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Robust multi-Bernoulli filtering for visual tracking
The 2014 International Conference on Control, Automation and Information Sciences (ICCAIS 2014), 2014To achieve reliable multi-object filtering in vision application, it is of great importance to determine appropriate model parameters. Parameters such as motion and measurement noise covariance can be chosen based on the image frame rate and the property of the designed detector. However, it is not trivial to obtain the average number of false positive
Du Yong Kim, Moongu Jeon
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A Tutorial on Bernoulli Filters: Theory, Implementation and Applications
IEEE Transactions on Signal Processing, 2013Bernoulli filters are a class of exact Bayesian filters for non-linear/non-Gaussian recursive estimation of dynamic systems, recently emerged from the random set theoretical framework. The common feature of Bernoulli filters is that they are designed for stochastic dynamic systems which randomly switch on and off.
Branko Ristic 0001 +3 more
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Log-domain filtering and the Bernoulli cell
IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 1999In this paper, the dynamic behavior of a nonlinear circuit element termed a Bernoulli cell is described, which is composed of a suitably biased bipolar junction transistor (BJT) and an emitter connected grounded capacitor. This cell has application in the synthesis of log-domain filters, since it facilitates the development of a low-level design ...
E.M. Drakakis, A.J. Payne, C. Toumazou
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Multi-Sensor Joint Detection and Tracking with the Bernoulli Filter
IEEE Transactions on Aerospace and Electronic Systems, 2012This paper proposes a filter for joint detection and tracking of a single target using measurements from multiple sensors under the presence of detection uncertainty and clutter. To capture the target presence/absence in the surveillance region as well as its kinematic state, we represent the target state as a set that can take on either the empty set ...
Ba-Tuong Vo +3 more
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Multiple Model Multi-Bernoulli Filters for Manoeuvering Targets
IEEE Transactions on Aerospace and Electronic Systems, 2013The cardinality balanced multitarget multi-Bernoulli (CBMeMBer) filter is a recursive, multitarget tracking mechanism based on the random finite set (RFS) theory using the finite set statistics (FISST) framework. It provides an estimate of the number of targets in a given scenario space, along with the most likely locations of those targets.
Darcy Dunne, Thia Kirubarajan
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Gating technique for the Gaussian mixture multi-Bernoulli filter
2014 American Control Conference, 2014The multi-Bernoulli (MB) filter is a new attractive approach for multi-target filtering in the presence of clutter and detection uncertainty. However, the computational complexity grows as clutter density increases. The clutter measurements may also degrade the filtering accuracy.
Tong-yang Jiang +3 more
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On multiple-model extended target multi-Bernoulli filters
Digital Signal Processing, 2016Abstract In this paper, we propose a multiple-model (MM) version of the extended target multi-Bernoulli (ET-MB) filter for estimating multiple maneuvering extended targets. A Gaussian mixture (GM) implementation of the MM-ET-MB filter for linear Gaussian models and a sequential Monte Carlo (SMC) implementation of the MM-ET-MB filter for nonlinear ...
Tong-yang Jiang +3 more
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An improved Bernoulli particle filter for single target tracking
Multidimensional Systems and Signal Processing, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Possibilistic Bernoulli Filter for Extended Target Tracking
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023Zhijin Chen +2 more
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