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dc.contributor.authorShan, MKen_US
dc.contributor.authorLee, SYen_US
dc.date.accessioned2014-12-08T15:27:13Z-
dc.date.available2014-12-08T15:27:13Z-
dc.date.issued1998en_US
dc.identifier.isbn0-8194-3022-6en_US
dc.identifier.issn0277-786Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/19445-
dc.identifier.urihttp://dx.doi.org/10.1117/12.319738en_US
dc.description.abstractMotion is one of the most prominent features of video. For content-based video retrieval, motion trajectory is the intuitive specification of motion features. In this paper, approaches for video retrieval via single motion trajectory and multiple motion trajectories are addressed. For the retrieval via single motion trajectory, the trajectory is modeled as a sequence of segments and each segment is represented as the slope. Two quantitative similarity measures and corresponding algorithms based on the sequence similarity are presented. For the retrieval via multiple motion trajectories, the trajectories of the video are modeled as a sequence of symbolic pictures. Four quantitative similarity measures and algorithms, which are also based on the sequence similarity, are proposed. All the proposed algorithms are developed based on the dynamic programming approach.en_US
dc.language.isoen_USen_US
dc.subjectcontent-based retrievalen_US
dc.subjectvideo retrievalen_US
dc.subjectmotion trajectoryen_US
dc.subjectsimilarity measuresen_US
dc.subjectsequence similarityen_US
dc.titleContent-based video retrieval via motion trajectoriesen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1117/12.319738en_US
dc.identifier.journalELECTRONIC IMAGING AND MULTIMEDIA SYSTEMS IIen_US
dc.citation.volume3561en_US
dc.citation.spage52en_US
dc.citation.epage61en_US
dc.contributor.department資訊科學與工程研究所zh_TW
dc.contributor.departmentInstitute of Computer Science and Engineeringen_US
dc.identifier.wosnumberWOS:000077160100007-
Appears in Collections:Conferences Paper


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