Subimage Selection from Multiple Image on Eigenspace for Clustering

An Eigenspace Approach to Multiple Image Registration

Multiple images can be indexed by their projections on a few \eigenfeatures". These eigenfeatures are the eigenvectors of a large covariance matrix, constructed from the images. It is known that registration is essential for computing \useful" eigenfeatures, and a preliminary step of putting the images in register is common practice. We propose to evaluate multiple image registration by the qua...

Subimage Registration Based on Candidate Selection and Multiple Correspondences Master Degree Final Project

Robust Speaker Clustering in Eigenspace

In this paper we propose a speaker clustering scheme working in ’Eigenspace’. Speaker models are transformed to a low-dimensional subspace using ’Eigenvoices’. For the speaker clustering procedure simple distance measures, e.g. Euklidean distance can be applied. Moreover, clustering can be accomplished with base models (for Eigenvoice projection) like Gaussian Mixture Models as well as conventi...

An Eigenspace Update Algorithm for Image Analysis

During the past few years several interesting applications of eigenspace representation of images have been proposed. These include face recognition, video coding, and pose estimation. However, the vision research community has largely overlooked parallel developments in signal processing and numerical linear algebra concerning efficient eigenspace updating algorithms. These new developments ar...

Subimage Sensitive Eigenvalue Spectra for Image Comparison Can One Hear what’s Painted on A Drum?

This publication is a contribution to basic research in image comparison using eigenvalue spectra as features. The differential-geometric approach of eigenvalue spectrum based descriptors is naturally applicable to shape data, but so far little work has been done to transfer it to the setting of image data painted on a rectangle or general curved surface. We present a new semi-global feature de...