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Ontology reasoning scheme for constructing meaningful sports video summarisation
by
Liu, Renren
, Ouyang, Jian-quan
in
Algorithms
/ Applied sciences
/ content management
/ content‐directed ontology reasoning approach
/ data mining
/ digital sports video
/ Engines
/ Exact sciences and technology
/ Image processing
/ inference mechanisms
/ Information, signal and communications theory
/ meaningful sports video summarisation
/ meta data
/ metadata acquisition
/ next generation multimedia applications
/ ontologies (artificial intelligence)
/ pervasive video summary
/ query languages
/ query performance improvement
/ Query processing
/ Reasoning
/ reasoning engine
/ Searching
/ semantic information mining
/ semantic reasoning
/ semantic video summary
/ Semantics
/ Signal processing
/ sport
/ sports video content management
/ sports video database query
/ sports video descriptive language
/ SVDL
/ Tableau algorithm
/ Telecommunications and information theory
/ video retrieval
/ video streaming
2013
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Ontology reasoning scheme for constructing meaningful sports video summarisation
by
Liu, Renren
, Ouyang, Jian-quan
in
Algorithms
/ Applied sciences
/ content management
/ content‐directed ontology reasoning approach
/ data mining
/ digital sports video
/ Engines
/ Exact sciences and technology
/ Image processing
/ inference mechanisms
/ Information, signal and communications theory
/ meaningful sports video summarisation
/ meta data
/ metadata acquisition
/ next generation multimedia applications
/ ontologies (artificial intelligence)
/ pervasive video summary
/ query languages
/ query performance improvement
/ Query processing
/ Reasoning
/ reasoning engine
/ Searching
/ semantic information mining
/ semantic reasoning
/ semantic video summary
/ Semantics
/ Signal processing
/ sport
/ sports video content management
/ sports video database query
/ sports video descriptive language
/ SVDL
/ Tableau algorithm
/ Telecommunications and information theory
/ video retrieval
/ video streaming
2013
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Do you wish to request the book?
Ontology reasoning scheme for constructing meaningful sports video summarisation
by
Liu, Renren
, Ouyang, Jian-quan
in
Algorithms
/ Applied sciences
/ content management
/ content‐directed ontology reasoning approach
/ data mining
/ digital sports video
/ Engines
/ Exact sciences and technology
/ Image processing
/ inference mechanisms
/ Information, signal and communications theory
/ meaningful sports video summarisation
/ meta data
/ metadata acquisition
/ next generation multimedia applications
/ ontologies (artificial intelligence)
/ pervasive video summary
/ query languages
/ query performance improvement
/ Query processing
/ Reasoning
/ reasoning engine
/ Searching
/ semantic information mining
/ semantic reasoning
/ semantic video summary
/ Semantics
/ Signal processing
/ sport
/ sports video content management
/ sports video database query
/ sports video descriptive language
/ SVDL
/ Tableau algorithm
/ Telecommunications and information theory
/ video retrieval
/ video streaming
2013
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Ontology reasoning scheme for constructing meaningful sports video summarisation
Journal Article
Ontology reasoning scheme for constructing meaningful sports video summarisation
2013
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Overview
As digital sports video becomes increasingly pervasive, semantic video summary becomes one of the important components for the next generation of multimedia applications. Ontology is a feasible way to mine the semantic information from the video stream. However, current ontology-based methods did not concentrate on the effectiveness and soundness of semantic reasoning. Here, the authors propose a content-directed ontology reasoning approach to produce meaningful sports video summarisation. The proposed ontology can facilitate the metadata acquisition of video and the improvement of query performance. It also provides a flexible way to query the sports video database, which cannot be achieved by simple keyword search. For annotating, describing and managing the sports video content, we propose a sports video descriptive language (SVDL) based on the proposed ontology. Moreover, the semantically meaningful sports video abstraction is produced by reasoning engine which is based on the extension of the Tableau algorithm. Meanwhile, the soundness and completeness of the reasoning algorithm can be solidly proved. Subjective assessment experimental results reveal the reliability and efficiency of the propose scheme.
Publisher
The Institution of Engineering and Technology,Institution of Engineering and Technology,The Institution of Engineering & Technology
Subject
/ content‐directed ontology reasoning approach
/ Engines
/ Exact sciences and technology
/ Information, signal and communications theory
/ meaningful sports video summarisation
/ next generation multimedia applications
/ ontologies (artificial intelligence)
/ query performance improvement
/ sport
/ sports video content management
/ sports video descriptive language
/ SVDL
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