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

Francois Caron 1, 2 Branko Ristic 3 Emmanuel Duflos 4, 5 Philippe Vanheeghe 4, 5
1 ALEA - Advanced Learning Evolutionary Algorithms
Inria Bordeaux - Sud-Ouest, UB - Université de Bordeaux, CNRS - Centre National de la Recherche Scientifique : UMR5251
4 SEQUEL - Sequential Learning
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe, LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
5 LAGIS-SI
LAGIS - Laboratoire d'Automatique, Génie Informatique et Signal
Abstract : 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.
Document type :
Journal articles
Complete list of metadatas

https://hal.archives-ouvertes.fr/hal-00782301
Contributor : Philippe Vanheeghe <>
Submitted on : Tuesday, January 29, 2013 - 2:44:47 PM
Last modification on : Thursday, February 21, 2019 - 10:52:49 AM

Links full text

Identifiers

Citation

Francois Caron, Branko Ristic, Emmanuel Duflos, Philippe Vanheeghe. Least committed basic belief density induced by a multivariate Gaussian: Formulation with applications. International Journal of Approximate Reasoning, Elsevier, 2008, 48 (2), pp.419-436. ⟨10.1016/j.ijar.2006.10.003⟩. ⟨hal-00782301⟩

Share

Metrics

Record views

389