Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/294
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electronic and Information Engineering | - |
dc.creator | Long, F | - |
dc.creator | Feng, DD | - |
dc.creator | Peng, H | - |
dc.creator | Siu, WC | - |
dc.date.accessioned | 2014-12-11T08:28:25Z | - |
dc.date.available | 2014-12-11T08:28:25Z | - |
dc.identifier.issn | 0272-1716 | - |
dc.identifier.uri | http://hdl.handle.net/10397/294 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | en_US |
dc.rights | This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. | en_US |
dc.subject | Image segmentation | en_US |
dc.subject | Video signal processing | en_US |
dc.title | Extracting semantic video objects | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.description.otherinformation | Dagan Feng | en_US |
dc.identifier.spage | 48 | - |
dc.identifier.epage | 55 | - |
dc.identifier.volume | 21 | - |
dc.identifier.issue | 1 | - |
dc.identifier.doi | 10.1109/38.895132 | - |
dcterms.abstract | We present an accurate and user-interactive semantic video object (SVO) extraction system. Although we also obtain an SVO with an accurate boundary by integrating temporal and spatial information, our way is quite different from others' work. Instead of fusing spatial and temporal segmentations on the first or all the frames of a video sequence, our system adaptively performs spatial and temporal segmentation and fusion when necessary. To achieve this, our system detects the variations between successive frames. We only need to fuse the spatial and temporal segmentation when a large variation occurs. Otherwise, the system tracks the previous SVO's boundary. We find this simple method efficient in both speed and accuracy. Since the temporal segmentation, spatial segmentation, spatio-temporal fusion, and boundary tracking all employ simple algorithms, our system has a low computational complexity. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE computer graphics and applications, Jan./Feb. 2001, v. 21, issue 1, p. 48-55 | - |
dcterms.isPartOf | IEEE computer graphics and applications | - |
dcterms.issued | 2001-01 | - |
dc.identifier.isi | WOS:000166139600010 | - |
dc.identifier.scopus | 2-s2.0-0035121091 | - |
dc.identifier.eissn | 1558-1756 | - |
dc.identifier.rosgroupid | r00937 | - |
dc.description.ros | 2000-2001 > Academic research: refereed > Publication in refereed journal | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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semantic-video_01.pdf | 326.99 kB | Adobe PDF | View/Open |
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