Gaussian process dynamical models for human motion
We introduce Gaussian process dynamical models (GPDM) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensionalmotion capture data. A GPDM is a latent variable model. It comprises a low-dimensional latent space with associated dynamics, a...
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 30(2008), 2 vom: 15. Feb., Seite 283-98 |
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| Auteur principal: | |
| Autres auteurs: | , |
| Format: | Article |
| Langue: | English |
| Publié: |
2008
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence |
| Sujets: | Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. |