Density Estimation on the rotation group ...
Document type :
Article dans une revue scientifique: Article original
Title :
Density Estimation on the rotation group using Diffusive wavelets
Author(s) :
Le Bihan, Nicolas [Auteur]
GIPSA - Communication Information and Complex Systems [GIPSA-CICS]
Flamant, Julien [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Manton, Jonathan [Auteur]
Department of Electrical and Electronic Engineering [Melbourne]
GIPSA - Communication Information and Complex Systems [GIPSA-CICS]
Flamant, Julien [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Manton, Jonathan [Auteur]
Department of Electrical and Electronic Engineering [Melbourne]
Journal title :
Journal of Advances in Information Fusion
Pages :
173-185
Publisher :
ISIF
Publication date :
2016
ISSN :
1557-6418
HAL domain(s) :
Informatique [cs]/Traitement du signal et de l'image [eess.SP]
English abstract : [en]
This paper considers the problem of estimating probability den- sity functions on the rotation group SO(3). Two distinct approaches are proposed, one based on characteristic functions and the other on wavelets using the ...
Show more >This paper considers the problem of estimating probability den- sity functions on the rotation group SO(3). Two distinct approaches are proposed, one based on characteristic functions and the other on wavelets using the heat kernel. Expressions are derived for their Mean Integrated Squared Errors. The performance of the estima- tors is studied numerically and compared with the performance of an existing technique using the De La Vall´ee Poussin kernel estimator. The heat kernel wavelet approach appears to offer the best compromise, with faster convergence to the optimal bound and guaranteed positivity of the estimated probability density function.Show less >
Show more >This paper considers the problem of estimating probability den- sity functions on the rotation group SO(3). Two distinct approaches are proposed, one based on characteristic functions and the other on wavelets using the heat kernel. Expressions are derived for their Mean Integrated Squared Errors. The performance of the estima- tors is studied numerically and compared with the performance of an existing technique using the De La Vall´ee Poussin kernel estimator. The heat kernel wavelet approach appears to offer the best compromise, with faster convergence to the optimal bound and guaranteed positivity of the estimated probability density function.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
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