DC FieldValueLanguage
dc.contributor.authorNtalianis, Klimis-
dc.contributor.authorDoulamis, Nikolaos-
dc.contributor.authorDoulamis, Anastasios-
dc.contributor.authorKollias, Stefanos-
dc.date.accessioned2024-07-19T07:44:53Z-
dc.date.available2024-07-19T07:44:53Z-
dc.date.issued2001-08-
dc.identifiergoogle_scholar-vd7COBsAAAAJ:yFnVuubrUp4C-
dc.identifier.isbn3-540-42486-5-
dc.identifier.issn0302-9743-
dc.identifier.othervd7COBsAAAAJ:yFnVuubrUp4C-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2748-
dc.description.abstractIn this paper, an adaptive neural network architecture is proposed for efficient video object segmentation and tracking of stereoscopic video sequences. Object extraction is a very important issue, addressed by the emerging multimedia applications, since it provides a meaningful description of the visual content. The scheme includes:(A) A retraining algorithm that optimally adapts the network weights to the current conditions and simultaneously minimally degrades the previous knowledge.(B) A semantically meaningful object extraction module for constructing the retraining set of the current conditions and (C) a decision mechanism, which detects the time instances when network retraining is required. The algorithm results in the minimization of a convex function subject to linear constraints. Furthermore description of the current conditions is achieved by appropriate combination of color and depth information. Experimental results on real life video sequences indicate the promising performance of the proposed adaptive neural network-based scheme.en_US
dc.language.isoenen_US
dc.relation.ispartofArtificial Neural Networks - ICANN 2001en_US
dc.relation.ispartofseriesLecture Notes in Computer Scienceen_US
dc.sourceProc. of International Conference on Artificial Neural Networks, 0-
dc.titleAdaptable neural networks for unsupervised video object segmentation of stereoscopic sequencesen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Artificial Neural Networks (ICANN 2001), 21-25 August 2001, Vienna, Austriaen_US
dc.identifier.doi10.1007/3-540-44668-0_147en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.identifier.spage1060en_US
dc.identifier.epage1066en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldEngineering and Technologyen_US
dc.journalsOpen Accessen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusnot verifieden_US
item.fulltextNo Fulltext-
item.grantfulltextnone-
item.openairetypeConference Paper-
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-
Appears in Collections:Book Chapter / Κεφάλαιο Βιβλίου
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