Efficient dynamic skinning with low-rank helper bone controllers

ACM Transactions on Graphics

Volumn 35, Issue 4, 2016, Pages

  Mukai, Tomohiko ^a   Kuriyama, Shigeru ^b  

^a TOKAI UNIVERSITY   (Japan)

^b TOYOHASHI UNIVERSITY OF TECHNOLOGY   (Japan)

Author keywords

Dynamic skinning; Helper bone rig; Nuclear norm optimization; State space model

Indexed keywords

COMPUTATIONAL EFFICIENCY; CONTROLLERS; DEFORMATION; DYNAMICS; INTERACTIVE COMPUTER GRAPHICS; INVARIANCE; LINEAR SYSTEMS; MUSCULOSKELETAL SYSTEM; STATE SPACE METHODS; TIME VARYING CONTROL SYSTEMS;

APPROXIMATION METHODS; DISCRETE-TIME LINEAR TIME-INVARIANT SYSTEMS; HELPER BONE RIG; INTERACTIVE APPLICATIONS; LIFE-LIKE CHARACTERS; LOW-RANK PROPERTIES; REAL-TIME COMPUTATIONS; STATE - SPACE MODELS;

BONE;

EID: 84979995373     PISSN: 07300301     EISSN: 15577368     Source Type: Journal    
DOI: 10.1145/2897824.2925905     Document Type: Conference Paper

References (41)

1. ANDERSEN, M. S., DAHL, J., AND VANDENBERGHE, L. CVXOPT: A python package for convex optimization. http://cvxopt.org.
2. ANGELIDIS, A., AND SINGH, K. 2007. Kinodynamic skinning using volume-preserving deformations. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation 2007, 129-140.
3. DE AGUIAR, E., SIGAL, L., TREUILLE, A., AND HODGINS, J. K. 2010. Stable spaces for real-time clothing. ACM Transactions on Graphics 29, 4, 106:1-106:9.
4. FAN, Y., LITVEN, J., AND PAI, D. K. 2014. Active volumetric musculoskeletal systems. ACM Transactions on Graphics 33, 4, 152:1-152:9.
5. HAHN, F., MARTIN, S., THOMASZEWSKI, B., SUMNER, R., COROS, S., AND GROSS, M. 2012. Rig-space physics. ACM Transactions on Graphics 31, 4, 72:1-72:8.
6. HAHN, F., THOMASZEWSKI, B., COROS, S., SUMNER, R., AND MARKUS. 2013. Efficient simulation of secondary motion in rigspace. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation 2013, 165-171.
7. HSU, E., PULLI, K., AND POPOVIĆ, J. 2005. Style translation for human motion. ACM Transactions on Graphics 24, 3, 1082-1089.
8. JAMES, D. L., AND PAI, D. K. 2002. Dyrt: Dynamic response textures for real time deformation simulation with graphics hardware. ACM Transactions on Graphics 21, 3, 582-585.
9. KAVAN, L., AND SORKINE, O. 2012. Elasticity-inspired deformers for character articulation. ACM Transactions on Graphics 31, 6, 196:1-196:8.
10. KAVAN, L., COLLINS, S., ZARA, J., AND O'SULLIVAN, C. 2007. Skinning with dual quaternions. In Proceedings of ACM SIGGRAPH Symposium on Interactive 3D Graphics 2007, 39-46.
11. KIM, J., AND KIM, C.-H. 2011. Implementation and application of the real-time helper-joint system. In Game Developers Conference 2011.
12. KRY, P. G., JAMES, D. L., AND PAI, D. K. 2002. Eigenskin: Real time large deformation character skinning in hardware. In Proc. of ACM SIGGRAPH/Eurographics Symposium on Computer Animation 2002, 153-159.
13. LARIMORE, W. 1990. Canonical variate analysis in identification, filtering and adaptive control. In Proceedings of Control & Decision Conference, 596-604.
14. LE, B. H., AND DENG, Z. 2012. Smooth skinning decomposition with rigid bones. ACM Transactions on Graphics 31, 6, 199:1-199:10.
15. LE, B. H., AND DENG, Z. 2014. Robust and accurate skeletal rigging from mesh sequences. ACM Transactions on Graphics 33, 4, 84.
16. LEWIS, J. P., CORDNER, M., AND FONG, N. 2000. Pose space deformation: A unified approach to shape interpolation and skeleton-driven deformation. In Proceedings of SIGGRAPH 2000, 165-172.
17. LI, D., SUEDA, S., NEOG, D. R., AND PAI, D. K. 2013. Thin skin elastodynamics. ACM Transactions on Graphics 32, 4, 49:1-49:9.
18. LIU, Z., AND VANDENBERGHE, L. 2009. Interior-point method for nuclear norm approximation with application to system identification. SIAM Journal on Matrix Analysis and Application 31, 3, 1235-1256.
19. LIU, Z., HANSSON, A., AND VANDENBERGHE, L. 2013. Nuclear norm system identification with missing inputs and outputs. Systems & Control Letters 62, 8, 605-612.
20. LIU, Z. 2009. Structured Semidefinite Programs in System Identification and Control. PhD thesis, University of California, Los Angeles.
21. LJUNG, L. 1999. System Identification: Theory for the User. Prentice Hall.
22. LOPER, M., AND BLACK, N. M. M. J. 2014. Motion and shape capture from sparse markers. ACM Transactions on Graphics 33, 6, 220:1-220:13.
23. LOPER, M., MAHMOOD, N., ROMERO, J., PONS-MOLL, G., AND BLACK, M. J. 2015. SMPL: A skinned multi-person linear model. ACM Transactions on Graphics 34, 6, 248:1-248:16.
24. MAGNENAT-THALMANN, N., LAPERRIÈRE, R., AND THALMANN, D. 1988. Joint-dependent local deformations for hand animation and object grasping. In Proceedings on Graphics Interface '88, 26-33.
25. MARI, J., STOICA, P., AND MCKELVEY, T. 2000. Vector ARMA estimation: a reliable subspace approach. IEEE Transaction on Signal Processing 48, 7, 2092-2104.
26. MOHR, A., AND GLEICHER, M. 2003. Building efficient, accurate character skins from examples. ACM Transactions on Graphics 22, 3, 562-568.
27. MOOR, B. D.,MARC MOONEN AND, L. V., AND VANDEWALLE, J. 1988. A geometrical approach for the identification of state space models with singular value decomposition. In International Conference on Acoustics, Speech, and Signal Processing, vol. 4, 2244-2247.
28. MUKAI, T. 2015. Building helper bone rigs from examples. In Proceedings of ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games 2015, 77-84.
29. NEUMANN, T., VARANASI, K., HASLER, N., WACKER, M., MAGNOR, M., AND THEOBALT, C. 2013. Capture and statistical modeling of arm-muscle deformations. Computer Graphics Forum 32, 2, 285-294.
30. PARK, S. I., AND HODGINS, J. K. 2008. Data-driven modeling of skin and muscle deformation. ACM Transactions on Graphics 27, 3, 96:1-96:6.
31. PARKS, J. 2005. Helper joints: Advanced deformations on runtime characters. In Game Developers Conference 2005.
32. PONS-MOLL, G., ROMERO, J., MAHMOOD, N., AND BLACK, M. J. 2015. Dyna: A model of dynamic human shape in motion. ACM Transactions on Graphics 33, 4, 120:1-120:10.
33. RECHT, B., FAZEL, M., AND PARRILO, P. A. 2010. Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization. SIAM Review 52, 3, 471-501.
34. RUMMAN, N. A., AND FRATARCANGELI, M. 2015. Positionbased skinning for soft articulated characters. Computer Graphics Forum 34, 6, 240-250.
35. SHI, X., ZHOU, K., TONG, Y., DESBRUN, M., BAO, H., AND GUO, B. 2008. Example-based dynamic skinning in real time. ACM Transactions on Graphics 27, 3, 29:1-29:8.
36. TIBSHIRANI, R. 2011. Regression shrinkage and selection via the lasso: A retrospective. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 73, 3, 273-282.
37. VERHAEGEN, M. 1994. Identification of the deterministic part of MIMO state space models given in innovations form from inputoutput data. Automatica 30, 1, 61-74.
38. VIBERG, M. 1995. On subspace-based methods for the identification of linear time-invariant systems. Automatica 31, 12, 1835-1852.
39. WANG, X. C., AND PHILLIPS, C. 2002. Multi-weight enveloping: Least-squares approximation techniques for skin animation. In Proceedings of ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 129-138.
40. WANG, R. Y., PULLI, K., AND POPOVIĆ, J. 2007. Real-time enveloping with rotational regression. ACM Transactions on Graphics 26, 3, 73:1-73:10.
41. XIA, S., WANG, C., CHAI, J., AND HODGINS, J. 2015. Realtime style transfer for unlabeled heterogeneous human motion. ACM Transactions on Graphics 34, 4, 119:1-119:10.