Modeling human locomotion with topologically constrained latent variable models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4814 LNCS, Issue , 2007, Pages 104-118

  Urtasun, Raquel ^a   Fleet, David J ^b   Lawrence, Neil D ^c  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b UNIVERSITY OF TORONTO   (Canada)

^c UNIVERSITY OF MANCHESTER   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; CONSTRAINT THEORY; GAUSSIAN DISTRIBUTION; LEARNING SYSTEMS; MATHEMATICAL MODELS; TOPOLOGY;

LATENT CONFIGURATIONS; MONOCULAR TRACKING; STYLISTIC VARIATIONS;

MOTION ESTIMATION;

EID: 38149117180     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75703-0_8     Document Type: Conference Paper

References (29)

1. Arikan, O., Forsyth, D.: Interactive motion generation from examples. In: SIGGRAPH, pp. 483-490 (2002)
2. Bissacco, A.: Modeling and Learning Contact Dynamics in Human Motion. In: CVPR, pp. 421-428 (2005)
3. Brand, M., Hertzmann, A.: Style Machines. In: SIGGRAPH, pp. 183-192 (2000)
4. Elgammal, A., Lee, C.: Separating Style and Content on a Nonlinear Manifold. In: CVPR, vol. 1, pp. 478-485 (2004)
5. Grochow, K., Martin, S., Hertzmann, A., Popovic, Z.: Style-based inverse kinematics. In: SIGGRAPH, pp. 522-531 (2004)
6. Vasilescu, M.A.: Human Motion Signatures: Analysis, Synthesis. In: ICPR, pp. 456-460 (2002)
7. Kovar, L., Gleicher, M., Pighin, F.: Motion Graphs. In: SIGGRAPH, pp. 473-482 (2002)
8. Lawrence, N., Quinonero-Candela, J.: Local distance preservation in the GP-LVM through back constraints. In: ICML, pp. 513-520 (2006)
9. Lawrence, N.D., Seeger, M., Herbrich, R.: Fast sparse Gaussian process methods: The informative vector machine. In: NIPS, pp. 609-616 (2003)
10. Lawrence, N.D.: Gaussian Process Models for Visualisation of High Dimensional Data. In: NIPS (2004)
11. Lawrence, N.: Learning for larger datasets with the Gaussian process latent variable model. In: AISTATS (2007)
12. Li, R., Yang, M.H., Sclaroff, S., Tian, T.: Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 137-150. Springer, Heidelberg (2006)
13. Li, Y., Wang, T., Shum, H.: Motion Texture: A Two-Level Statistical Model for Character Motion Synthesis. In: SIGGRAPH, pp. 465-472 (2002)
14. Moon, K., Pavlovic, V.: Impact of Dynamics on Subspace Embedding and Tracking of Sequences. In: CVPR, pp. 198-205 (2006)
15. Pavlovic, J.M., Rehg, J., MacCormick, J.: Learning switching linear models of human motion. In: NIPS, pp. 981-987 (2000)
16. Quiñonero-Candela, J., Rasmussen, C.E.: A Unifying View of Sparse Approximate Gaussian Process Regression. In: JMLR, vol. 6, pp. 1939-1959 (2006)
17. Rasmussen, C.E., Williams, C.K.: Gaussian Process for Machine Learning. MIT Press, Cambridge (2006)
18. Roweis, S., Saul, L.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323-2326 (2000)
19. Sidenbladh, H., Black, M.J., Sigal, L.: Implicit Probabilistic Models of Human Motion for Synthesis and Tracking. In: Tistarelli, M., Bigun, J., Jain, A.K. (eds.) ECCV 2002. LNCS, pp. 784-800. Springer, Heidelberg (2002)
20. Sminchisescu, C., Jepson, A.: Generative Modeling for Continuous Non-Linearly Embedded Visual Inference. In: ICML, pp. 96-103 (2004)
21. Snelson, E., Ghahramani, Z.: Sparse Gaussian processes using pseudo-inputs. In: NIPS, pp. 1257-1264 (2006)
22. Taylor, G.W., Hinton, G.E., Roweis, S.: Modeling human motion using binary latent variables. In: NIPS, pp. 1345-1352 (2007)
23. Tenenbaum, J., de Silva, V., Langford, J.: A global geometric framework for nonlinear dimensionality reduction. Science 290(5500), 2319-2323 (2000)
24. Tian, T., Li, R., Sclaroff, S.: Articulated Pose Estimation in a Learned Smooth Space of Feasible Solutions. In: CVPR Learning Workshop (2005)
25. Urtasun, R.: Motion Models for Robust 3D Human Body Tracking. PhD thesis, EPFL (2006)
26. Urtasun, R., Fleet, D.J., Fua, P.: 3d people tracking with gaussian process dynamical models. In: CVPR, vol. 1, pp. 238-245 (2006)
27. Urtasun, R., Fleet, D.J., Hertzman, A., Fua, P.: Priors for people tracking from small training sets. In: ICCV, pp. 403-410 (2005)
28. Wang, J., Fleet, D.J., Hertzman, A.: Gaussian Process dynamical models. In: NIPS, pp. 1441-1448 (2005)
29. Wang, J., Fleet, D.J., Hertzman, A.: Multifactor Gaussian Process Models for Style-Content Separation. In: ICML, pp. 975-982 (2007)