CARON, Francois; RISTIC, Branko; DUFLOS, Emmanuel; VANHEEGHE, Philippe

doi:10.1016/j.ijar.2006.10.003

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CARON, Francois
Advanced Learning Evolutionary Algorithms [ALEA]
Institut de Mathématiques de Bordeaux [IMB]

RISTIC, Branko
Defence Science and Technology Organisation [DSTO]

DUFLOS, Emmanuel
Sequential Learning [SEQUEL]
LAGIS-SI

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International Journal of Approximate Reasoning. 2008-06, vol. 48, n° 2, p. 419-436

Elsevier

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We consider here the case where our knowledge is partial and based on a betting density function which is n-dimensional Gaussian. The explicit formulation of the least committed basic belief density (bbd) of the multivariate Gaussian pdf is provided in the transferable belief model (TBM) framework. Beliefs are then assigned to hyperspheres and the bbd follows a khi-2 distribution. Two applications are also presented. The first one deals with model based classification in the joint speed-accel- eration feature space. The second is devoted to joint target tracking and classification: the tracking part is performed using a Rao-Blackwellized particle filter, while the classification is carried out within the developed TBM scheme.< Leer menos

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Belief function theory

Transferable belief model

Evidential theory

Multivariate Gaussian pdf

Target classification

Target tracking

Particle filtering

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Least committed basic belief density induced by a multivariate Gaussian: Formulation with applications

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