On Decomposing Object Appearance using PCA and Wavelet bases with Applications to Image Segmentation

AbstractGenerative models capable of synthesising complete object images have over the past few years proven their worth when interpreting images. Due to the recent development of computational machinery it has become feasible to model the variation of image intensities and landmark positions over the complete object surface using principal component analysis. This typically involves matrices with a few thousands and up to 100.000+ rows.
This paper demonstrates applications of such models applied on colour images of human faces and cardiac magnetic resonance images. Further, we devise methods for alleviating the obvious computational and storage requirements of these large models by means of truncated wavelet bases.
TypeConference paper [Abstract]
ConferenceMATRIX'02, Eleventh International Workshop on Matrices and Statistics
EditorsHans Joachim Werner
Year2002    Month September    pp. 21
PublisherInformatics and Mathematical Modelling, Technical University of Denmark, DTU
AddressRichard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Image Analysis & Computer Graphics