DC FieldValueLanguage
dc.contributor.authorNtalianis, Klimis-
dc.contributor.authorDoulamis, Anastasios-
dc.contributor.authorKollias, Stefanos-
dc.contributor.authorAvrithis, Yannis-
dc.contributor.authorDoulamis, Nikolaos-
dc.date.accessioned2024-07-31T12:50:01Z-
dc.date.available2024-07-31T12:50:01Z-
dc.date.issued2000-12-03-
dc.identifierscopus-0033719973-
dc.identifier.issn1051-8215-
dc.identifier.other0033719973-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2771-
dc.description.abstractAn efficient technique for summarization of stereoscopic video sequences is presented in this paper, which extracts a small but meaningful set of video frames using a content-based sampling algorithm. The proposed video-content representation provides the capability of browsing digital stereoscopic video sequences and performing more efficient content-based queries and indexing. Each stereoscopic video sequence is first partitioned into shots by applying a shot-cut detection algorithm so that frames (or stereo pairs) of similar visual characteristics are gathered together. Each shot is then analyzed using stereo-imaging techniques, and the disparity field, occluded areas, and depth map are estimated. A multiresolution implementation of the Recursive Shortest Spanning Tree (RSST) algorithm is applied for color and depth segmentation, while fusion of color and depth segments is employed for reliable video object extraction. In particular, color segments are projected onto depth segments so that video objects on the same depth plane are retained, while at the same time accurate object boundaries are extracted. Feature vectors are then constructed using multidimensional fuzzy classification of segment features including size, location, color, and depth. Shot selection is accomplished by clustering similar shots based on the generalized Lloyd-Max algorithm, while for a given shot, key frames are extracted using an optimization method for locating frames of minimally correlated feature vectors. For efficient implementation of the latter method, a genetic algorithm is used. Experimental results are presented, which indicate the reliable performance of the proposed scheme on real-life stereoscopic video sequences.en_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Circuits and Systems for Video Technologyen_US
dc.titleEfficient summarization of stereoscopic video sequencesen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/76.844996en_US
dc.identifier.scopus2-s2.0-0033719973-
dcterms.accessRights0en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume10en_US
dc.relation.issue4en_US
dc.identifier.spage501en_US
dc.identifier.epage517en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.journalsSubscriptionen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
crisitem.author.deptDepartment of Business Administration-
crisitem.author.facultySchool of Administrative, Economics and Social Sciences-
crisitem.author.parentorgSchool of Administrative, Economics and Social Sciences-
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