25 search results - page 2 / 5 » Learning GP-BayesFilters via Gaussian process latent variabl... |
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
HUMO
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. Learned, activity-specific motion models are useful for human pose and motion estimation. Nevertheless, while the use of activityspecific models simplifies monocular t...
IJCAI
2007
13 years 9 months ago
2007
WiFi localization, the task of determining the physical location of a mobile device from wireless signal strengths, has been shown to be an accurate method of indoor and outdoor l...
PAMI
2008
13 years 7 months ago
2008
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
ICIP
2007
IEEE
14 years 9 months ago
2007
IEEE
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...