364 citations · 1.3k across the 18 of their papers we have counts for
4 papers · 1 filter
An efficient, variational approximation of the best fitting multi-Bernoulli filter
Jason L. Williams
The joint probabilistic data association (JPDA) filter is a popular tracking methodology for problems involving well-spaced targets, but it is rarely applied in problems with close…
Hybrid Poisson and multi-Bernoulli filters
Jason L. Williams
The probability hypothesis density (PHD) and multi-target multi-Bernoulli (MeMBer) filters are two leading algorithms that have emerged from random finite sets (RFS). In this paper…
Marginal multi-Bernoulli filters: RFS derivation of MHT, JIPDA and association-based MeMBer
Jason L. Williams
Recent developments in random finite sets (RFSs) have yielded a variety of tracking methods that avoid data association. This paper derives a form of the full Bayes RFS filter and…
Graphical model approximations of random finite set filters
Jason L. Williams
Random finite sets (RFSs) has been a fruitful area of research in recent years, yielding new approximate filters such as the probability hypothesis density (PHD), cardinalised PHD…