Gaussian mixture PHD and CPHD filtering with partially uniform target birth

QR Code

Gaussian mixture PHD and CPHD filtering with partially uniform target birth

The standard Gaussian Mixture Probability Hypothesis Density (GMPHD) filter and Cardinalised Probability Hypothesis Density (GMCPHD) filter require the target birth model to take the form of a Gaussian mixture. Although any density (including a uniform density), can be approximated using a sum of Ga...

Full description

Bibliographic Details
Main Authors:	Beard, Michael, Vo, Ba Tuong, Vo, Ba-Ngu, Arulampalam, S.
Other Authors:	Gee Wah NG
Format:	Conference Paper
Published:	IEEE 2012
Online Access:	http://hdl.handle.net/20.500.11937/16543

Similar Items

A Partially Uniform Target Birth Model for Gaussian Mixture PHD/CPHD Filtering
by: Beard, Michael, et al.
Published: (2013)

Adaptive Target Birth Intensity for PHD and CPHD Filters
by: Ristic, B., et al.
Published: (2012)

Square root Gaussian mixture PHD filter for multi-target bearings only tracking
by: Wong, S., et al.
Published: (2011)

CPHD filtering with unknown clutter rate and detection profile
by: Mahler, R., et al.
Published: (2011)

CPHD Filtering With Unknown Clutter Rate and Detection Profile
by: Mahler, R., et al.
Published: (2011)

Derivation of the PHD and CPHD Filters Based on Direct Kullback-Leibler Divergence Minimization
by: Garcia-Fernandez, Angel, et al.
Published: (2015)

A Gaussian Mixture PHD Filter for Jump Markov System Models
by: Pasha, S., et al.
Published: (2009)

An improved CPHD filter for unknown clutter backgrounds
by: Mahler, R., et al.
Published: (2014)

Sensor control for multi-target tracking using Cauchy-Schwarz divergence
by: Beard, M., et al.
Published: (2015)

Multitarget Filtering With Unknown Clutter Density Using a Bootstrap GMCPHD Filter
by: Beard, Michael, et al.
Published: (2013)

The para-normal Bayes multi-target filter and the spooky effect
by: Vo, Ba Tuong, et al.
Published: (2012)

Performance Evaluation for Large-Scale Multi-Target Tracking Algorithms
by: Beard, Michael, et al.
Published: (2018)

OSPA(2): Using the OSPA metric to evaluate multi-target tracking performance
by: Beard, Michael, et al.
Published: (2017)

Multi-target tracking with merged measurements using labelled random finite sets
by: Beard, Michael, et al.
Published: (2014)

Multi-Sensor Multi-Object Tracking with the Generalized Labeled Multi-Bernoulli Filter
by: Vo, Ba-Ngu, et al.
Published: (2019)

Void Probabilities and Cauchy-Schwarz Divergence for Generalized Labeled Multi-Bernoulli Models
by: Beard, Michael, et al.
Published: (2017)

Data Association and Track Management for the Gaussian Mixture Probability Hypothesis Density Filter
by: Panta, K., et al.
Published: (2009)

A Generalized Labeled Multi-Bernoulli filter for maneuvering targets
by: Punchihewa, Y., et al.
Published: (2016)

CPHD filters for unknown clutter and target-birth processes
by: Mahler, Ronald
Published: (2014)

The Cardinality Balanced Multi-Target Multi-Bernoulli Filter and Its Implementations
by: Vo, Ba Tuong, et al.
Published: (2009)

Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter
by: Vo, Ba-Ngu, et al.
Published: (2014)

Bayesian multi-target tracking with merged measurements using labelled random finite sets
by: Beard, M., et al.
Published: (2015)

A generalised labelled multi-Bernoulli filter for extended multi-target tracking
by: Beard, M., et al.
Published: (2015)

Visual Tracking of Numerous Targets via Multi-Bernoulli Filtering of Image Data
by: Hoseinnezhad, R., et al.
Published: (2012)

Multi-Scan Generalized Labeled Multi-Bernoulli Filter
by: Vo, Ba Tuong, et al.
Published: (2018)

A random finite set conjugate prior and application to multi-target tracking
by: Vo, Ba Tuong, et al.
Published: (2011)

Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter
by: Hoseinnezhad, R., et al.
Published: (2011)

An implementation of the multi-sensor generalized labeled multi-Bernoulli filter via Gibbs sampling
by: Vo, Ba-Ngu, et al.
Published: (2017)

A Solution for Large-Scale Multi-Object Tracking
by: Beard, Michael, et al.
Published: (2020)

Derivation of the PHD filter based on direct Kullback-Leibler divergence minimisation
by: García-Fernández, Ángel, et al.
Published: (2015)

Measurement driven birth model for the generalized labeled multi-Bernoulli filter
by: Lin, S., et al.
Published: (2017)

Bayesian Filtering With Random Finite Set Observations
by: Vo, Ba Tuong, et al.
Published: (2008)

A Note on the Reward Function for PHD Filters with Sensor Control
by: Ristic, B., et al.
Published: (2011)

The Labeled Multi-Bernoulli Filter
by: Reuter, S., et al.
Published: (2014)

A Consistent Metric for Performance Evaluation of Multi-Object Filters
by: Schuhmacher, D., et al.
Published: (2008)

Multiple Extended Target Tracking With Labeled Random Finite Sets
by: Beard, M., et al.
Published: (2016)

Sensor management for multi-target tracking via multi-bernoulli filtering
by: Hoang, Hung, et al.
Published: (2014)

Multi-object particle filter revisited
by: Kim, Du Yong, et al.
Published: (2017)

Generalised labelled multi-Bernoulli forward-backward smoothing
by: Beard, M., et al.
Published: (2016)

Visual Tracking in Background Subtracted Image Sequences via Multi-Bernoulli Filtering
by: Hoseinnezhad, R., et al.
Published: (2013)

Cannot write session to /tmp/vufind_sessions/sess_qgdr17a49kfjrvgb06s2ehmm4f