Name
Title | ||
|---|---|---|
Bayesian estimation of multi-object systems with independently identically distributed correlations |
Abstract | ||
|---|---|---|
Recent generalisations of stochastic filtering methods to multi-object systems have become very popular for solving multi-target tracking problems over the last decade. However, there was previously no general means of introducing correlations between objects. In this article, we investigate generalisations of such multi-object filters for systems where there may be dependencies between objects. Determining probability and factorial moment densities is facilitated by the use of a recent result in variational calculus, a general form of Faà di Bruno's formula. The result is illustrated through the Probability Hypothesis Density (PHD) filter, as a first-order moment example of the general form. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/SSP.2014.6884617 | Statistical Signal Processing |
Keywords | Field | DocType |
Bayes methods,filtering theory,stochastic processes,target tracking,Bayesian estimation,Faà di Bruno's formula,PHD filter,factorial moment densities,independently identically distributed correlations,multiobject filters,multiobject systems,multitarget tracking problems,probability hypothesis density,probability moment densities,stochastic filtering methods | Probability hypothesis density filter,Applied mathematics,Factorial moment,Pattern recognition,Point process,Calculus of variations,Filter (signal processing),Artificial intelligence,Independent and identically distributed random variables,Bayes estimator,Mathematics | Conference |
Citations | PageRank | References |
1 | 0.39 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeremie Houssineau | 1 | 34 | 9.57 |
| Daniel E. Clark | 2 | 360 | 36.76 |