Ontology-Driven Semantic Video Analysis Using Visual Information Objects
Identifieur interne : 001B82 ( Main/Exploration ); précédent : 001B81; suivant : 001B83Ontology-Driven Semantic Video Analysis Using Visual Information Objects
Auteurs : Georgios Th. Papadopoulos [Grèce] ; Vasileios Mezaris [Grèce] ; Ioannis Kompatsiaris [Grèce] ; Michael G. Strintzis [Grèce]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: In this paper, an ontology-driven approach for the semantic analysis of video is proposed. This approach builds on an ontology infrastructure and in particular a multimedia ontology that is based on the notions of Visual Information Object (VIO) and Multimedia Information Object (MMIO). The latter constitute extensions of the Information Object (IO) design pattern, previously proposed for refining and extending the DOLCE core ontology. This multimedia ontology, along with the more domain-specific parts of the developed knowledge infrastructure, supports the analysis of video material, models the content layer of video, and defines generic as well as domain-specific concepts whose detection is important for the analysis and description of video of the specified domain. The signal-level video processing that is necessary for linking the developed ontology infrastructure with the signal domain includes the combined use of a temporal and a spatial segmentation algorithm, a layered structure of Support Vector Machines (SVMs)-based classifiers and a classifier fusion mechanism. A Genetic Algorithm (GA) is introduced for optimizing the performed information fusion step. These processing methods support the decomposition of visual information, as specified by the multimedia ontology, and the detection of the defined domain-specific concepts that each piece of video signal, treated as a VIO, is related to. Experimental results in the domain of disaster news video demonstrate the efficiency of the proposed approach.
Url:
DOI: 10.1007/978-3-540-77051-0_5
Affiliations:
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Strintzis</name><affiliation wicri:level="1"><country xml:lang="fr">Grèce</country><wicri:regionArea>Information Processing Laboratory, Electrical and Computer Engineering Department, Aristotle University of Thessaloniki</wicri:regionArea><wicri:noRegion>Aristotle University of Thessaloniki</wicri:noRegion></affiliation><affiliation wicri:level="1"><country xml:lang="fr">Grèce</country><wicri:regionArea>Informatics and Telematics Institute/CERTH, 1st Km Thermi-Panorama Road, Thessaloniki, GR-57001</wicri:regionArea><wicri:noRegion>GR-57001</wicri:noRegion></affiliation><affiliation wicri:level="1"><country wicri:rule="url">Grèce</country></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2007</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">F4F14898C65A2AEC850EE311F4013783179A0B1C</idno><idno type="DOI">10.1007/978-3-540-77051-0_5</idno><idno type="ChapterID">5</idno><idno type="ChapterID">Chap5</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: In this paper, an ontology-driven approach for the semantic analysis of video is proposed. This approach builds on an ontology infrastructure and in particular a multimedia ontology that is based on the notions of Visual Information Object (VIO) and Multimedia Information Object (MMIO). The latter constitute extensions of the Information Object (IO) design pattern, previously proposed for refining and extending the DOLCE core ontology. This multimedia ontology, along with the more domain-specific parts of the developed knowledge infrastructure, supports the analysis of video material, models the content layer of video, and defines generic as well as domain-specific concepts whose detection is important for the analysis and description of video of the specified domain. The signal-level video processing that is necessary for linking the developed ontology infrastructure with the signal domain includes the combined use of a temporal and a spatial segmentation algorithm, a layered structure of Support Vector Machines (SVMs)-based classifiers and a classifier fusion mechanism. A Genetic Algorithm (GA) is introduced for optimizing the performed information fusion step. These processing methods support the decomposition of visual information, as specified by the multimedia ontology, and the detection of the defined domain-specific concepts that each piece of video signal, treated as a VIO, is related to. Experimental results in the domain of disaster news video demonstrate the efficiency of the proposed approach.</div></front></TEI><affiliations><list><country><li>Grèce</li></country></list><tree><country name="Grèce"><noRegion><name sortKey="Papadopoulos, Georgios Th" sort="Papadopoulos, Georgios Th" uniqKey="Papadopoulos G" first="Georgios Th." last="Papadopoulos">Georgios Th. Papadopoulos</name></noRegion><name sortKey="Kompatsiaris, Ioannis" sort="Kompatsiaris, Ioannis" uniqKey="Kompatsiaris I" first="Ioannis" last="Kompatsiaris">Ioannis Kompatsiaris</name><name sortKey="Kompatsiaris, Ioannis" sort="Kompatsiaris, Ioannis" uniqKey="Kompatsiaris I" first="Ioannis" last="Kompatsiaris">Ioannis Kompatsiaris</name><name sortKey="Mezaris, Vasileios" sort="Mezaris, Vasileios" uniqKey="Mezaris V" first="Vasileios" last="Mezaris">Vasileios Mezaris</name><name sortKey="Mezaris, Vasileios" sort="Mezaris, Vasileios" uniqKey="Mezaris V" first="Vasileios" last="Mezaris">Vasileios Mezaris</name><name sortKey="Papadopoulos, Georgios Th" sort="Papadopoulos, Georgios Th" uniqKey="Papadopoulos G" first="Georgios Th." last="Papadopoulos">Georgios Th. Papadopoulos</name><name sortKey="Papadopoulos, Georgios Th" sort="Papadopoulos, Georgios Th" uniqKey="Papadopoulos G" first="Georgios Th." last="Papadopoulos">Georgios Th. Papadopoulos</name><name sortKey="Strintzis, Michael G" sort="Strintzis, Michael G" uniqKey="Strintzis M" first="Michael G." last="Strintzis">Michael G. Strintzis</name><name sortKey="Strintzis, Michael G" sort="Strintzis, Michael G" uniqKey="Strintzis M" first="Michael G." last="Strintzis">Michael G. Strintzis</name><name sortKey="Strintzis, Michael G" sort="Strintzis, Michael G" uniqKey="Strintzis M" first="Michael G." last="Strintzis">Michael G. Strintzis</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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