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» Motion vector recovery with Gaussian Process Regression
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HUMO
2007
Springer
14 years 2 months ago
Modeling Human Locomotion with Topologically Constrained Latent Variable Models
Abstract. Learned, activity-specific motion models are useful for human pose and motion estimation. Nevertheless, while the use of activityspecific models simplifies monocular t...
Raquel Urtasun, David J. Fleet, Neil D. Lawrence
ECCV
1998
Springer
14 years 9 months ago
Robust Techniques for the Estimation of Structure from Motion in the Uncalibrated Case
Abstract. Robust techniques are developed for determining structure from motion in the uncalibrated case. The structure recovery is based on previous work [7] in which it was shown...
Michael J. Brooks, Wojciech Chojnacki, Anton van d...
JMLR
2011
148views more  JMLR 2011»
13 years 2 months ago
Bayesian Generalized Kernel Mixed Models
We propose a fully Bayesian methodology for generalized kernel mixed models (GKMMs), which are extensions of generalized linear mixed models in the feature space induced by a repr...
Zhihua Zhang, Guang Dai, Michael I. Jordan
PAMI
2006
358views more  PAMI 2006»
13 years 7 months ago
Recovering 3D Human Pose from Monocular Images
We describe a learning based method for recovering 3D human body pose from single images and monocular image sequences. Our approach requires neither an explicit body model nor pri...
Ankur Agarwal, Bill Triggs
IJCNN
2008
IEEE
14 years 2 months ago
A neural network approach to ordinal regression
— Ordinal regression is an important type of learning, which has properties of both classification and regression. Here we describe an effective approach to adapt a traditional ...
Jianlin Cheng, Zheng Wang, Gianluca Pollastri