完整後設資料紀錄
DC 欄位語言
dc.contributor.authorChen, Liang-Huaen_US
dc.contributor.authorLai, Yu-Chunen_US
dc.contributor.authorLiao, Hong-Yuan Marken_US
dc.date.accessioned2014-12-08T15:12:31Z-
dc.date.available2014-12-08T15:12:31Z-
dc.date.issued2008-03-01en_US
dc.identifier.issn0031-3203en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.patcog.2007.07.024en_US
dc.identifier.urihttp://hdl.handle.net/11536/9610-
dc.description.abstractScene extraction is the first step toward semantic understanding of a video. It also provides improved browsing and retrieval facilities to users of video database. This paper presents an effective approach to movie scene extraction based on the analysis of background images. Our approach exploits the fact that shots belonging to one particular scene often have similar backgrounds. Although part of the video frame is covered by foreground objects, the background scene can still be reconstructed by a mosaic technique. The proposed scene extraction algorithm consists of two main components: determination of the shot similarity measure and a shot grouping process. In our approach, several low-level visual features are integrated to compute the similarity measure between two shots. On the other hand, the rules of film-making are used to guide the shot grouping process. Experimental results show that our approach is promising and outperforms some existing techniques. (C) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectvideo content analysisen_US
dc.subjectvideo segmentationen_US
dc.subjectshot clusteringen_US
dc.subjectscene extractionen_US
dc.titleMovie scene segmentation using background informationen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.patcog.2007.07.024en_US
dc.identifier.journalPATTERN RECOGNITIONen_US
dc.citation.volume41en_US
dc.citation.issue3en_US
dc.citation.spage1056en_US
dc.citation.epage1065en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000251357100024-
dc.citation.woscount16-
顯示於類別:期刊論文


文件中的檔案:

  1. 000251357100024.pdf

若為 zip 檔案,請下載檔案解壓縮後,用瀏覽器開啟資料夾中的 index.html 瀏覽全文。