HEAL DSpace

Intelligent visual descriptor extraction from video sequences

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dc.contributor.author Tzouveli, P en
dc.contributor.author Andreou, G en
dc.contributor.author Tsechpenakis, G en
dc.contributor.author Avrithis, Y en
dc.contributor.author Kollias, S en
dc.date.accessioned 2014-03-01T01:20:39Z
dc.date.available 2014-03-01T01:20:39Z
dc.date.issued 2004 en
dc.identifier.issn 0302-9743 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/16001
dc.relation.uri http://www.scopus.com/inward/record.url?eid=2-s2.0-33846076935&partnerID=40&md5=7ccdf837d2f041289ab34fc15d343c25 en
dc.subject.classification Computer Science, Theory & Methods en
dc.title Intelligent visual descriptor extraction from video sequences en
heal.type journalArticle en
heal.language English en
heal.publicationDate 2004 en
heal.abstract Extraction of visual descriptors is a crucial problem for state-of-the-art visual information analysis. In this paper, we present a knowledge-based approach for detection of visual objects in video sequences, extraction of visual descriptors and matching with pre-defined objects. The proposed approach models objects through their visual descriptors defined in MPEG7. It first extracts moving regions using an efficient active contours technique. It then computes visual descriptions of the moving regions including color, motion and shape features that are invariant to affine transformations. The extracted features are matched to a-priori knowledge about the objects' descriptions, using appropriately defined matching functions. Results are presented which illustrate the theoretical developments. © Springer-Verlag 2004. en
heal.publisher SPRINGER-VERLAG BERLIN en
heal.journalName Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) en
heal.bookName LECTURE NOTES IN COMPUTER SCIENCE en
dc.identifier.isi ISI:000222846700009 en
dc.identifier.volume 3094 en
dc.identifier.spage 132 en
dc.identifier.epage 146 en


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