UNSPECIFIED (2002) Multiresolution Gaussian mixtures for image analysis. In: 5th Conference on Mathematics in Signal Processing, DEC 18-20, 2000, UNIV WARWICK, COVENTRY, ENGLAND.

Full text not available from this repository.

Abstract

This paper introduces a generalization of scale-space and pyramids, which combines statistical modelling with a spatial representation. The representation uses the familiar concept of multiple resolutions, but applied to a Gaussian mixture density representation of the image. It is shown that MGMM can approximate any probability density and can accommodate the effects of smooth motions. After a brief presentation of the theory, examples are used to show how MGMM can be applied to problems such as segmentation.

Item Type:	Conference Item (UNSPECIFIED)
Subjects:	Q Science > QA Mathematics
Series Name:	INSTITUTE OF MATHEMATICS AND ITS APPLICATIONS CONFERENCE SERIES : NEW SERIES
Journal or Publication Title:	MATHEMATICS IN SIGNAL PROCESSING V
Publisher:	CLARENDON PRESS
ISBN:	0-19-850734-8
Editor:	McWhirter, JG and Proudler, IK
Date:	2002
Number:	71
Number of Pages:	11
Page Range:	pp. 205-215
Publication Status:	Published
Title of Event:	5th Conference on Mathematics in Signal Processing
Location of Event:	UNIV WARWICK, COVENTRY, ENGLAND
Date(s) of Event:	DEC 18-20, 2000
URI:	http://wrap.warwick.ac.uk/id/eprint/9013

Data sourced from Thomson Reuters' Web of Knowledge

Request changes to a record

Actions (login required)

View Item