Proceedings ArticleDOI
Real-Time Tracking Of Hundreds Of Targets With Efficient Exact JPDAF Implementation
Paul R. Horridge,Simon Maskell +1 more
- pp 1-8
TLDR
This work shows the feasibility of using an exact JPDAF implementation to track 400 targets and generalizes this approach to process the objects in a tree structure this exploits conditional independence between subsets of the objects.Abstract:
An assignment problem is considered with the constraint that the same hypothesis cannot be applied to more than one object. We desire efficiency without approximation. Multiple target tracking methods such as the Joint Probabilistic Association Filter (JPDAF) motivate us. Methods of solving this assignment problem involving enumerating all possible joint assignments are infeasible except for small problems. A recent approach circumvents this combinatorial explosion by representing the structure of the target hypotheses in a `net' which exploits redundancy in an ordered list of objects used to describe the problem. Here, we generalize this approach to process the objects in a tree structure; this exploits conditional independence between subsets of the objects. This gives a substantial computational saving and allows us to consider scenarios which were previously impractical. In particular, we show the feasibility of using an exact JPDAF implementation to track 400 targets.read more
Citations
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Journal ArticleDOI
Message Passing Algorithms for Scalable Multitarget Tracking
Florian Meyer,Thomas Kropfreiter,Jason L. Williams,Roslyn A. Lau,Franz Hlawatsch,Paolo Braca,Moe Z. Win +6 more
TL;DR: This tutorial paper advocates a recently proposed paradigm for scalable multitarget tracking that is based on message passing or, more concretely, the loopy sum–product algorithm, which provides a highly effective, efficient, and scalable solution to the probabilistic data association problem, a major challenge in multitargettracking.
Journal ArticleDOI
Marginal multi-bernoulli filters: RFS derivation of MHT, JIPDA, and association-based member
TL;DR: In this paper, the authors derived a form of the full Bayes RFS filter and observed that data association is implicitly present, in a data structure similar to multiple hypothesis tracking (MHT).
Journal ArticleDOI
A Scalable Algorithm for Tracking an Unknown Number of Targets Using Multiple Sensors
TL;DR: An algorithm for tracking an unknown number of targets based on measurements provided by multiple sensors that can outperform multisensor versions of the probability hypothesis density (PHD) filter, the cardinalized PHD filter, and the multi-Bernoulli filter.
Journal ArticleDOI
Approximate evaluation of marginal association probabilities with belief propagation
Jason L. Williams,Roslyn A. Lau +1 more
TL;DR: A graphical model formulation of data association is presented and an approximate inference method, belief propagation (BP), is applied to obtain estimates of marginal association probabilities to prove that BP is guaranteed to converge, and bound the number of iterations necessary.
Journal ArticleDOI
Cooperative robotic networks for underwater surveillance: an overview
Gabriele Ferri,Andrea Munafo,Alessandra Tesei,Paolo Braca,Florian Meyer,Konstantinos Pelekanakis,Roberto Petroccia,Joao Alves,Christopher Strode,Kevin D. LePage +9 more
TL;DR: The main thrust of this study is to review the underwater surveillance scenario within a framework of four research areas: (i) underwater robotics, (ii) acoustic signal processing, (iii) tracking and distributed information fusion, and (iv) underwater communications networks.
References
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Journal ArticleDOI
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