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ICASSP
2011
IEEE
9 years 6 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
AAAI
2008
10 years 4 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...
CORR
2008
Springer
91views Education» more  CORR 2008»
10 years 2 months ago
Particle Filtering for Large Dimensional State Spaces with Multimodal Observation Likelihoods
We study efficient importance sampling techniques for particle filtering (PF) when either (a) the observation likelihood (OL) is frequently multimodal or heavy-tailed, or (b) the s...
Namrata Vaswani
FGR
2004
IEEE
105views Biometrics» more  FGR 2004»
10 years 6 months ago
Particle Filtering with Factorized Likelihoods for Tracking Facial Features
In the recent years particle filtering has been the dominant paradigm for tracking facial and body features, recognizing temporal events and reasoning in uncertainty. A major prob...
Ioannis Patras, Maja Pantic
PAMI
2007
214views more  PAMI 2007»
10 years 2 months ago
Tracking Deforming Objects Using Particle Filtering for Geometric Active Contours
—Tracking deforming objects involves estimating the global motion of the object and its local deformations as a function of time. Tracking algorithms using Kalman filters or part...
Yogesh Rathi, Namrata Vaswani, Allen Tannenbaum, A...
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