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ICPR
2002
IEEE
15 years 11 months ago
Boosting and Structure Learning in Dynamic Bayesian Networks for Audio-Visual Speaker Detection
Bayesian networks are an attractive modeling tool for human sensing, as they combine an intuitive graphical representation with ef?cient algorithms for inference and learning. Ear...
Tanzeem Choudhury, James M. Rehg, Vladimir Pavlovi...
ISRR
2005
Springer
178views Robotics» more  ISRR 2005»
15 years 3 months ago
Improved Estimation of Target Velocity Using Multiple Model Estimation and a Dynamic Bayesian Network for a Robotic Tracker of O
A vision-based automatic tracking system for ocean animals in the midwater has been demonstrated in Monterey Bay, CA. Currently, the input to this system is a measurement of relati...
Aaron Plotnik, Stephen Rock
IDEAL
2004
Springer
15 years 3 months ago
Stock Trading by Modelling Price Trend with Dynamic Bayesian Networks
We study a stock trading method based on dynamic bayesian networks to model the dynamics of the trend of stock prices. We design a three level hierarchical hidden Markov model (HHM...
Jangmin O, Jae Won Lee, Sung-Bae Park, Byoung-Tak ...
AAAI
2008
15 years 3 days ago
Reducing Particle Filtering Complexity for 3D Motion Capture using Dynamic Bayesian Networks
Particle filtering algorithms can be used for the monitoring of dynamic systems with continuous state variables and without any constraints on the form of the probability distribu...
Cédric Rose, Jamal Saboune, François...
UAI
2000
14 years 11 months ago
Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
Particle filters (PFs) are powerful samplingbased inference/learning algorithms for dynamic Bayesian networks (DBNs). They allow us to treat, in a principled way, any type of prob...
Arnaud Doucet, Nando de Freitas, Kevin P. Murphy, ...