynamic coupled component analysis. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 643–650.]]Google Scholar
    8. Dontcheva, M., Yngve, G., and Popović, Z. 2003. Layered acting for character animation. ACM Transactions on Graphics 22, 3 (July), 409–416.]] Google ScholarDigital Library
    9. Duda, R. O., Hart, P. E., and Stork, D. G. 2000. Pattern Classification, 2nd ed. John Wiley & Sons, Inc., New York.]] Google ScholarDigital Library
    10. Faloutsos, P., Van De Panne, M., and Terzopoulos, D. 2001. Composable controllers for physics-based character animation. In Computer Graphics (Proceedings of ACM SIGGRAPH 2001), ACM SIGGRAPH, Annual Conference Series, 251–260.]] Google ScholarDigital Library
    11. Freeman, W. T., Tenenbaum, J. B., and Pasztor, E. 2003. Learning style translation for the lines of a drawing. ACM Transactions on Graphics 22, 1 (Jan.), 33–46.]] Google ScholarDigital Library
    12. Giese, M. A., and Poggio, T. 2000. Morphable models for the analysis and synthesis of complex motion patterns. International Journal of Computer Vision 38, 1 June), 59–73.]] Google ScholarDigital Library
    13. Gleicher, M. 1998. Retargetting motion to new characters. In Computer Graphics (Proceedings of SIGGRAPH 98), ACM SIGGRAPH, Annual Conference Series, 33–42.]] Google ScholarDigital Library
    14. Grassia, F. S. 1998. Practical parameterization of rotation using the exponential map. Journal of Graphics Tools 3, 3, 29–48.]] Google ScholarDigital Library
    15. Grochow, K., Martin, S. L., Hertzmann, A., and Popović, Z. 2004. Style-based inverse kinematics. ACM Transactions on Graphics 23, 3 (Aug.), 522–531.]] Google ScholarDigital Library
    16. Hertzmann, A., Jacobs, C. E., Oliver, N., Curless, B., and Salesin, D. H. 2001. Image analogies. In Computer Graphics (Proceedings of SIGGRAPH 2001), ACM SIGGRAPH, Annual Conference Series, 327–340.]] Google ScholarDigital Library
    17. Hsu, E., Gentry, S., and Popović, J. 2004. Example-based control of human motion. In 2004 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 69–77.]] Google ScholarDigital Library
    18. Ilg, W., and Giese, M. A. 2002. Modeling of movement sequences based on hierarchical spatial-temporal correspondence of movement primitives. In Biologically Motivated Computer Vision, 528–537.]] Google ScholarDigital Library
    19. Jebara, T., and Pentland, A. 1999. Action reaction learning: Automatic visual analysis and synthesis of interactive behaviour. In International Conference on Computer Vision Systems (ICVS), vol. 1542, 273–292.]] Google ScholarDigital Library
    20. Kovar, L., and Gleicher, M. 2003. Flexible automatic motion blending with registration curves. In Proceedings of the ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 214–224.]] Google ScholarDigital Library
    21. Kovar, L., and Gleicher, M. 2004. Automated extraction and parameterization of motions in large data sets. ACM Transactions on Graphics 23, 3 (Aug.), 559–568.]] Google ScholarDigital Library
    22. Kovar, L., Gleicher, M., and Pighin, F. 2002. Motion graphs. ACM Transactions on Graphics 21, 3 (July), 473–482.]] Google ScholarDigital Library
    23. Kovar, L., Schreiner, J., and Gleicher, M. 2002. Footskate cleanup for motion capture editing. In ACM SIGGRAPH Symposium on Computer Animation, 97–104.]] Google ScholarDigital Library
    24. Lee, J., and Shin, S. Y. 1999. A hierarchical approach to interactive motion editing for human-like figures. In Computer Graphics (Proceedings of SIGGRAPH 99), ACM SIGGRAPH, Annual Conference Series, 39–48.]] Google ScholarDigital Library
    25. Lee, J., Chai, J., Reitsma, P. S. A., Hodgins, J. K., and Pollard, N. S. 2002. Interactive control of avatars animated with human motion data. ACM Transactions on Graphics 21, 3 (July), 491–500.]] Google ScholarDigital Library
    26. Li, Y., Wang, T., and Shum, H.-Y. 2002. Motion texture: A two-level statistical model for character motion synthesis. ACM Transactions on Graphics 21, 3 (July), 465–472.]] Google ScholarDigital Library
    27. Ljung, L. 1999. System Identification: Theory for the User, 2nd ed. Prentice Hall PTR.]] Google ScholarDigital Library
    28. Luenberger, D. G. 1979. Introduction to Dynamic Systems: Theory, Models, and Applications, 1st ed. Wiley.]]Google Scholar
    29. Park, S. I., Shin, H. J., and Shin, S. Y. 2002. On-line locomotion generation based on motion blending. In ACM SIGGRAPH Symposium on Computer Animation, 105–112.]] Google ScholarDigital Library
    30. Park, S. I., Shin, H. J., Kim, T. H., and Shin, S. Y. 2004. On-line motion blending for real-time locomotion generation. Computer Animation and Virtual Worlds 15, 3-4, 125–138.]] Google ScholarDigital Library
    31. Perlin, K. 1995. Real time responsive animation with personality. IEEE Transactions on Visualization and Computer Graphics 1, 1 (Mar.), 5–15.]] Google ScholarDigital Library
    32. Popović, Z., and Witkin, A. P. 1999. Physically based motion transformation. In Computer Graphics (Proceedings of SIGGRAPH 99), ACM SIGGRAPH, Annual Conference Series, 11–20.]] Google ScholarDigital Library
    33. Pullen, K., and Bregler, C. 2002. Motion capture assisted animation: Texturing and synthesis. ACM Transactions on Graphics 21, 3 (July), 501–508.]] Google ScholarDigital Library
    34. Rabiner, L., and Juang, B.-H. 1993. Fundamentals of Speech Recognition. Prentice Hall, New Jersey.]] Google ScholarDigital Library
    35. Rose, C., Cohen, M. F., and Bodenheimer, B. 1998. Verbs and adverbs: Multidimensional motion interpolation. IEEE Computer Graphics and Applications 18, 5, 32–40.]] Google ScholarDigital Library
    36. Shin, H. J., Lee, J., Gleicher, M., and Shin, S. Y. 2001. Computer puppetry: An importance-based approach. ACM Transactions on Graphics 20, 2 (Apr.), 67–94.]] Google ScholarDigital Library
    37. Soatto, S., Doretto, G., and Wu, Y. N. 2001. Dynamic textures. In International Conference on Computer Vision (ICCV), 439–446.]]Google Scholar
    38. Stengel, R. F. 1994. Optimal Control and Estimation. Dover Books on Advanced Mathematics, New York, NY.]]Google Scholar
    39. Sturman, D. J. 1998. Computer puppetry. IEEE Computer Graphics and Applications 18, 1, 38–45.]] Google ScholarDigital Library
    40. Tenenbaum, J. B., and Freeman, W. T. 2000. Separating style and content with bilinear models. Neural Computation 12, 1247–1283.]] Google ScholarDigital Library
    41. Unuma, M., Anjyo, K., and Tekeuchi, R. 1995. Fourier principles for emotion-based human figure animation. In Computer Graphics (Proceedings of SIGGRAPH 95), ACM SIGGRAPH, Annual Conference Series, 91–96.]] Google ScholarDigital Library
    42. Van Overschee, P., and De Moor, B. 1996. Subspace Identification for Linear Systems: Theory, Implementation, Applications. Kluwer Academic Publishers, Dordrecht, Netherlands.]]Google Scholar
    43. Vasilescu, M. A. O. 2002. Human motion signatures: analysis, synthesis, recognition. In International Conference on Pattern Recognition (ICPR), vol. 3, 456–460.]] Google ScholarDigital Library
    44. Witkin, A., and Popović, Z. 1995. Motion warping. In Computer Graphics (Proceedings of SIGGRAPH 95), ACM SIGGRAPH, Annual Conference Series, 105–108.]] Google ScholarDigital Library


ACM Digital Library Publication: