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dc.contributor.authorHsu, FJen_US
dc.contributor.authorLee, SYen_US
dc.contributor.authorLin, BSen_US
dc.date.accessioned2014-12-08T15:48:47Z-
dc.date.available2014-12-08T15:48:47Z-
dc.date.issued1998-08-01en_US
dc.identifier.issn1045-926Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/32458-
dc.description.abstractVideo data contains a large amount of spatial and temporal information. The changes of video frames are quite useful for motion analysis and cannot be provided by other media easily. Chang et al: had proposed an effective 2D string approach for spatial indexing of image data. In this paper, we extend this iconic approach and apply it to video data indexing. We propose 2D C-trees to represent the spatial content within individual frames. A video sequence can then be represented and indexed by a temporal set or an ordering set of 2D C-trees. The similarity retrieval of video matching problem becomes the problem of video sequence matching by computing the similarity, or the minimum cost of matched frames. We present three schemes, full-sequence matching, segment matching and subsequence matching, for video information retrieval. The matching schemes can be modified and extended to approximate sequence matching by computing the partial distance for providing a comprehensive retrieval of video data. A prototype video information system is also developed to validate the effectiveness of video data indexing by 2D C-trees. (C) 1998 Academic Press.en_US
dc.language.isoen_USen_US
dc.titleVideo data indexing by 2D C-treesen_US
dc.typeArticleen_US
dc.identifier.journalJOURNAL OF VISUAL LANGUAGES AND COMPUTINGen_US
dc.citation.volume9en_US
dc.citation.issue4en_US
dc.citation.spage375en_US
dc.citation.epage397en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000075623500002-
dc.citation.woscount8-
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