Gaussian process latent variable models for human pose estimation

Gaussian process latent variable models for human pose estimation

We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1] encapsulating both pose and silhouette features Our method is generative, this allows us to model the ambiguities of a...

Полное описание

Библиографические подробности
Главные авторы:	Ek, CH, Torr, PHS, Lawrence, ND
Формат:	Conference item
Язык:	English
Опубликовано:	Springer 2008

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