Hypersphere Fitting From Noisy Data Using an EM Algorithm

This letter studies a new expectation maximization (EM) algorithm to solve the problem of circle, sphere and more generally hypersphere fitting. This algorithm relies on the introduction of random latent vectors having a priori independent von Mises-Fisher distributions defined on the hypersphere. T...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE signal processing letters Vol. 28; pp. 314 - 318
Main Authors:	Lesouple, Julien, Pilastre, Barbara, Altmann, Yoann, Tourneret, Jean-Yves
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.01.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Institute of Electrical and Electronics Engineers
Subjects:	Algorithms Computer Science Distributed databases Engineering Sciences Expectation-Maximization Algorithm Fitting Hypersphere Fitting Hyperspheres Iterative algorithms Maximum likelihood estimation Noise measurement Signal and Image Processing Signal processing algorithms Statistical models Three-dimensional displays von Mises-Fisher distribution Maximum likelihood estimation von Mises-Fisher distribution Expectation-maximization algorithm Hypersphere fitting
ISSN:	1070-9908, 1558-2361
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!