Journal of KIISE:Computer Systems and Theory (한국정보과학회논문지:시스템및이론)

Korean Institute of Information Scientists and Engineers (한국정보과학회)
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Segmentation and Transition Techniques for Plausible Dance Motion Generation

자연스러운 춤 동작 생성을 위한 분절화와 전이기법

  • Published : 2008.08.15
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Abstract

This paper presents novel segmentation and transition techniques for dancing motion synthesis. The segmentation method for dancing motions is based on Laban Movement Analysis (LMA). We assume a dance sequence as a set of small dancing motions. To segment a dancing motion is a subjective, psychological, and complex problem, so we extract the shape factor of LMA from a dance motion and observe shape's changes to find the boundaries of dance segments. We also introduce a transition method that meets constraints on the feet. This method that is based on a linear interpolation modifies the intermediate posture motion after analyzing footprint positions. The posture could be a key-frame between source motion and target motion on the transition. With the proposed techniques, it would be easy for multimedia applications to generate plausible dance motions.

본 연구에서는 긴 춤 시퀀스를 춤 세그먼트들로 분절하는 방법과 이 춤 세그먼트들의 자연스러운 연결을 위한 전이 방법을 제안한다. 제안하는 분절화(segmentation) 방법은 라반 운동 분석(LMA)을 기반으로 한다. 춤 세그먼트 안에서 춤추는 캐릭터 외형의 변화가 일정한 패턴을 이루며 발생하는 것에 착안하여, 패턴이 변화되는 구간에서 춤 세그먼트의 경계를 찾는다. 이 방법은 춤 시퀀스에서 얻어낸 LMA의 외형 곡선에서 키 자세(key pose)를 찾고, 나타나는 패턴을 분석하여 수행된다. 제안하는 전이(transition) 방법은 춤과 같이 유사도가 낮은 모션을 대상으로 하고 있다. 이 방법은 선형 보간 방법을 기본으로 이용하고, 발에 발생하는 제약사항을 만족하도록 중간 자세를 생성하고, 전이 구간 중간의 키 프레임으로 사용하여 전이를 완성한다. 우리가 제안하는 방법들은 기존의 춤 모션 데이타를 사용한 새로운 춤 시퀀스 합성에 활용이 가능하다.

Keywords

References

  1. K. Hachimura, K. Takashina and M. Yoshimura, "Analysis and Evaluation of Dancing Movement Based on LMA," 2005 IEEE International Workshop on Robots and Human Interactive Communication, pp. 294-299, 2005
  2. K. Kahol, P. Tripathi and S. Panchanathan, "Automated Gesture Segmentation from Dance Sequences," The Sixth IEEE International Conference on Automatic Face and Gesture Recognition, pp. 883-888, 2004
  3. L. Zhao, "Synthesis and Acquisition of Laban Movement Analysis Qualitative Parameters for Communicative Gestures," PhD dissertation, University of Pennsylvania, 2006
  4. A. Camurri, I. Lagerlöf and G. Volpe, "Recognizing Emotion from Dance Movement Comparison of Spectator Recognition and Automated Technique," International Journal of Human-Computer Studies, Vol.59, No.1, pp. 216-225, 2003
  5. D. Chi, M. Costa, L. Zhao and N. Badler, "The EMOTE Model for Effort and Shape," SIGGRAPH 2000, pp. 173-182, 2000
  6. T. Nakata, T.Mori and T.Sato, "Analysis of Impression of Robot Bodily Expression," Journal of Robotics and Mechatronics. Vol.14, No.1, pp. 27- 36, 2002 https://doi.org/10.20965/jrm.2002.p0027
  7. T. Kim, S.I. Park and S.Y. Shin. "Rhythmic- motion Synthesis Based on Motion-beat Analysis," ACM Transactions on Graphics. Vol.22, No.3, pp. 392-401, 2003 https://doi.org/10.1145/882262.882283
  8. L. Kovar, M. Gleicher and F. Pighin, "Motion Graphs," ACM Transactions on Graphics, Vol.21, No.3, pp. 473-482, 2002
  9. O. Arikan and D. Forsythe, "Interactive Motion Generation from Examples," The 29th annual conference on Computer graphics and interactive techniques, pp. 483-490, 2002
  10. J. Lee, J. Chai, P. S. A. Reitsma, and J. K. Hodgins, N.S. Pollard, "Interactive control of avatars animated with human motion data," ACM Transactions on Graphics, Vol.21, No.3, pp. 491- 500, 2002
  11. O. Arikan and D. A. Forsyth, "Interactive Motion Generation from Examples," ACM Transactions on Graphics, Vol.21, No.3, pp. 483-490, 2002
  12. T. S. Wang, H. Y. Shum, Y. Q. Xu and N.N. Zheng, "Unsupervised Analysis of Human Gestures," Lecture Notes in Computer Science, Vol.2195, pp. 174-181, 2001
  13. K. Kahol, P. Tripathi, and S. Panchanathan, "Recognizing Whole Body Movements and Gestures through Activities in Human Anatomy," International Conference on Systemics, Cybernetics and Informatics, 2005
  14. J. Assa, Y. Caspi and D. Cohen-Or, "Action Synopsis: Pose Selection and Illustration," ACM Transactions on Graphics, Vol.24, No.3, pp. 667-676, 2005 https://doi.org/10.1145/1073204.1073246
  15. T. Weingaertner, S. Hassfeld and R. Dillmann, "Human Motion Analysis: A Review," 1997 IEEE Workshop on Motion of Non-Rigid and Articulated Objects. 1997
  16. J. Barbic, A. Safonova, J. Y. Pan, C. Faloutsos, J. K. Hodgins, N. S. Pollard, "Segmentation Motion Capture Data into Distinct Behaviors," Graphics Interface 2004, pp. 185-194, 2004
  17. S. I. Park, H. J. Shin and S. Y. Shin, "On-line Locomotion Generation Based on Motion Blending," ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 105-111, 2002
  18. L. Ikemoto, O. Arikan and D. Forsyth, "Quick Transitions with Cached Multi-way Blends," ACM Symposium on Interactive 3D Graphics, pp. 145- 151, 2007
  19. L. Kovar and M. Gleicher, "Flexible Automatic Motion Blending with Registration Curves," ACM SIGGRAPH/ Eurographics Symposium on Computer Animation, pp. 214-224, 2003
  20. C. Rose, B. Guenter, B. Bodenheimer, and M. F. Cohen, "Efficient Generation of Motion Transitions using Spacetime Constraints," SIGGRAPH 1996, pp. 147-154, 1996
  21. A. Safonova and J. K. Hodgins, "Analyzing the Physical Correctness of Interpolated Human Motion," ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 171-180, 2005
  22. K. L. Clarkson, K. Mehlhorn, and R. Seide, "Four Results on Randomized Incremental Constructions," Computational Geometry: Theory and Applications, Vol.3, No.4, pp. 185-121, 1993 https://doi.org/10.1016/0925-7721(93)90009-U
  23. L. Ikemoto, O. Arikan and D. Forsyth, "Knowing When To Put Your Foot Down," ACM SIGGRAPH/Eurographics Symposium on Interactive 3D Graphics, pp. 49-53, 2006
  24. L. Kovar, M. Gleicher, and J. Schreiner, "Footskate Cleanup for Motion Capture Editing," ACM SIGGRAPH Symposium on Computer Animation 2002, pp.97-104, 2002
  25. J. Wang and B. Bodenheimer, "Computing the Duration of Motion Transitions: An Empirical Approach," ACM SIGGRAPH Symposium on Computer Animation, pp. 335-344, 2004