1 / 9

Aims : (Semi-)automatic MM metadata specification process Information extraction techniques

MUSCLE WP9 E-Team Integration of structural and semantic models for multimedia metadata management. Aims : (Semi-)automatic MM metadata specification process Information extraction techniques Intelligent approaches Semantic Web and multimedia content analysis Multimedia data indexing

akando
Download Presentation

Aims : (Semi-)automatic MM metadata specification process Information extraction techniques

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. MUSCLE WP9 E-TeamIntegration of structural and semantic models for multimedia metadata management • Aims: • (Semi-)automatic MM metadata specification process • Information extraction techniques • Intelligent approaches • Semantic Web and multimedia content analysis • Multimedia data indexing • Participants: BILKENT, CEA, CNR, IBAI

  2. E-Team“Integration of structural and semantic models for multimedia metadata management” Partners Contributions BILKENTvideo database system CEA LISTText analysis and XML metadata extraction and collection CNR-ISTIdesign and development of an Infrastructure for MultiMedia Metadata Management (4M) for MUSCLE integration IBAIdata preparation of web log files

  3. E-Team“Integration of structural and semantic models for multimedia metadata management” Study, design and implementation of an Infrastructure for MultiMedia MetaData Management - 4M -

  4. RDF Multimedia Metadata Background • Multimedia data coming from different fields • Metadata production, storing, retrieve, elaboration Key tools: • MPEG-7 provides detailed and multimedia specific metadata descriptors. • Semantic Web technologies (RDF, OWL, etc), promoted by the W3C, enable large scale interoperability of structured knowledge repositories.

  5. M <?xml version=“1.0” ?> <mpeg-7> . . . </mpeg-7> XML DB MPEG-7feature processing X O Algorithms Ontology I Integration A Annotations network 4M Infrastructure

  6. M <?xml version=“1.0” ?> <mpeg-7> . . . </mpeg-7> XML DB MPEG-7feature processing X O Algorithms Ontology I Integration A Annotations network 4M Infrastructure • BILKENT • XML metadata • (video annotation; salient • object extraction • from video key frames; • spatio-temporal, • semantic and low-level features on video data) • Direct linksto local resources (e.g., BilVideo)

  7. M <?xml version=“1.0” ?> <mpeg-7> . . . </mpeg-7> XML DB MPEG-7feature processing X O Algorithms Ontology I Integration A Annotations network 4M Infrastructure • CEA • XML metadata • (text analysis) • Web-Searching • (XML DB)

  8. M <?xml version=“1.0” ?> <mpeg-7> . . . </mpeg-7> XML DB MPEG-7feature processing X O Algorithms Ontology I Integration A Annotations network 4M Infrastructure • CNR • System software • Database development • Features extraction from audio/images • Ontology for image analysis

  9. M <?xml version=“1.0” ?> <mpeg-7> . . . </mpeg-7> XML DB MPEG-7feature processing X O Algorithms Ontology I Integration A Annotations network 4M Infrastructure • IBAI • XML metadata • (semantic transformation • of Log Files, • features discretization) • Web Serverinteraction

More Related