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The multiple hypothesis tracker (MHT) is a popular algorithm for solving multi-target tracking (MTT) problem in cluttered environment. It is known as a maximum a posterior (MAP) estimator which enumerates all possible global hypotheses and dedicates to find the most likely solution based on the received reports. However, its practical application is often limited by the complexity of data association...
Robust belief revision methods are crucial in streaming data situations for updating existing knowledge (or beliefs) with new incoming evidence. Bayes conditioning is the primary mechanism in use for belief revision in data fusion systems that use probabilistic inference. However, traditional conditioning methods face several challenges due to inherent data/source imperfections in big-data environments...
The question addressed in this paper is “what” is to be evaluated by the Uncertainty Representation and Reasoning Evaluation Framework (URREF) ontology. We thus identify the elements composing uncertainty representation and reasoning approaches, which constitute various subjects being assessed. We distinguish between primary evaluation subjects (Uncertainty Representation and Reasoning components...
Belief fusion consists of taking into account multiple sources of belief about a domain of interest. This paper describes cumulative and averaging multi-source belief fusion in the formalism of subjective logic, which represent generalisations of binary-source belief fusion operators previously described. The advantage of this approach is that we can model and analyse belief fusion situations involving...
In the framework of belief functions, basic belief assignments building is an important step that should be made carefully since it can greatly influence the performances of a system. In the context of tree species recognition through a leaf and a bark, we analyze the impact of Bayesian as well as consonant basic belief assignments in the case of fusion of uncertain and not equally reliable sources...
The single-object Bayesian filter for an interval, or batch, of data is extended to the multiple object case using the method of analytic combinatorics. The exact expression for the probability generating functional of the Bayes posterior process is derived. It is a nested composition of functions and functionals that is evaluated via a backward recursion. Branching and immigration processes are used...
Uncertainty measures in evidence theory can supply a new criterion to rate the quality of information carried by belie structures. It can also be used to measure the quantity of knowledge conveyed by belief structures. Following the work of Klir and Yuan, several uncertainty measures for belief structures have been developed. Among them, aggregate uncertainty AU, the total uncertainty TU and the ambiguity...
Different belief sources often provide conflicting evidence, due to e.g. varying source reliability or deliberate deception. Source trust expresses the source reliability as seen by the analyst. In case of conflicting sources the analyst needs a strategy for managing and revising source trust. Intuitively, trust should be reduced for sources that produce advice which is in conflict with the ground...
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