J. Vermaak

发表

Monte Carlo filtering for multi target tracking and data association

S. Godsill, P. Pérez, J. Vermaak, 2005, IEEE Transactions on Aerospace and Electronic Systems.

Non-stationary Bayesian modelling and enhancement of speech signals

Simon J. Godsill, Christophe Andrieu, Arnaud Doucet, 1999 .

Variational inference for visual tracking

Patrick Pérez, Neil D. Lawrence, Jaco Vermaak, 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

Reversible Jump Markov Chain Monte Carlo Strategies for Bayesian Model Selection in Autoregressive Processes

A. Doucet, C. Andrieu, S. Godsill, 2004, Journal of Time Series Analysis.

On-line Bayesian modelling and enhancement of speech signals

Simon J. Godsill, Christophe Andrieu, Arnaud Doucet, 2000 .

Maintaining multimodality through mixture tracking

Patrick Pérez, Arnaud Doucet, Jaco Vermaak, 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

Mphil in Computer Speech and Language Processing Bayesian Enhancement of Speech Signals

J. Vermaak, 2007 .

MODELS AND ALGORITHMS FOR TRACKING USING VARIABLE DIMENSION PARTICLE FILTERS

S. Godsill, J. Vermaak, 2004 .

RADIAL BASIS FUNCTION REGRESSION USING TRANS-DIMENSIONAL SEQUENTIAL

A. Doucet, S. Godsill, J. Vermaak, 2003 .

Variable rate particle filters for tracking applications

J. Vermaak, S. Godsill, S. Godsill, 2005, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005.

Bayesian model selection of autoregressive processes

Simon J. Godsill, Christophe Andrieu, Arnaud Doucet, 2000 .

Markov chain Monte Carlo estimation for the seasonal autoregressive process with application to pitch modelling

Simon J. Godsill, J. Vermaak, M Niranjan, 1998 .

Particle methods for Bayesian modeling and enhancement of speech signals

Simon J. Godsill, Christophe Andrieu, Arnaud Doucet, 2002, IEEE Trans. Speech Audio Process..

Models and Algorithms for Tracking of Maneuvering Objects Using Variable Rate Particle Filters

Simon J. Godsill, William Ng, Jack F. Li, 2007, Proceedings of the IEEE.

Sequential Monte Carlo framework for extended object tracking

Simon J. Godsill, N. Ikoma, J. Vermaak, 2005 .

A unifying framework for multi-target tracking and existence

J. Vermaak, M. Briers, S. Maskell, 2005, 2005 7th International Conference on Information Fusion.

A grid-based proposal for efficient global localisation of mobile robots

Jaco Vermaak, Man Yin Yee, J. Vermaak, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

Data fusion for visual tracking with particles

Patrick Pérez, Andrew Blake, Jaco Vermaak, 2004, Proceedings of the IEEE.

Sequential Bayesian Kernel Regression

Simon J. Godsill, Arnaud Doucet, Jaco Vermaak, 2003, NIPS.

Towards Improved Observation Models for Visual Tracking: Selective Adaptation

Patrick Pérez, Andrew Blake, Michel Gangnet, 2002, ECCV.

A review of recent results in multiple target tracking

J. Vermaak, J. Li, W. Ng, 2005, ISPA 2005. Proceedings of the 4th International Symposium on Image and Signal Processing and Analysis, 2005..

Online multitarget detection and tracking using sequential Monte Carlo methods

J. Vermaak, J. Li, W. Ng, 2005, 2005 7th International Conference on Information Fusion.

Tracking variable number of targets using sequential monte carlo methods

Simon J. Godsill, William Ng, Jack F. Li, 2005, IEEE/SP 13th Workshop on Statistical Signal Processing, 2005.

Multitarget tracking using a new soft-gating approach and sequential Monte Carlo methods

Simon J. Godsill, William Ng, Jack F. Li, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

A hybrid approach for online joint detection and tracking for multiple targets

J. Vermaak, J. Li, W. Ng, 2005, 2005 IEEE Aerospace Conference.

Extended object tracking using particle techniques

N. Ikoma, J. Vermaak, S.J. Godsill, 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

Integrated tracking with vision and sound

Patrick Pérez, Andrew Blake, Michel Gangnet, 2001, Proceedings 11th International Conference on Image Analysis and Processing.

Sequential Monte Carlo fusion of sound and vision for speaker tracking

A. Blake, M. Gangnet, J. Vermaak, 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.

Discordancebetween Measuredand CalculatedTotal Carbon Dioxide

J. Vermaak, M. J. Ungerer, 1990 .

Color-Based Probabilistic Tracking

Patrick Pérez, Michel Gangnet, Jaco Vermaak, 2002, ECCV.

An improved speech production model for voiced speech utilising seasonal AR-AR model and Markov chain Monte Carlo simulation

Simon J. Godsill, J. Vermaak, M Niranjan, 1998 .

MARKOV CHAINMONTE CARLO ESTIMATION FOR THE SEASONAL AUTOREGRESSIVE PROCESS WITH APPLICATION TO PITCHMODELLING

M. Niranjan, J. Vermaak, S. Godsill, 1998 .

Comparing solution methodologies for speech enhancement within a Bayesian framework

Simon J. Godsill, J. Vermaak, M Niranjan, 1998 .

Markov chain Monte Carlo methods for speech enhancement

Mahesan Niranjan, Jaco Vermaak, M. Niranjan, 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

Models and algorithms for tracking using trans-dimensional sequential Monte Carlo

Simon J. Godsill, Jaco Vermaak, S. Godsill, 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

Constrained subspace modeling

Patrick Pérez, Jaco Vermaak, P. Pérez, 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

Sequential Monte Carlo framework for extended object tracking

S. Godsill, J. Vermaak, N. Ikoma, 2005 .

Nonlinear filtering for speaker tracking in noisy and reverberant environments

Andrew Blake, Jaco Vermaak, A. Blake, 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).