DC FieldValueLanguage
dc.contributor.authorNtalianis, Klimis-
dc.contributor.authorDoulamis, Anastasios-
dc.contributor.authorDoulamis, Nikolaos-
dc.contributor.authorKollias, Stefanos-
dc.date.accessioned2024-07-30T12:13:02Z-
dc.date.available2024-07-30T12:13:02Z-
dc.date.issued2000-
dc.identifiergoogle_scholar-vd7COBsAAAAJ:ruyezt5ZtCIC-
dc.identifier.issn1793-6349-
dc.identifier.othervd7COBsAAAAJ:ruyezt5ZtCIC-
dc.identifier.urihttps://uniwacris.uniwa.gr/handle/3000/2769-
dc.description.abstractThis paper presents an efficient technique for unsupervised content-based segmentation in stereoscopic video sequences by appropriately combined different content descriptors in a hierarchical framework. Three main modules are involved in the proposed scheme; extraction of reliable depth information, image partition into color and depth regions and a constrained fusion algorithm of color segments using information derived from the depth map. In the first module, each stereo pair is analyzed and the disparity field and depth map are estimated. Occlusion detection and compensation are also applied for improving the depth map estimation. In the following phase, color and depth regions are created using a novel complexity-reducing multiresolution implementation of the Recursive Shortest Spanning Tree algorithm (M-RSST). While depth segments provide a coarse representation of the image content, color regions describe very accurately object boundaries. For this reason, in the final phase, a new segmentation fusion algorithm is employed which projects color segments onto depth segments. Experimental results are presented which exhibit the efficiency of the proposed scheme as content-based descriptor, even in case of images with complicated visual content.en_US
dc.language.isoenen_US
dc.publisherWorld Scientific Publishing Companyen_US
dc.relation.ispartofInternational Journal on Artificial Intelligence Toolsen_US
dc.sourceInternational Journal on Artificial Intelligence Tools 9 (02), 277-303, 2000-
dc.subjectUnsupervised segmentationen_US
dc.subjectM-RSSTen_US
dc.subjectDepth/color extractionen_US
dc.subjectInformation fusionen_US
dc.titleEfficient unsupervised content-based segmentation in stereoscopic video sequencesen_US
dc.typeArticleen_US
dc.identifier.doi10.1142/S0218213000000197en_US
dc.relation.deptDepartment of Business Administrationen_US
dc.relation.facultySchool of Administrative, Economics and Social Sciencesen_US
dc.relation.volume9en_US
dc.relation.issue2en_US
dc.identifier.spage277en_US
dc.identifier.epage303en_US
dc.collaborationUniversity of West Attica (UNIWA)en_US
dc.subject.fieldEngineering and Technologyen_US
dc.journalsSubscriptionen_US
dc.publicationPeer Revieweden_US
dc.countryGreeceen_US
local.metadatastatusverifieden_US
item.openairetypeArticle-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.languageiso639-1en-
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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