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» Unsupervised Learning of Human Motion Models
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CVPR
2006
IEEE
15 years 27 days ago
3D People Tracking with Gaussian Process Dynamical Models
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
Raquel Urtasun, David J. Fleet, Pascal Fua
ICRA
2009
IEEE
163views Robotics» more  ICRA 2009»
14 years 5 months ago
Markerless human motion tracking with a flexible model and appearance learning
— A new approach to the 3D human motion tracking problem is proposed, which combines several particle filters with a physical simulation of a flexible body model. The flexible...
Florian Hecht, Pedram Azad, Rüdiger Dillmann
CVPR
2012
IEEE
12 years 1 months ago
Unsupervised learning of translation invariant occlusive components
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Zhenwen Dai, Jörg Lücke
CVPR
1997
IEEE
15 years 27 days ago
Learning Parameterized Models of Image Motion
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
Michael J. Black, Yaser Yacoob, Allan D. Jepson, D...