Multiresolution Gaussian mixtures for image analysis
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.
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|
|Editor:||McWhirter, JG and Proudler, IK|
|Number of Pages:||11|
|Page Range:||pp. 205-215|
|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|
Actions (login required)