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» Niching in Monte Carlo Filtering Algorithms
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WSC
2008
13 years 10 months ago
A particle filtering framework for randomized optimization algorithms
We propose a framework for optimization problems based on particle filtering (also called Sequential Monte Carlo method). This framework unifies and provides new insight into rand...
Enlu Zhou, Michael C. Fu, Steven I. Marcus
IJCNN
2006
IEEE
14 years 1 months ago
A Monte Carlo Sequential Estimation for Point Process Optimum Filtering
— Adaptive filtering is normally utilized to estimate system states or outputs from continuous valued observations, and it is of limited use when the observations are discrete e...
Yiwen Wang 0002, António R. C. Paiva, Jose ...
ICPR
2006
IEEE
14 years 8 months ago
An integrated Monte Carlo data association framework for multi-object tracking
We propose a sequential Monte Carlo data association algorithm based on a two-level computational framework for tracking varying number of interacting objects in dynamic scene. Fi...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
AAAI
2000
13 years 9 months ago
Monte Carlo Localization with Mixture Proposal Distribution
Monte Carlo localization (MCL) is a Bayesian algorithm for mobile robot localization based on particle filters, which has enjoyed great practical success. This paper points out a ...
Sebastian Thrun, Dieter Fox, Wolfram Burgard
IJCV
2008
188views more  IJCV 2008»
13 years 7 months ago
Partial Linear Gaussian Models for Tracking in Image Sequences Using Sequential Monte Carlo Methods
The recent development of Sequential Monte Carlo methods (also called particle filters) has enabled the definition of efficient algorithms for tracking applications in image sequen...
Elise Arnaud, Étienne Mémin