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ICASSP
2008
IEEE
14 years 2 months ago
On nonlinear transformations of stochastic variables and its application to nonlinear filtering
A class of nonlinear transformation-based filters (NLTF) for state estimation is proposed. The nonlinear transformations that can be used include first (TT1) and second (TT2) or...
Fredrik Gustafsson, Gustaf Hendeby
ICMCS
2007
IEEE
191views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Variable Number of "Informative" Particles for Object Tracking
Particle filter is a sequential Monte Carlo method for object tracking in a recursive Bayesian filtering framework. The efficiency and accuracy of the particle filter depends on t...
Yu Huang, Joan Llach
ICASSP
2011
IEEE
12 years 11 months ago
Particle algorithms for filtering in high dimensional state spaces: A case study in group object tracking
We briefly present the current state-of-the-art approaches for group and extended object tracking with an emphasis on particle methods which have high potential to handle complex...
Lyudmila Mihaylova, Avishy Carmi
ACL
2012
11 years 10 months ago
Using Rejuvenation to Improve Particle Filtering for Bayesian Word Segmentation
We present a novel extension to a recently proposed incremental learning algorithm for the word segmentation problem originally introduced in Goldwater (2006). By adding rejuvenat...
Benjamin Börschinger, Mark Johnson
CVPR
2012
IEEE
11 years 10 months ago
Decentralized particle filter for joint individual-group tracking
In this paper, we address the task of tracking groups of people in surveillance scenarios. This is a major challenge in computer vision, since groups are structured entities, subj...
Loris Bazzani, Marco Cristani, Vittorio Murino