Abstract
Responsive motion generation of avatars who have physical interactions with their environment is a key issue in VR and video games. We present a performance-driven avatar control interface with physically-based motion retrieval. When the interaction between the user-controlled avatar and its environment is going to happen, the avatar has to select the motion clip that satisfies both kinematic and dynamic constraints. A two-steps process is proposed. Firstly, it selects a set of candidate motions according to the performance of the user. Secondly, these candidate motions are further ranked according to their capability to satisfy dynamic constraints such as balance and comfort. The motion associated with the highest score is finally adapted in order to accurately satisfy the kinematic constraints imposed by the virtual world. The experimental results show that it can efficiently control the avatar with an intuitive performance-based interface based on few motion sensors.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Chai, J., Hodgins, J.: Performance animation from low-dimensional control signals. ACM Trans. on Graph. 24(3), 686–696 (2005)
Liang, X., Li, Q., Zhang, X., Zhang, S., Geng, W.: Performance-driven motion choreographing with accelerometers. Computer Animation and Virtual Worlds 20(2-3), 89–99 (2009)
Shiratori, T., Hodgins, J.: Accelerometer-based user interfaces for the control of a physically simulated character. ACM Trans. on Graph. 27(5), 1–9 (2008)
Liu, F., Zhuang, Y., Wu, F., Pan, Y.: 3d motion retrieval with motion index tree. Computer Vision and Image Understanding 92(2-3), 265–284 (2003)
Keogh, E., Palpanas, T., Zordan, V., Gunopulos, D., Cardle, M.: Indexing large human-motion databases. In: Proceedings of the 30th International Conference on Very Large Data Bases, pp. 780–791 (2004)
Muller, M., Roder, T., Clausen, M.: Efficient content-based retrieval of motion capture data. ACM Trans. on Graph. 24(3), 677–685 (2005)
Slyper, R., Hodgins, J.: Action capture with accelerometers. In: Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 193–199 (2008)
Liang, X., Zhang, S., Li, Q., Pronost, N., Geng, W., Multon, F.: Intuitive motion retrieval with motion sensors. In: Proceedings of Computer Graphics International, pp. 64–71 (2008)
Hodgins, J., Wooten, W., Brogan, D., O’Brien, J.: Animating human athletics. In: Proceedings of ACM SIGGRAPH 1995, pp. 71–78 (1995)
Hodgins, J., Pollard, N.: Adapting simulated behaviors for new characters. In: Proceedings of ACM SIGGRAPH 1997, pp. 153–162 (1997)
Wooten, W.L., Hodgins, J.: Animation of human diving. Computer Graphics Forum 15, 3–13 (1996)
Yin, K., Loken, K., van de Panne, M.: Simbicon: Simple biped locomotion control. ACM Trans. on Graph. 26(3), 105 (2007)
Sok, K.W., Kim, M., Lee, J.: Simulating biped behaviors from human motion data. ACM Trans. Graph. 26(3), 107 (2007)
Zordan, V., Hodgins, J.: Motion capture-driven simulations that hit and react. In: Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 89–96 (2002)
Tak, S., Song, O.Y., Ko, H.S.: Motion balance filtering. Computer Graphics Forum 19(3), 437–446 (2000)
Yamane, K., Nakamura, Y.: Dynamic filters - concept and implementations of online motion generator for human figures. IEEE Trans. on Robotics and Automation 19(3), 421–432 (2003)
Tak, S., Ko, H.: A physically-based motion retargeting filter. ACM Trans. on Graph. 24(1), 98–117 (2005)
Tak, S., Song, O.Y., Ko, H.S.: Spacetime sweeping: a interactive dynamic constraints solver. In: Proceedings of IEEE Computer Animation, pp. 261–270 (2002)
Witkin, A., Kass, M.: Spacetime constraints. In: Proceedings of ACM SIGGRAPH, pp. 159–168 (1988)
Sofonova, A., Hodgins, J., Pollard, N.: Synthesizing physically realistic human motion in lowdimensional, behavior-specific spaces. ACM Trans., on Graph. 23(3), 514–521 (2004)
Jain, S., Ye, Y., Liu, K.: Optimization-based interactive motion synthesis. ACM Trans. on Graph. 28(1), 10:1–10:12 (2009)
Shin, H., Kovar, L., Gleicher, M.: Physical touch-up of human motions. In: Proceedings of Pacific Graphics 2003, pp. 194–203 (2003)
Zordan, V., Majkowska, A., Chiu, B., Fast, M.: Dynamic response for motion capture animation. ACM Trans. on Graph. 24, 697–701 (2005)
Mitake, H., Asano, K., Aoki, T., Marc, S., Sato, M., Hasegawa, S.: Physics-driven multi dimensional keyframe animation for artist-directable interactive character. Computer Graphics Forum 28(2), 279–287 (2009)
Treuille, A., Lee, Y., Popović, Z.: Near-optimal character animation with continuous control. ACM Trans. Graph. 26(3), 7:1–7:7 (2007)
Cooper, S., Hertzmann, A., Popović, Z.: Active learning for real-time motion controllers. ACM Trans. on Graph. 26(3), 5 (2007)
Ishigaki, S., White, T., Zordan, V.B., Liu, C.K.: Performance-based control interface for character animation. ACM Trans. on Graph. 28(3), 61:1–61:8 (2009)
Kajita, S.: Humanoid Robot, Ohmsha, Japan (2005)
Kulpa, R., Multon, F., Arnaldi, B.: Morphology-independent representation of motions for interactive human-like animation. Computer Graphics Forum 24, 343–352 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liang, X., Hoyet, L., Geng, W., Multon, F. (2010). Responsive Action Generation by Physically-Based Motion Retrieval and Adaptation. In: Boulic, R., Chrysanthou, Y., Komura, T. (eds) Motion in Games. MIG 2010. Lecture Notes in Computer Science, vol 6459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16958-8_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-16958-8_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16957-1
Online ISBN: 978-3-642-16958-8
eBook Packages: Computer ScienceComputer Science (R0)