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Keyframe extraction using local visual semantics in the form of a region thesaurus

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dc.contributor.author Spyrou, E en
dc.contributor.author Avrithis, Y en
dc.date.accessioned 2014-03-01T02:44:46Z
dc.date.available 2014-03-01T02:44:46Z
dc.date.issued 2007 en
dc.identifier.uri http://hdl.handle.net/123456789/31947
dc.subject Hierarchical Clustering en
dc.subject Semantic Information en
dc.subject Texture Features en
dc.subject.other Information theory en
dc.subject.other Motion Picture Experts Group standards en
dc.subject.other Thesauri en
dc.subject.other Hierarchical clustering approach en
dc.subject.other International (CO) en
dc.subject.other Key-frame extraction en
dc.subject.other Key-frames en
dc.subject.other Local regions en
dc.subject.other Media adaptation en
dc.subject.other Personalization en
dc.subject.other Semantic features en
dc.subject.other Semantic information en
dc.subject.other Texture features en
dc.subject.other Video shots en
dc.subject.other Visual semantics en
dc.subject.other Semantics en
dc.title Keyframe extraction using local visual semantics in the form of a region thesaurus en
heal.type conferenceItem en
heal.identifier.primary 10.1109/SMAP.2007.4414394 en
heal.identifier.secondary http://dx.doi.org/10.1109/SMAP.2007.4414394 en
heal.identifier.secondary 4414394 en
heal.publicationDate 2007 en
heal.abstract This paper presents an approach for efficient keyframe extraction, using local semantics inform of a region thesaurus. More specifically, certain MPEG-7 color and texture features are locally extracted from keyframe regions. Then, using a hierarchical clustering approach a local region thesaurus is constructed to facilitate the description of each frame in terms of higher semantic features. The thesaurus consists of the most common region types that are encountered within the video shot, along with their synonyms. These region types carry semantic information. Each keyframe is represented by a vector consisting of the degrees of confidence of the existence of all region types within this shot. Using this keyframe representation, the most representative keyframe is then selected for each shot. Where a single keyframe is not adequate, using the same algorithm and exploiting the presence of the region types of the visual thesaurus, more keyframes are extracted. © 2007 IEEE. en
heal.journalName SMAP07 - Second International Workshop on Semantic Media Adaptation and Personalization en
dc.identifier.doi 10.1109/SMAP.2007.4414394 en
dc.identifier.spage 98 en
dc.identifier.epage 103 en


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