Name
Abstract | ||
|---|---|---|
An analytic solution to the multi-target Bayes recursion known as the δ-Generalized Labeled Multi-Bernoulli ( δ-GLMB) filter has been recently proposed by Vo and Vo in [“Labeled Random Finite Sets and Multi-Object Conjugate Priors,” IEEE Trans. Signal Process., vol. 61, no. 13, pp. 3460-3475, 2014]. As a sequel to that paper, the present paper details efficient implementations of the δ-GLMB multi-target tracking filter. Each iteration of this filter involves an update operation and a prediction operation, both of which result in weighted sums of multi-target exponentials with intractably large number of terms. To truncate these sums, the ranked assignment and K-th shortest path algorithms are used in the update and prediction, respectively, to determine the most significant terms without exhaustively computing all of the terms. In addition, using tools derived from the same framework, such as probability hypothesis density filtering, we present inexpensive (relative to the δ-GLMB filter) look-ahead strategies to reduce the number of computations. Characterization of the L1-error in the multi-target density arising from the truncation is presented. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TSP.2014.2364014 | IEEE Transactions on Signal Processing |
Keywords | Field | DocType |
labeled random finite set,multitarget exponential weighted sum,multitarget density,conjugate prior,δ-generalized labeled multibernoulli filter,tracking filters,look-ahead strategy,kth shortest path algorithm,bayes methods,target tracking,bayesian estimation,random finite set,set theory,bayes multitarget tracking filter,multitarget bayes recursion,l1-error characterisation,marked point process,prediction operation,filter iteration,ranked assignment,δ-glmb filter,iterative methods,trajectory,indexes,prediction algorithms,estimation | Truncation,Mathematical optimization,Finite set,Exponential function,Shortest path problem,Filter (signal processing),Bayes estimator,Conjugate prior,Mathematics,Bayes' theorem | Journal |
Volume | Issue | ISSN |
62 | 24 | 1053-587X |
Citations | PageRank | References |
52 | 1.58 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ba-Ngu Vo | 1 | 457 | 22.45 |
| Ba-Tuong Vo | 2 | 515 | 28.30 |
| Dinh Q. Phung | 3 | 1469 | 144.58 |