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An investigation into weighted data fusion for content-based multimedia information retrieval |
Wilkins, Peter
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Content Based Multimedia Information Retrieval (CBMIR) is characterised by the combination of noisy sources of information which, in unison, are able to achieve strong performance. In this thesis we focus on the combination of ranked results from the independent retrieval experts which comprise a CBMIR system through linearly weighted data fusion. The independent retrieval experts are low-level multimedia features, each of which contains an indexing function and ranking algorithm. This thesis is comprised of two halves. In the first half, we perform a rigorous empirical investigation into the factors which impact upon performance in linearly weighted data fusion. In the second half, we leverage these finding to create a new class of weight generation algorithms for data fusion which are
capable of determining weights at query-time, such that the weights are topic dependent.
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Keyword(s):
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Information storage and retrieval systems; Digital video; Image processing; Information retrieval; data fusion |
Publication Date:
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2009 |
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Type:
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Other |
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Peer-Reviewed:
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Unknown |
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Language(s):
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English |
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Contributor(s):
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Smeaton, Alan F. |
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Institution:
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Dublin City University |
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Citation(s):
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Wilkins, Peter (2009) An investigation into weighted data fusion for content-based multimedia information retrieval. PhD thesis, Dublin City University. |
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Publisher(s):
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Dublin City University. School of Computing; Dublin City University. CLARITY: The Centre for Sensor Web Technologies |
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File Format(s):
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application/pdf |
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Related Link(s):
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http://doras.dcu.ie/14877/1/wilkins_thesis.pdf |
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First Indexed:
2009-11-17 02:04:38 Last Updated:
2019-02-09 06:57:49 |
