COST292 experimental framework for TRECVID 2006

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dc.contributor.authorĆalić J.en_US
dc.contributor.authorKrämer P.en_US
dc.contributor.authorNaci, U.en_US
dc.contributor.authorVrochidis, S.en_US
dc.contributor.authorAksoy, S.en_US
dc.contributor.authorZhangk Q.en_US
dc.contributor.authorBenois-Pineau J.en_US
dc.contributor.authorSaracoglu, A.en_US
dc.contributor.authorDoulaverakis, C.en_US
dc.contributor.authorJarina, R.en_US
dc.contributor.authorCampbell, N.en_US
dc.contributor.authorMezaris V.en_US
dc.contributor.authorKompatsiaris I.en_US
dc.contributor.authorSpyrou, E.en_US
dc.contributor.authorKoumoulos G.en_US
dc.contributor.authorAvrithis, Y.en_US
dc.contributor.authorDalkilic, A.en_US
dc.contributor.authorAlatan, A.en_US
dc.contributor.authorHanjalic, A.en_US
dc.contributor.authorIzquierdo, E.en_US
dc.date.accessioned2016-02-08T11:49:13Z
dc.date.available2016-02-08T11:49:13Z
dc.date.issued2006en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionConference name: TRECVID 2006, TREC Video Retrieval Evaluation Notebook
dc.description.abstractIn this paper we give an overview of the four TRECVID tasks submitted by COST292, European network of institutions in the area of semantic multimodal analysis and retrieval of digital video media. Initially, we present shot boundary evaluation method based on results merged using a confidence measure. The two SB detectors user here are presented, one of the Technical University of Delft and one of the LaBRI, University of Bordeaux 1, followed by the description of the merging algorithm. The high-level feature extraction task comprises three separate systems. The first system, developed by the National Technical University of Athens (NTUA) utilises a set of MPEG-7 low-level descriptors and Latent Semantic Analysis to detect the features. The second system, developed by Bilkent University, uses a Bayesian classifier trained with a "bag of subregions" for each keyframe. The third system by the Middle East Technical University (METU) exploits textual information in the video using character recognition methodology. The system submitted to the search task is an interactive retrieval application developed by Queen Mary, University of London, University of Zilina and ITI from Thessaloniki, combining basic retrieval functionalities in various modalities (i.e. visual, audio, textual) with a user interface supporting the submission of queries using any combination of the available retrieval tools and the accumulation of relevant retrieval results over all queries submitted by a single user during a specified time interval. Finally, the rushes task submission comprises a video summarisation and browsing system specifically designed to intuitively and efficiently presents rushes material in video production environment. This system is a result of joint work of University of Bristol, Technical University of Delft and LaBRI, University of Bordeaux 1.en_US
dc.identifier.urihttp://hdl.handle.net/11693/27264
dc.language.isoEnglishen_US
dc.publisherNational Institute of Standards and Technologyen_US
dc.source.title2006 TREC Video Retrieval Evaluation Notebook Papersen_US
dc.subjectCharacter recognitionen_US
dc.subjectFeature extractionen_US
dc.subjectMotion Picture Experts Group standardsen_US
dc.subjectMultimedia systemsen_US
dc.subjectSemanticsen_US
dc.subjectUser interfacesen_US
dc.subjectHigh-level feature extractionsen_US
dc.subjectInteractive retrievalen_US
dc.subjectLatent Semantic Analysisen_US
dc.subjectLow level descriptorsen_US
dc.subjectMiddle East Technical Universityen_US
dc.subjectTechnical universitiesen_US
dc.subjectUniversity of Bristolen_US
dc.subjectUniversity of Londonen_US
dc.subjectImage retrievalen_US
dc.titleCOST292 experimental framework for TRECVID 2006en_US
dc.typeConference Paperen_US

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