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ECCV
2008
Springer
14 years 9 months ago
Tracking of Abrupt Motion Using Wang-Landau Monte Carlo Estimation
Abstract. We propose a novel tracking algorithm based on the WangLandau Monte Carlo sampling method which efficiently deals with the abrupt motions. Abrupt motions could cause conv...
Junseok Kwon, Kyoung Mu Lee
IPSN
2004
Springer
14 years 24 days ago
A probabilistic approach to inference with limited information in sensor networks
We present a methodology for a sensor network to answer queries with limited and stochastic information using probabilistic techniques. This capability is useful in that it allows...
Rahul Biswas, Sebastian Thrun, Leonidas J. Guibas
ACCV
2006
Springer
14 years 1 months ago
Tracking Targets Via Particle Based Belief Propagation
We first formulate multiple targets tracking problem in a dynamic Markov network(DMN)which is derived from a MRFs for joint target state and a binary process for occlusion of dual...
Jianru Xue, Nanning Zheng, Xiaopin Zhong
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
TIP
2008
111views more  TIP 2008»
13 years 7 months ago
Unsupervised Bayesian Convex Deconvolution Based on a Field With an Explicit Partition Function
This paper proposes a non-Gaussian Markov field with a special feature: an explicit partition function. To the best of our knowledge, this is an original contribution. Moreover, th...
Jean-François Giovannelli