Ontology-enriched semantic space for video search

Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel fr...

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Bibliographic Details
Main Authors: WEI, Xiao-Yong, NGO, Chong-wah
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2007
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Online Access:https://ink.library.smu.edu.sg/sis_research/6526
https://ink.library.smu.edu.sg/context/sis_research/article/7529/viewcontent/1291233.1291447.pdf
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Institution: Singapore Management University
Language: English
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Summary:Multimedia-based ontology construction and reasoning have recently been recognized as two important issues in video search, particularly for bridging semantic gap. The lack of coincidence between low-level features and user expectation makes concept-based ontology reasoning an attractive midlevel framework for interpreting high-level semantics. In this paper, we propose a novel model, namely ontology-enriched semantic space (OSS), to provide a computable platform for modeling and reasoning concepts in a linear space. OSS enlightens the possibility of answering conceptual questions such as a high coverage of semantic space with minimal set of concepts, and the set of concepts to be developed for video search. More importantly, the query-to-concept mapping can be more reasonably conducted by guaranteeing the uniform and consistent comparison of concept scores for video search. We explore OSS for several tasks including conceptbased video search, word sense disambiguation and multimodality fusion. Our empirical findings show that OSS is a feasible solution to timely issues such as the measurement of concept combination and query-concept dependent fusion.