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ORCIDBa-Ngu Vo
Publications
- 2025
[i19]Tran Thien Dat Nguyen, Ba-Tuong Vo, Ba-Ngu Vo, Hoa Van Nguyen, Changbeom Shim:
The Mean of Multi-Object Trajectories. CoRR abs/2504.20391 (2025)- 2024
- [j70]Hoa Van Nguyen
, Ba-Ngu Vo, Ba-Tuong Vo, Hamid Rezatofighi, Damith C. Ranasinghe:
Multi-Objective Multi-Agent Planning for Discovering and Tracking Multiple Mobile Objects. IEEE Trans. Signal Process. 72: 3669-3685 (2024) - [j69]Ba-Ngu Vo, Ba-Tuong Vo, Tran Thien Dat Nguyen, Changbeom Shim:
An Overview of Multi-Object Estimation via Labeled Random Finite Set. IEEE Trans. Signal Process. 72: 4888-4917 (2024) - 2023
- [j68]Tran Thien Dat Nguyen, Hamid Rezatofighi, Ba-Ngu Vo, Ba-Tuong Vo, Silvio Savarese, Ian D. Reid:
How Trustworthy are Performance Evaluations for Basic Vision Tasks? IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8538-8552 (2023) - [j67]Changbeom Shim, Ba-Tuong Vo, Ba-Ngu Vo, Jonah Ong, Diluka Moratuwage:
Linear Complexity Gibbs Sampling for Generalized Labeled Multi-Bernoulli Filtering. IEEE Trans. Signal Process. 71: 1981-1994 (2023) - 2022
- [j66]Jonah Ong, Ba-Tuong Vo, Ba-Ngu Vo, Du Yong Kim, Sven Nordholm:
A Bayesian Filter for Multi-View 3D Multi-Object Tracking With Occlusion Handling. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2246-2263 (2022) - [j65]Jonah Ong, Ba-Tuong Vo, Sven Nordholm, Ba-Ngu Vo, Diluka Moratuwage, Changbeom Shim:
Audio-Visual Based Online Multi-Source Separation. IEEE ACM Trans. Audio Speech Lang. Process. 30: 1219-1234 (2022) - [j64]Diluka Moratuwage, Ba-Ngu Vo, Ba-Tuong Vo, Changbeom Shim:
Multi-Scan Multi-Sensor Multi-Object State Estimation. IEEE Trans. Signal Process. 70: 5429-5442 (2022) - [c82]Yuthika Punchihewa, Ba-Tuong Vo, Ba-Ngu Vo, Amanda Bessell, Sanjeev Arulampalam, Jessica Irons, Samuel J. Davey:
Target Motion Analysis via Hard and Soft Data Fusion. ICCAIS 2022: 101-106 - [i17]Hoa Van Nguyen, Ba-Ngu Vo, Ba-Tuong Vo, Hamid Rezatofighi, Damith C. Ranasinghe:
Multi-Objective Multi-Agent Planning for Discovering and Tracking Unknown and Varying Number of Mobile Objects. CoRR abs/2203.04551 (2022) - [i16]Diluka Moratuwage, Ba-Ngu Vo, Ba-Tuong Vo, Changbeom Shim:
Multi-Scan Multi-Sensor Multi-Object State Estimation. CoRR abs/2205.15516 (2022) - 2021
- [j62]Tran Thien Dat Nguyen, Ba-Ngu Vo, Ba-Tuong Vo, Du Yong Kim, Yu Suk Choi:
Tracking Cells and Their Lineages Via Labeled Random Finite Sets. IEEE Trans. Signal Process. 69: 5611-5626 (2021) - 2020
- [j61]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo:
A Solution for Large-Scale Multi-Object Tracking. IEEE Trans. Signal Process. 68: 2754-2769 (2020) - [i15]Jonah Ong, Ba-Tuong Vo, Ba-Ngu Vo, Du Yong Kim, Sven Nordholm:
A Bayesian 3D Multi-view Multi-object Tracking Filter. CoRR abs/2001.04118 (2020) - [i14]Hamid Rezatofighi, Tran Thien Dat Nguyen, Ba-Ngu Vo, Ba-Tuong Vo, Silvio Savarese, Ian D. Reid:
How Trustworthy are the Existing Performance Evaluations for Basic Vision Tasks? CoRR abs/2008.03533 (2020) - 2019
- [j60]Du Yong Kim, Ba-Ngu Vo, Ba-Tuong Vo, Moongu Jeon:
A labeled random finite set online multi-object tracker for video data. Pattern Recognit. 90: 377-389 (2019) - [j59]Ba-Ngu Vo, Ba-Tuong Vo:
A Multi-Scan Labeled Random Finite Set Model for Multi-Object State Estimation. IEEE Trans. Signal Process. 67(19): 4948-4963 (2019) - [j57]Ba-Ngu Vo, Ba-Tuong Vo, Michael Beard:
Multi-Sensor Multi-Object Tracking With the Generalized Labeled Multi-Bernoulli Filter. IEEE Trans. Signal Process. 67(23): 5952-5967 (2019) - 2018
- [j56]Ba-Ngu Vo, Nhan Dam, Dinh Q. Phung, Quang N. Tran, Ba-Tuong Vo:
Model-based learning for point pattern data. Pattern Recognit. 84: 136-151 (2018) - [j55]Claudio Fantacci, Ba-Ngu Vo, Ba-Tuong Vo, Giorgio Battistelli, Luigi Chisci:
Robust Fusion for Multisensor Multiobject Tracking. IEEE Signal Process. Lett. 25(5): 640-644 (2018) - [j54]Yuthika Gardiyawasam Punchihewa, Ba-Tuong Vo, Ba-Ngu Vo, Du Yong Kim:
Multiple Object Tracking in Unknown Backgrounds With Labeled Random Finite Sets. IEEE Trans. Signal Process. 66(11): 3040-3055 (2018) - [j53]Daniel S. Bryant, Ba-Tuong Vo, Ba-Ngu Vo, Brandon A. Jones:
A Generalized Labeled Multi-Bernoulli Filter With Object Spawning. IEEE Trans. Signal Process. 66(23): 6177-6189 (2018) - [c80]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo:
Performance Evaluation for Large-Scale Multi-Target Tracking Algorithms. FUSION 2018: 1-5 - [c79]Ba-Tuong Vo, Ba-Ngu Vo:
Multi-Scan Generalized Labeled Multi-Bernoulli Filter. FUSION 2018: 195-202 - 2017
- [j52]Ba-Ngu Vo, Ba-Tuong Vo, Hung Gia Hoang:
An Efficient Implementation of the Generalized Labeled Multi-Bernoulli Filter. IEEE Trans. Signal Process. 65(8): 1975-1987 (2017) - [j51]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo, Sanjeev Arulampalam:
Void Probabilities and Cauchy-Schwarz Divergence for Generalized Labeled Multi-Bernoulli Models. IEEE Trans. Signal Process. 65(19): 5047-5061 (2017) - [c77]Ba-Ngu Vo, Ba-Tuong Vo:
An implementation of the multi-sensor generalized labeled multi-Bernoulli filter via Gibbs sampling. FUSION 2017: 1-8 - [c75]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo:
OSPA(2): Using the OSPA metric to evaluate multi-target tracking performance. ICCAIS 2017: 86-91 - [c74]Daniel S. Bryant, Ba-Tuong Vo, Ba-Ngu Vo, Brandon A. Jones:
A labeled random finite set spawning model. ICCAIS 2017: 215-220 - [i10]Ba-Ngu Vo, Quang N. Tran, Dinh Q. Phung, Ba-Tuong Vo:
Model-based Classification and Novelty Detection For Point Pattern Data. CoRR abs/1701.08473 (2017) - [i9]Quang N. Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo:
Clustering For Point Pattern Data. CoRR abs/1702.02262 (2017) - [i8]Ba-Ngu Vo, Dinh Q. Phung, Quang N. Tran, Ba-Tuong Vo:
Model-Based Multiple Instance Learning. CoRR abs/1703.02155 (2017) - [i7]Quang N. Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo, Nguyen Cong Thuong:
Multiple Instance Learning with the Optimal Sub-Pattern Assignment Metric. CoRR abs/1703.08933 (2017) - 2016
- [j50]Michael Beard, Stephan Reuter, Karl Granström, Ba-Tuong Vo, Ba-Ngu Vo, Alexander Scheel:
Multiple Extended Target Tracking With Labeled Random Finite Sets. IEEE Trans. Signal Process. 64(7): 1638-1653 (2016) - [c73]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo:
Generalised labelled multi-Bernoulli forward-backward smoothing. FUSION 2016: 688-694 - [c72]Yuthika Punchihewa, Ba-Ngu Vo, Ba-Tuong Vo:
A Generalized Labeled Multi-Bernoulli filter for maneuvering targets. FUSION 2016: 980-986 - [c71]Du Yong Kim, Ba-Ngu Vo, Ba-Tuong Vo:
Multi-object particle filter revisited. ICCAIS 2016: 42-47 - [c70]Ba-Ngu Vo, Nhat-Quang Tran, Dinh Q. Phung, Ba-Tuong Vo:
Model-based classification and novelty detection for point pattern data. ICPR 2016: 2622-2627 - [c69]Nhat-Quang Tran, Ba-Ngu Vo, Dinh Q. Phung, Ba-Tuong Vo:
Clustering for point pattern data. ICPR 2016: 3174-3179 - [i6]Yuthika Punchihewa, Ba-Ngu Vo, Ba-Tuong Vo:
A Generalized Labeled Multi-Bernoulli Filter for Maneuvering Targets. CoRR abs/1603.04565 (2016) - [i5]Du Yong Kim, Ba-Ngu Vo, Ba-Tuong Vo:
Online Visual Multi-Object Tracking via Labeled Random Finite Set Filtering. CoRR abs/1611.06011 (2016) - 2015
- [j49]Hung Gia Hoang, Ba-Ngu Vo, Ba-Tuong Vo, Ronald P. S. Mahler:
The Cauchy-Schwarz Divergence for Poisson Point Processes. IEEE Trans. Inf. Theory 61(8): 4475-4485 (2015) - [j48]Seyed Hamid Rezatofighi, Stephen Gould, Ba-Tuong Vo, Ba-Ngu Vo, Katarina Mele, Richard I. Hartley:
Multi-Target Tracking With Time-Varying Clutter Rate and Detection Profile: Application to Time-Lapse Cell Microscopy Sequences. IEEE Trans. Medical Imaging 34(6): 1336-1348 (2015) - [j47]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo:
Bayesian Multi-Target Tracking With Merged Measurements Using Labelled Random Finite Sets. IEEE Trans. Signal Process. 63(6): 1433-1447 (2015) - [j46]Francesco Papi, Ba-Ngu Vo, Ba-Tuong Vo, Claudio Fantacci, Michael Beard:
Generalized Labeled Multi-Bernoulli Approximation of Multi-Object Densities. IEEE Trans. Signal Process. 63(20): 5487-5497 (2015) - [c68]Stephan Reuter, Alexander Scheel, Michael Beard, Karl Granström, Ba-Tuong Vo, Ba-Ngu Vo, Klaus Dietmayer:
Environment Perception for Companion Systems. ISCT 2015: 68-72 - [c67]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo, Sanjeev Arulampalam:
Sensor control for multi-target tracking using Cauchy-Schwarz divergence. FUSION 2015: 937-944 - [c66]Michael Beard, Stephan Reuter, Karl Granström, Ba-Tuong Vo, Ba-Ngu Vo, Alexander Scheel:
A generalised labelled multi-Bernoulli filter for extended multi-target tracking. FUSION 2015: 991-998 - [c65]Hung Gia Hoang, Ba-Tuong Vo, Ba-Ngu Vo:
A fast implementation of the generalized labeled multi-Bernoulli filter with joint prediction and update. FUSION 2015: 999-1006 - [c64]Brandon A. Jones, Daniel S. Bryant, Ba-Tuong Vo, Ba-Ngu Vo:
Challenges of multi-target tracking for space situational awareness. FUSION 2015: 1278-1285 - [i4]Claudio Fantacci, Ba-Ngu Vo, Ba-Tuong Vo, Giorgio Battistelli, Luigi Chisci:
Consensus Labeled Random Finite Set Filtering for Distributed Multi-Object Tracking. CoRR abs/1501.01579 (2015) - [i3]Hung Gia Hoang, Ba-Tuong Vo, Ba-Ngu Vo:
A Generalized Labeled Multi-Bernoulli Filter Implementation using Gibbs Sampling. CoRR abs/1506.00821 (2015) - [i2]Seyed Hamid Rezatofighi, Stephen Gould, Ba-Tuong Vo, Ba-Ngu Vo, Katarina Mele, Richard I. Hartley:
Multi-Target Tracking with Time-Varying Clutter Rate and Detection Profile: Application to Time-lapse Cell Microscopy Sequences. CoRR abs/1507.06397 (2015) - 2014
- [j42]Stephan Reuter, Ba-Tuong Vo, Ba-Ngu Vo, Klaus Dietmayer:
The Labeled Multi-Bernoulli Filter. IEEE Trans. Signal Process. 62(12): 3246-3260 (2014) - [j40]Ba-Ngu Vo, Ba-Tuong Vo, Dinh Q. Phung:
Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter. IEEE Trans. Signal Process. 62(24): 6554-6567 (2014) - [c61]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo:
Multi-target tracking with merged measurements using labelled random finite sets. FUSION 2014: 1-8 - [c60]Ángel F. García-Fernández, Ba-Ngu Vo, Ba-Tuong Vo:
MCMC-based posterior independence approximation for RFS multitarget particle filters. FUSION 2014: 1-8 - [c58]Stephan Reuter, Ba-Tuong Vo, Ba-Ngu Vo, Klaus Dietmayer:
Multi-object tracking using labeled multi-Bernoulli random finite sets. FUSION 2014: 1-8 - [c57]Ba-Ngu Vo, Ba-Tuong Vo:
A stochastic geometric approach to sensor array processing. SSP 2014: 236-239 - [c56]Hung Gia Hoang, Ba-Ngu Vo, Ba-Tuong Vo, Ronald P. S. Mahler:
The Cauchy-Schwarz divergence for poisson point processes. SSP 2014: 240-243 - 2013
- [j37]Ba-Tuong Vo, Ba-Ngu Vo, Reza Hoseinnezhad, Ronald P. S. Mahler:
Robust Multi-Bernoulli Filtering. IEEE J. Sel. Top. Signal Process. 7(3): 399-409 (2013) - [j36]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo:
Multitarget Filtering With Unknown Clutter Density Using a Bootstrap GMCPHD Filter. IEEE Signal Process. Lett. 20(4): 323-326 (2013) - [j35]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo, Sanjeev Arulampalam:
A Partially Uniform Target Birth Model for Gaussian Mixture PHD/CPHD Filtering. IEEE Trans. Aerosp. Electron. Syst. 49(4): 2835-2844 (2013) - [j34]Reza Hoseinnezhad, Ba-Ngu Vo, Ba-Tuong Vo:
Visual Tracking in Background Subtracted Image Sequences via Multi-Bernoulli Filtering. IEEE Trans. Signal Process. 61(2): 392-397 (2013) - [j33]Branko Ristic, Ba-Tuong Vo, Ba-Ngu Vo, Alfonso Farina:
A Tutorial on Bernoulli Filters: Theory, Implementation and Applications. IEEE Trans. Signal Process. 61(13): 3406-3430 (2013) - [j32]Ba-Tuong Vo, Ba-Ngu Vo:
Labeled Random Finite Sets and Multi-Object Conjugate Priors. IEEE Trans. Signal Process. 61(13): 3460-3475 (2013) - [i1]Hung Gia Hoang, Ba-Ngu Vo, Ba-Tuong Vo, Ronald P. S. Mahler:
The Cauchy-Schwarz divergence for Poisson point processes. CoRR abs/1312.6224 (2013) - 2012
- [j31]Reza Hoseinnezhad, Ba-Ngu Vo, Ba-Tuong Vo, David Suter:
Visual tracking of numerous targets via multi-Bernoulli filtering of image data. Pattern Recognit. 45(10): 3625-3635 (2012) - [j30]Ronald P. S. Mahler, Ba-Tuong Vo, Ba-Ngu Vo:
Forward-Backward Probability Hypothesis Density Smoothing. IEEE Trans. Aerosp. Electron. Syst. 48(1): 707-728 (2012) - [j29]Branko Ristic, Daniel E. Clark, Ba-Ngu Vo, Ba-Tuong Vo:
Adaptive Target Birth Intensity for PHD and CPHD Filters. IEEE Trans. Aerosp. Electron. Syst. 48(2): 1656-1668 (2012) - [j28]Ba-Ngu Vo, Ba-Tuong Vo, Ronald P. S. Mahler:
Closed-Form Solutions to Forward-Backward Smoothing. IEEE Trans. Signal Process. 60(1): 2-17 (2012) - [j27]Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, David Suter:
Reply to "Comments on 'Joint Detection and Estimation of Multiple Objects from Image Observations'". IEEE Trans. Signal Process. 60(3): 1540-1541 (2012) - [c50]Ba-Tuong Vo, Ba-Ngu Vo:
The para-normal Bayes multi-target filter and the spooky effect. FUSION 2012: 173-180 - [c49]Michael Beard, Ba-Tuong Vo, Ba-Ngu Vo, Sanjeev Arulampalam:
Gaussian mixture PHD and CPHD filtering with partially uniform target birth. FUSION 2012: 535-541 - [c48]Shanhung Wong, Ba-Tuong Vo, Ba-Ngu Vo, Reza Hoseinnezhad:
Multi-Bernoulli based track-before-detect with road constraints. FUSION 2012: 840-846 - 2011
- [b1]John Mullane, Ba-Ngu Vo, Martin Adams, Ba-Tuong Vo:
Random Finite Sets for Robot Mapping and SLAM - New Concepts in Autonomous Robotic Map Representations. Springer Tracts in Advanced Robotics 72, Springer 2011, ISBN 978-3-642-21389-2, pp. 1-136 [contents] - [j25]John Mullane, Ba-Ngu Vo, Martin David Adams, Ba-Tuong Vo:
A Random-Finite-Set Approach to Bayesian SLAM. IEEE Trans. Robotics 27(2): 268-282 (2011) - [j24]Branko Ristic, Ba-Ngu Vo, Daniel E. Clark, Ba-Tuong Vo:
A Metric for Performance Evaluation of Multi-Target Tracking Algorithms. IEEE Trans. Signal Process. 59(7): 3452-3457 (2011) - [j23]Ronald P. S. Mahler, Ba-Tuong Vo, Ba-Ngu Vo:
CPHD Filtering With Unknown Clutter Rate and Detection Profile. IEEE Trans. Signal Process. 59(8): 3497-3513 (2011) - [j22]Ba-Tuong Vo, Daniel E. Clark, Ba-Ngu Vo, Branko Ristic:
Bernoulli Forward-Backward Smoothing for Joint Target Detection and Tracking. IEEE Trans. Signal Process. 59(9): 4473-4477 (2011) - [c45]Ba-Tuong Vo, Ba-Ngu Vo, Reza Hoseinnezhad, Ronald P. S. Mahler:
Multi-Bernoulli filtering with unknown clutter intensity and sensor field-of-view. CISS 2011: 1-6 - [c44]Ronald P. S. Mahler, Ba-Tuong Vo, Ba-Ngu Vo:
CPHD filtering with unknown clutter rate and detection profile. FUSION 2011: 1-8 - [c42]Reza Hoseinnezhad, Ba-Ngu Vo, Ba-Tuong Vo, David Suter:
Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter. ICASSP 2011: 2300-2303 - [c40]John Mullane, Ba-Ngu Vo, Martin Adams, Ba-Tuong Vo:
Mobile Robotics in a Random Finite Set Framework. ICSI (2) 2011: 519-528 - 2010
- [j19]Daniel E. Clark, Branko Ristic, Ba-Ngu Vo, Ba-Tuong Vo:
Bayesian multi-object filtering with amplitude feature likelihood for unknown object SNR. IEEE Trans. Signal Process. 58(1): 26-37 (2010) - [j16]Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, David Suter:
Joint detection and estimation of multiple objects from image observations. IEEE Trans. Signal Process. 58(10): 5129-5141 (2010) - [c39]Ronald P. S. Mahler, Ba-Ngu Vo, Ba-Tuong Vo:
The forward-backward Probability Hypothesis Density smoother. FUSION 2010: 1-8 - [c36]Ba-Ngu Vo, Ba-Tuong Vo, Ronald P. S. Mahler:
A closed form solution to the Probability Hypothesis Density Smoother. FUSION 2010: 1-8 - [c35]Reza Hoseinnezhad, Ba-Ngu Vo, David Suter, Ba-Tuong Vo:
Multi-object filtering from image sequence without detection. ICASSP 2010: 1154-1157 - 2009
- [j14]Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni:
The Cardinality Balanced Multi-Target Multi-Bernoulli Filter and Its Implementations. IEEE Trans. Signal Process. 57(2): 409-423 (2009) - [c33]Ba-Ngu Vo, Ba-Tuong Vo, Nam-Trung Pham, David Suter:
Bayesian multi-object estimation from image observations. FUSION 2009: 890-898 - [c32]Daniel E. Clark, Ba-Tuong Vo, Ba-Ngu Vo:
Forward-backward sequential Monte Carlo smoothing for joint target detection and tracking. FUSION 2009: 899-906 - 2008
- [j13]Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni:
Bayesian Filtering With Random Finite Set Observations. IEEE Trans. Signal Process. 56(4): 1313-1326 (2008) - [j12]Dominic Schuhmacher, Ba-Tuong Vo, Ba-Ngu Vo:
A Consistent Metric for Performance Evaluation of Multi-Object Filters. IEEE Trans. Signal Process. 56(8-1): 3447-3457 (2008) - [c30]Dominic Schuhmacher, Ba-Tuong Vo, Ba-Ngu Vo:
On performance evaluation of multi-object filters. FUSION 2008: 1-8 - 2007
- [j9]Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni:
Analytic Implementations of the Cardinalized Probability Hypothesis Density Filter. IEEE Trans. Signal Process. 55(7-2): 3553-3567 (2007) - [c28]Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni:
A Bayesian Approach to Target Tracking with Finite-Set-Valued Observations. ISIC 2007: 458-463 - 2006
- [c24]Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni:
The Cardinalized Probability Hypothesis Density Filter for Linear Gaussian Multi-Target Models. CISS 2006: 681-686 - [c21]Ba-Tuong Vo, Ba-Ngu Vo, Antonio Cantoni:
Performance of PHD Based Multi-Target Filters. FUSION 2006: 1-8
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