86 citations · 192 across the 27 of their papers we have counts for
5 papers · 1 filter
Sequential Markov Chain Monte Carlo for Bayesian Filtering with Massive Data
Allan De Freitas, François Septier, Lyudmila Mihaylova
Advances in digital sensors, digital data storage and communications have resulted in systems being capable of accumulating large collections of data. In the light of dealing with…
Multi-Target Tracking and Occlusion Handling with Learned Variational Bayesian Clusters and a Social Force Model
Ata-ur-Rehman, Syed Mohsen Naqvi, Lyudmila Mihaylova +1
This paper considers the problem of multiple human target tracking in a sequence of video data. A solution is proposed which is able to deal with the challenges of a varying number…
Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments
Christopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova
This paper develops a novel sequential Monte Carlo (SMC) approach for joint state and parameter estimation that can deal efficiently with abruptly changing parameters which is a co…
A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation
Matthew Hawes, Lyudmila Mihaylova, Francois Septier +1
In this paper, we look to address the problem of estimating the dynamic direction of arrival (DOA) of a narrowband signal impinging on a sensor array from the far field. The initia…
How Can Subsampling Reduce Complexity in Sequential MCMC Methods and Deal with Big Data in Target Tracking?
Allan De Freitas, François Septier, Lyudmila Mihaylova +1
Target tracking faces the challenge in coping with large volumes of data which requires efficient methods for real time applications. The complexity considered in this paper is whe…