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Parameter estimation of two dimensional component Gaussian mixtures
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Katugampala, Nilantha and Wilson, Roland (2003) Parameter estimation of two dimensional component Gaussian mixtures. University of Warwick. Department of Computer Science. (Department of Computer Science research report). (Unpublished)
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PDF (Department of Computer Science Research Report)
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Abstract
Multiresolution Gaussian Mixture Models (MGMM) can be used to represent image and video data in video annotation and retrieval. Preliminary experiments were carried out to estimate the model parameters for two-dimensional data. An iterative algorithm similar to Expectation-Maximisation (EM) is used to estimate the model parameters. The suitability of Akaike's Information Criterion (AIC) as a measure of model fit is also evaluated. AIC was successful for most of the synthetic data sets used in the experiments, however further work is required to develop a more consistent criterion for model fit.
Item Type: | Report | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Library of Congress Subject Headings (LCSH): | Mixture distributions (Probability theory), Digital video, Akaike Information Criterion | ||||
Series Name: | Department of Computer Science research report | ||||
Publisher: | University of Warwick. Department of Computer Science | ||||
Official Date: | 2003 | ||||
Dates: |
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Number: | Number 390 | ||||
Number of Pages: | 61 | ||||
DOI: | CS-RR-390 | ||||
Institution: | University of Warwick | ||||
Theses Department: | Department of Computer Science | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Unpublished | ||||
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