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Article: Video partitioning by temporal slice coherency

TitleVideo partitioning by temporal slice coherency
Authors
KeywordsColor-texture segmentation
Cut detection
Dissolve detection
Spatio-temporal pattern
Spatio-temporal slice
Video partitioning
Wipe detection
Issue Date2001
PublisherIEEE
Citation
Ieee Transactions On Circuits And Systems For Video Technology, 2001, v. 11 n. 8, p. 941-953 How to Cite?
AbstractWe present a novel approach for video partitioning by detecting three essential types of camera breaks, namely cuts, wipes, and dissolves. The approach is based on the analysis of temporal slices which are extracted from the video by slicing through the sequence of video frames and collecting temporal signatures. Each of these slices contains both spatial and temporal information from which coherent regions are indicative of uninterrupted video partitions separated by camera breaks. Properties could further be extracted from the slice for both the detection and classification of camera breaks. For example, cut and wipes are detected by color-texture properties, while dissolves are detected by statistical characteristics. The approach has been tested by extensive experiments.
Persistent Identifierhttp://hdl.handle.net/10722/65528
ISSN
2015 Impact Factor: 2.254
2015 SCImago Journal Rankings: 1.606
References

 

DC FieldValueLanguage
dc.contributor.authorNgo, CWen_HK
dc.contributor.authorPong, TCen_HK
dc.contributor.authorChin, RTen_HK
dc.date.accessioned2010-08-31T07:15:07Z-
dc.date.available2010-08-31T07:15:07Z-
dc.date.issued2001en_HK
dc.identifier.citationIeee Transactions On Circuits And Systems For Video Technology, 2001, v. 11 n. 8, p. 941-953en_HK
dc.identifier.issn1051-8215en_HK
dc.identifier.urihttp://hdl.handle.net/10722/65528-
dc.description.abstractWe present a novel approach for video partitioning by detecting three essential types of camera breaks, namely cuts, wipes, and dissolves. The approach is based on the analysis of temporal slices which are extracted from the video by slicing through the sequence of video frames and collecting temporal signatures. Each of these slices contains both spatial and temporal information from which coherent regions are indicative of uninterrupted video partitions separated by camera breaks. Properties could further be extracted from the slice for both the detection and classification of camera breaks. For example, cut and wipes are detected by color-texture properties, while dissolves are detected by statistical characteristics. The approach has been tested by extensive experiments.en_HK
dc.languageengen_HK
dc.publisherIEEEen_HK
dc.relation.ispartofIEEE Transactions on Circuits and Systems for Video Technologyen_HK
dc.subjectColor-texture segmentationen_HK
dc.subjectCut detectionen_HK
dc.subjectDissolve detectionen_HK
dc.subjectSpatio-temporal patternen_HK
dc.subjectSpatio-temporal sliceen_HK
dc.subjectVideo partitioningen_HK
dc.subjectWipe detectionen_HK
dc.titleVideo partitioning by temporal slice coherencyen_HK
dc.typeArticleen_HK
dc.identifier.emailChin, RT: rchin@hku.hken_HK
dc.identifier.authorityChin, RT=rp01300en_HK
dc.description.naturelink_to_subscribed_fulltexten_HK
dc.identifier.doi10.1109/76.937435en_HK
dc.identifier.scopuseid_2-s2.0-0035422807en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0035422807&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume11en_HK
dc.identifier.issue8en_HK
dc.identifier.spage941en_HK
dc.identifier.epage953en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridNgo, CW=7005184304en_HK
dc.identifier.scopusauthoridPong, TC=7004618149en_HK
dc.identifier.scopusauthoridChin, RT=7102445426en_HK
dc.identifier.citeulike11825870-

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