Leslie Ikemoto
David Forsyth
Skip Abstract Section
Skip Supplemental Material SectionAbstract
One way that artists create compelling character animations is by manipulating details of a character's motion. This process is expensive and repetitive. We show that we can make such motion editing more efficient by generalizing the edits an animator makes on short sequences of motion to other sequences. Our method predicts frames for the motion using Gaussian process models of kinematics and dynamics. These estimates are combined with probabilistic inference. Our method can be used to propagate edits from examples to an entire sequence for an existing character, and it can also be used to map a motion from a control character to a very different target character. The technique shows good generalization. For example, we show that an estimator, learned from a few seconds of edited example animation using our methods, generalizes well enough to edit minutes of character animation in a high-quality fashion. Learning is interactive: An animator who wants to improve the output can provide small, correcting examples and the system will produce improved estimates of motion. We make this interactive learning process efficient and natural with a fast, full-body IK system with novel features. Finally, we present data from interviews with professional character animators that indicate that generalizing and propagating animator edits can save artists significant time and work.
Supplemental Material
- Amaya, K., Bruderlin, A., and Calvert, T. 1996. Emotion from motion. In Proceedings of the Graphics Interface Conference. Google Scholar
Digital Library
- Arikan, O. and Forsyth, D. A. 2002. Interactive motion generation from examples. In Proceedings of the ACM SIGGRAPH'02 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Arikan, O., Forsyth, D. A., and O'Brien, J. F. 2003. Motion synthesis from annotations. In Proceedings of the ACM SIGGRAPH'03 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Beyer, H. and Holtzblatt, K. 1998. Contextual Design: A Customer-Centered Approach to Systems Designs. Morgan Kaufmann.Google Scholar
- Bodenheimer, B., Rose, C., Rosenthal, S., and Pella, J. 1997. The process of motion capture: Dealing with the data. In Proceedings of the Computer Animation and Simulation Conference.Google Scholar
- Brand, M. and Hertzmann, A. 2000. Style machines. In Proceedings of the ACM SIGGRAPH'00 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Bregler, C., Loeb, L., Chuang, E., and Deshpande, H. 2002. Turning to the masters: motion capturing cartoons. In Proceedings of the ACM SIGGRAPH'02 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Bruderlin, A. and Williams, L. 1995. Motion signal processing. In Proceedings of the ACM SIGGRAPH'95 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Chai, J. and Hodgins, J. K. 2005. Performance animation from low-dimensional control signals. In Proceedings of the ACM SIGGRAPH'05 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Chai, J. and Hodgins, J. K. 2007. Constraint-Based motion optimization using a statistical dynamic model. In Proceedings of the ACM SIGGRAPH'07 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Dontcheva, M., Yngve, G., and Popovic, Z. 2003. Layered acting for character animation. In Proceedings of the ACM SIGGRAPH'03 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Girard, M. and Maciejewski, A. A. 1985. Computational modeling for the computer animation of legged figures. In Proceedings of the ACM SIGGRAPH'85 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Gleicher, M. 1997. Motion editing with spacetime constraints. In Symposium on Interactive 3D Graphics Conference. Google ScholarDigital Library
- Gleicher, M. 1998. Retargetting motion to new characters. In Proceedings of the ACM SIGGRAPH'98 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Grassia, F. S. 1998. Practical parameterization of rotations using the exponential map. J. Graph. Tools 3. Google ScholarDigital Library
- Grochow, K., Martin, S. L., Hertzmann, A., and Popovic, Z. 2004. Style-based inverse kinematics. In Proceedings of the ACM SIGGRAPH'04 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Hsu, E., Gentry, S., and Popovic, J. 2004. Example-based control of human motion. In Proceedings of the Conference of the Science Connect of Asia (SCA'04).Google Scholar
- Hsu, E., Pulli, K., and Popovic, J. 2005. Style translation for human motion. In Proceedings of the ACM SIGGRAH'05 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Igarashi, T., Moscovich, T., and Hughes, J. F. 2005. Spatial keyframing for performance-driven animation. In Proceedings of the Conference of the Science Council of Asia (SCA'04). Google ScholarDigital Library
- Ikemoto, L., Arikan, O., and Forsyth, D. 2005. Knowing when to put your foot down. In Proceedings of the Symposium on Interactive 3D Graphics and Games (I3D). Google ScholarDigital Library
- Kovar, L. and Gleicher, M. 2004. Automated extraction and parameterization of motions in large data sets. ACM Trans. Graph. 23, 3, 559--568. Google ScholarDigital Library
- Kovar, L., Gleicher, M., and Pighin, F. 2002. Motion graphs. In Proceedings of the ACM SIGGRAPH'02 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Kovar, L., Schreiner, J., and Gleicher, M. 2002. Footskate cleanup for motion capture editing. In Proceedings of the Conference of the Science Council of Asia (SCA'02).Google Scholar
- Lawrence, N. 2004. Gaussian process models for visualisation of high dimensional data. In Proceedings of the Conference on Advances in Neural Information Processing Systems.Google Scholar
- Lawrence, N. D. and Moore, A. J. 2007. Hierarchical gaussian process latent variable models. In Proceedings of the International Conference in Machine Learning. Google ScholarDigital Library
- Lawrence, N. D. and Platt, J. C. 2004. Learning to learn with the informative vector machine. In Proceedings of the International Conference on Machine Learning (ICML). Google ScholarDigital Library
- 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. In Proceedings of the ACM SIGGRAPH'02 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Lee, J. and Shin, S. Y. 1999. A hierarchical approach to interactive motion editing for human-like figures. In Proceedings of the ACM SIGGRAPH'99 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Li, Y., Wang, T., and Shum, H.-Y. 2002. Motion texture: a two-level statistical model for character motion synthesis. In Proceedings of the ACM SIGGRAPH'02 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Liu, C. K., Hertzmann, A., and Popovic, Z. 2005. Learning physics-based motion style with nonlinear inverse optimization. In Proceedings of the ACM SIGGRAPH'05 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Liu, C. K. and Popovic, Z. 2002. Synthesis of complex dynamic character motion from simple animations. In Proceedings of the ACM SIGGRAPH'02 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Ljung, L., Ed. 1999. System Identification (2nd ed.): Theory for the User. Prentice Hall. Google ScholarDigital Library
- Mukai, T. and Kuriyama, S. 2005. Geostatistical motion interpolation. In Proceedings of the ACM SIGGRAPH'05 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Popovic, Z. and Witkin, A. 1999. Physically based motion transformation. In Proceedings of the ACM SIGGRAPH'99 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Pullen, K. and Bregler, C. 2002. Motion capture assisted animation: texturing and synthesis. In Proceedings of the ACM SIGGRAPH'02 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Rasmussen, C. and Williams, C. 2006a. Gaussian Processes for Machine Learning. MIT Press. Google ScholarDigital Library
- Rasmussen, C. and Williams, C. 2006b. Gaussian processes for machine learning software. http://www.gaussianprocess.org/gpml/code/matlab/doc/. Google ScholarDigital Library
- Rose, C., Cohen, M. F., and Bodenheimer, B. 1998. Verbs and adverbs: Multidimensional motion interpolation. IEEE Comput. Graph. Appl. 18, 5. Google ScholarDigital Library
- Safonova, A. and Hodgins, J. K. 2007. Construction and optimal search of interpolated motion graphs. Proceedings of the ACM SIGGRAPH'07 International Conference on Computer Graphics and Interactive Techniques, 106. Google ScholarDigital Library
- Shen, C., O'Brien, J. F., and Shewchuk, J. R. 2004. Interpolating and approximating implicit surfaces from polygon soup. In Proceedings of the ACM SIGGRAPH'04 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
- Shin, H. J., Kovar, L., and Gleicher, M. 2003. Physical touch-up of human motions. In Proceedings of the Pacific Graphics Conference. Google ScholarDigital Library
- Shin, H. J., Lee, J., Shin, S. Y., and Gleicher, M. 2001. Computer puppetry: An importance-based approach. ACM Trans. Graph. 20, 2. Google ScholarDigital Library
- Tak, S. and Ko, H.-S. 2005. A physically-based motion retargeting filter. ACM Trans. Graph. 24, 1. Google ScholarDigital Library
- Urtasun, R., Fleet, D. J., and Fua, P. 2006. Temporal motion models for monocular and multiview 3D human body tracking. In Comput. Vision Image Understand. SI. Modeling People. Google ScholarDigital Library
- Wang, J., Fleet, D., and Hertzmann, A. 2005. Gaussian process dynamic models. In Proceedings of the Conference on Advances in Neural Information Processing Systems (NIPS).Google Scholar
- Wang, J. M., Fleet, D. J., and Hertzmann, A. 2007. Multifactor gaussian process models for style-content separation. In Proceedings of the 24th International Conference on Machine Learning. ACM, New York, 975--982. Google ScholarDigital Library
- Wiley, D. J. and Hahn, J. K. 1997. Interpolation synthesis for articulated figure motion. In Virtual Reality Annual International Symposium (VRAIS '97). Google ScholarDigital Library
- Witkin, A. and Popovic, Z. 1995. Motion warping. In Proceedings of the ACM SIGGRAPH'95 International Conference on Computer Graphics and Interactive Techniques. Google ScholarDigital Library
Index Terms
- Generalizing motion edits with Gaussian processes
Recommendations
Driving motion control by motion capture using CG
SIGGRAPH '07: ACM SIGGRAPH 2007 sketchesIn creating the Pepsi "Dance Tron" commercial (accepted to the 2007 SIGGRAPH Computer Animation Festival), Method Studios combined motion capture with motion control in a novel manner. Following a pre-shoot motion capture session with breakdancers, we ...
Aesthetic edits for character animation
SCA '03: Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animationThe utility of an interactive tool can be measured by how pervasively it is embedded into a user's workflow. Tools for artists additionally must provide an appropriate level of control over expressive aspects of their work while suppressing unwanted ...
Rig-space motion retargeting
EG '16: Proceedings of the 37th Annual Conference of the European Association for Computer Graphics: PostersThis paper presents a framework for transferring rig parameters from a source animation to a target model, allowing artists to further refine and adjust the animation. Most previous methods only transfer animations to meshes or joint parameters. However,...
Comments