Title :
Exact Principal Geodesic Analysis for data on SO(3)
Author :
Said, Salem ; Courty, Nicolas ; Le Bihan, Nicolas ; Sangwine, Stephen J.
Author_Institution :
Dept. Images & Signal, GIPSA-Lab., Grenoble, France
Abstract :
PGA, or Principal Geodesic Analysis, is an extension of the classical PCA (Principal Component Analysis) to the case of data taking values on a Riemannian manifold. In this paper a new and original algorithm, for the exact computation of the PGA of data on the rotation group SO(3), is presented. Some properties of this algorithm are illustrated, with tests on simulated and real data, and its possible applications are finally discussed.
Keywords :
differential geometry; principal component analysis; PCA; PGA; Riemannian manifold; exact principal geodesic analysis; principal component analysis; rotation group SO(3); Convergence; Electronics packaging; Gaussian distribution; Manifolds; Principal component analysis; Quaternions; Signal processing algorithms;
Conference_Titel :
Signal Processing Conference, 2007 15th European
Conference_Location :
Poznan
Print_ISBN :
978-839-2134-04-6
