We consider the trainable fusion rule design problem when the expert classifiers provide crisp outputs and the behavior space knowledge method is used to fuse local experts’ decisions. If the training set is utilized to design both the experts and the fusion rule, the experts’ outputs become too self-assured. In small sample situations, “optimistically biased” experts’ outputs bluffs the fusion...

Several aspects of fusion rings and fusion rule algebras, and of their manifestations in two-dimensional (conformal) field theory, are described: diagonalization and the connection with modular invariance; the presentation in terms of quotients of polynomial rings; fusion graphs; various strategies that allow for a partial classification; and the role of the fusion rules in the conformal bootst...

This chapter discusses a multimodal biometric sensor fusion approach for controlling building access. A Bayesian framework is implemented fusing the decisions received from multiple biometric sensors and achieving the desired system accuracy. The optimal rule is a function of the error cost and a priori probability of an intruder. The chapter presents and then analyzes a Bayesian framework for ...

Abstract—Optimal distributed fusion assuming that sensor decision rules are given is considered. A general and computationally tractable optimal fusion rule is presented, which relies only on the joint conditional probability densities of all sensor observations and all local decision rules. It is valid for general decision systems with any sensor observations and sensor decision rules, regardl...

This is the second of two articles devoted to an exposition of the generating-function method for computing fusion rules in affine Lie algebras. The present paper focuses on fusion rules, using the machinery developed for tensor products in the companion article. Although the Kac-Walton algorithm provides a method for constructing a fusion generating function from the corresponding tensor-produ...

This presentation may look like a glossary of the fusion rules and we also introduce new ones presenting their formulas and examples: Conjunctive, Disjunctive, Exclusive Disjunctive, Mixed Conjunctive-Disjunctive rules, Conditional rule, Dempster's, Yager's, Smets' TBM rule, Dubois-Prade's, Dezert-Smarandache classical and hybrid rules, Murphy's average rule, Inagaki-Lefevre-Colot-Vannoorenberg...

In this paper, an experimental comparison between fixed and trained fusion rules for multimodal personal identity verification is reported. We focused on the behaviour of the considered fusion methods for ensembles of classifiers exhibiting significantly different performance, as this is one of the main characteristics of multimodal biometrics systems. The experiments were carried out on the XM...

Multiple features fusion based tracking is one of the most active research in tracking literature, In this paper, a novel adaptive fusion strategy is proposed for multiple features fusion, based on two common used fusion rules: product rule and weighted sum rule. This strategy employs particle filtering technique, product rule and weighted sum rule are unified into an adaptive framework through...

This chapter may look like a glossary of the fusion rules and we also introduce new ones presenting their formulas and examples: Conjunctive, Disjunctive, Exclusive Disjunctive, Mixed Conjunctive-Disjunctive rules, Conditional rule, Dempster’s, Yager’s, Smets’ TBM rule, Dubois-Prade’s, DezertSmarandache classical and hybrid rules, Murphy’s average rule, Inagaki-LefevreColot-Vannoorenberghe Unif...

In this chapter, we present two applications in information fusion in order to evaluate the generalized proportional conflict redistribution rule presented in the chapter [5]. Most of the time the combination rules are evaluated only on simple examples. We study here different combination rules and compare them in terms of decision on real data. Indeed, in real applications, we need a reliable ...