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» Method of Motion Data Processing Based on Manifold Learning
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CVPR
2010
IEEE
13 years 6 months ago
Multi-structure model selection via kernel optimisation
Our goal is to fit the multiple instances (or structures) of a generic model existing in data. Here we propose a novel model selection scheme to estimate the number of genuine str...
Tat-Jun Chin, David Suter, Hanzi Wang
JMLR
2010
129views more  JMLR 2010»
13 years 3 months ago
Efficient Multioutput Gaussian Processes through Variational Inducing Kernels
Interest in multioutput kernel methods is increasing, whether under the guise of multitask learning, multisensor networks or structured output data. From the Gaussian process pers...
Mauricio Alvarez, David Luengo, Michalis Titsias, ...
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
IJCAI
2007
13 years 10 months ago
WiFi-SLAM Using Gaussian Process Latent Variable Models
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...
Brian Ferris, Dieter Fox, Neil D. Lawrence
AVSS
2007
IEEE
14 years 2 months ago
Model-based human posture estimation for gesture analysis in an opportunistic fusion smart camera network
In multi-camera networks rich visual data is provided both spatially and temporally. In this paper a method of human posture estimation is described incorporating the concept of a...
Chen Wu, Hamid K. Aghajan