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» Estimating random variables from random sparse observations
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WACV
2002
IEEE
14 years 1 months ago
Range Synthesis for 3D Environment Modeling
In this paper a range synthesis algorithm is proposed as an initial solution to the problem of 3D environment modeling from sparse data. We develop a statistical learning method f...
Luz Abril Torres-Méndez, Gregory Dudek
ISPW
2008
IEEE
14 years 3 months ago
Accurate Estimates without Calibration?
Most process models calibrate their internal settings using historical data. Collecting this data is expensive, tedious, and often an incomplete process. Is it possible to make acc...
Tim Menzies, Oussama El-Rawas, Barry W. Boehm, Ray...
NIPS
2007
13 years 10 months ago
People Tracking with the Laplacian Eigenmaps Latent Variable Model
Reliably recovering 3D human pose from monocular video requires models that bias the estimates towards typical human poses and motions. We construct priors for people tracking usi...
Zhengdong Lu, Miguel Á. Carreira-Perpi&ntil...
ICASSP
2008
IEEE
14 years 3 months ago
A GIS-like training algorithm for log-linear models with hidden variables
Conditional Random Fields (CRFs) are often estimated using an entropy based criterion in combination with Generalized Iterative Scaling (GIS). GIS offers, upon others, the immedi...
Georg Heigold, Thomas Deselaers, Ralf Schlüte...
PSIVT
2007
Springer
129views Multimedia» more  PSIVT 2007»
14 years 2 months ago
Multi-target Tracking with Poisson Processes Observations
This paper considers the problem of Bayesian inference in dynamical models with time-varying dimension. These models have been studied in the context of multiple target tracking pr...
Sergio Hernández, Paul Teal