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ICASSP
2009
IEEE
14 years 2 months ago
Multi-view tracking of articulated human motion in silhouette and pose manifolds
This paper presents a multi-view articulated human motion tracking framework using particle filter with manifold learning through Gaussian process latent variable model. The dime...
Feng Guo, Gang Qian
CVPR
2009
IEEE
13 years 11 months ago
Switching Gaussian Process Dynamic Models for simultaneous composite motion tracking and recognition
Traditional dynamical systems used for motion tracking cannot effectively handle high dimensionality of the motion states and composite dynamics. In this paper, to address both is...
Jixu Chen, Minyoung Kim, Yu Wang, Qiang Ji
ICASSP
2011
IEEE
12 years 11 months ago
A partial least squares framework for speaker recognition
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
Balaji Vasan Srinivasan, Dmitry N. Zotkin, Ramani ...
ICCV
2005
IEEE
14 years 1 months ago
Priors for People Tracking from Small Training Sets
We advocate the use of Scaled Gaussian Process Latent Variable Models (SGPLVM) to learn prior models of 3D human pose for 3D people tracking. The SGPLVM simultaneously optimizes a...
Raquel Urtasun, David J. Fleet, Aaron Hertzmann, P...
ICML
2006
IEEE
14 years 8 months ago
Local distance preservation in the GP-LVM through back constraints
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
Joaquin Quiñonero Candela, Neil D. Lawrence