Artificial Intelligence
Estimation with Applications to Tracking and Navigation
Estimation with Applications to Tracking and Navigation
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Belief functions on real numbers
International Journal of Approximate Reasoning
Particle filters for state estimation of jump Markov linear systems
IEEE Transactions on Signal Processing
Target identification based on the transferable belief model interpretation of dempster-shafer model
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
International Journal of Approximate Reasoning
Multi-camera people tracking using evidential filters
International Journal of Approximate Reasoning
Combination of partially non-distinct beliefs: The cautious-adaptive rule
International Journal of Approximate Reasoning
Shape from silhouette using Dempster-Shafer theory
Pattern Recognition
Consonant continuous belief functions conflicts calculation
IPMU'10 Proceedings of the Computational intelligence for knowledge-based systems design, and 13th international conference on Information processing and management of uncertainty
Continuous belief functions to qualify sensors performances
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
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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 @g^2 distribution. Two applications are also presented. The first one deals with model based classification in the joint speed-acceleration 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.