922 search results - page 21 / 185 » Learning Gaussian Process Models from Uncertain Data |
PAMI
2010
13 years 5 months ago
2010
—We present a generative model and inference algorithm for 3D nonrigid object tracking. The model, which we call G-flow, enables the joint inference of 3D position, orientation, ...
NIPS
2003
13 years 8 months ago
2003
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...
EUROSSC
2008
Springer
13 years 9 months ago
2008
Springer
Abstract. This paper describes methods and sensor technology used to identify persons from their walking characteristics. We use an array of simple binary switch floor sensors to d...
SUM
2010
Springer
13 years 5 months ago
2010
Springer
CCTV and sensor based surveillance systems are part of our daily lives now in this modern society due to the advances in telecommunications technology and the demand for better sec...
PAMI
2008
13 years 7 months ago
2008
Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demandin...