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Multiresolution Gaussian mixture models : theory and applications
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Wilson, Roland (2000) Multiresolution Gaussian mixture models : theory and applications. University of Warwick. Department of Computer Science. (Department of Computer Science research report). (Unpublished)
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Abstract
This paper introduces a new generalisation of scale-space and multiresolution pyramids, which combines statistical modelling with a spatial representation. The representation uses the familiar concept of multiple resolutions, but applied to a Gaussian mixture representation of the image; hence the title Multiresolution Gaussian Mixture Model (MGMM). It is shown that MGMM can approximate any probability density and can deal with the smooth motions that typically occur in image analysis and vision. An efficient recursive algorithm for computing MGMM representations, based on Monte Carlo Markov Chain methods, is presented. After a brief presentation of the theory, examples are used to show how MGMM can be applied to vision problems such as segmentation, stereopsis and motion analysis.
| Item Type: | Report | ||||
|---|---|---|---|---|---|
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) | ||||
| Divisions: | Faculty of Science > Computer Science | ||||
| Library of Congress Subject Headings (LCSH): | Image processing -- Digital techniques, Gaussian processes | ||||
| Series Name: | Department of Computer Science research report | ||||
| Publisher: | University of Warwick. Department of Computer Science | ||||
| Official Date: | 28 February 2000 | ||||
| Dates: |
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| Number: | Number 371 | ||||
| Number of Pages: | 27 | ||||
| DOI: | CS-RR-371 | ||||
| Institution: | University of Warwick | ||||
| Theses Department: | Department of Computer Science | ||||
| Status: | Not Peer Reviewed | ||||
| Publication Status: | Unpublished | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Funder: | Engineering and Physical Sciences Research Council (EPSRC) | ||||
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