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PKDD
2009
Springer
146views Data Mining» more  PKDD 2009»
14 years 5 days ago
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding prob...
Eva Besada-Portas, Sergey M. Plis, Jesús Ma...
ICPR
2002
IEEE
14 years 8 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»
14 years 1 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
14 years 29 days 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
13 years 10 months 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...