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研究生(外文):Yi-An Deng
論文名稱(外文):Ontological Video Management System-Case in Soccer Video
指導教授(外文):Lawrence Y.Deng
外文關鍵詞:OntologyContent managementIndexingRetrievalSummarizationSearch
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科技的進步快速,越來越多的影音訊息充斥著我們的生活,這些訊息可能是靜態的圖片、3D圖形、聲音或video等,這些訊息可能以類比或數位的方式被存在照片、底片、磁帶等實體中,隨著影音訊息的需求越來越多,相對的我們所使用存放影音訊的實體也日益增加,在眾多的影音訊息中,管理起相當的不便,若是要從中找尋自已想要的或喜歡的訊息那就更加的困難了。近年來,由於運動比賽節目越來越普遍,一般大眾或運動專業工作者隨時可利用各式各樣的數位錄影工具將其錄製下來,並擷取有用的資訊或是精彩的片段,以便閒暇再觀看,使得運動影片分析及萃取之研究開始引人注意。其中又以探討精彩片段分析及萃取方法之研究為主,主因係運動影片結構較其他類型的影片具有一定規則,另一原因為精彩片段可協助群眾快速掌握重要運動資訊,如棒球比賽的全壘打、足球比賽的進球,以及網球比賽中雙方對壘等場景萃取,更是學界及業界積極投入研究的方向。因此本論文以足球影片為例以本體論(Ontology)來描述和定義影音內容,並使用本體論的知識,建構出一套運動影片本體論(Sport Video Ontology),將所建構之運動影片本體論轉存資料庫欄位後在將我們所分析足球影片之數據存入(例:分鏡、logo、shot內容等…)在將完整的足球運動影片資料庫轉換成可延伸標記語言(Extensible Markup Language,簡稱XML)表示,讓足球影片在XML表示下能夠更完整的描述整個足球影片。經由讀取XML的檔案格式,使用者可以有效率地搜尋、過濾和定義想要的影音資料。
How to indexing and retrieving and then to make event mining in video content management system are become more and more important. In this paper, we reconstructed a novel description based on the ontology for the soccer video. The video content management system provided event feature manipulations at multiple levels: signal, structural, or semantic in order to meet user preferences while striking the overall utility of the video. The experiment results showed that our proposed methodologies could correctly detect shot switch, logo and also to achieve the purpose of video indexing, retrieval and summarization.
第一章 緒論 1
1.1 研究動機 1
1.2 論文架構 2
第二章 國內外相關研究 4
2.1 多媒體內容描述 4
2.1.1 MPEG 4
2.1.2 MPEG-7簡介 5
2.1.3 MPEG-7應用 8
2.2 本體論(Ontology) 8
2.2.1 何為本體論 8
2.2.2 本體論整合問題的方法 10
2.2.3 本體論應用 12
2.3 影片分析相關研究 12
2.3.1 分鏡偵測(Shot boundary detection) 12
2.3.2 鏡頭分類(Shot Classification) 16
2.3.3 慢動作及重播偵測(Slow-Motion Replay Detection) 16
2.3.4 移動物件切割與追蹤(Moving Object Segmentation and Tracking) 16
2.3.5 影片語意分析(Video Semantic analysis) 17
2.3.6 影片分析應用 17
2.4 MPEG-7、本體論、低階特徵分析比較 18
第三章 運動影片本體論(Sport Video Ontology) 20
3.1 Protégé-3.1.1 20
3.2 分鏡(Shot) 24
3.3 精彩鏡頭(Excellent Replay) 27
3.4 影片內容(Video Content) 29
3.5 運動影片本體論(Sport Video Ontology) 30
第四章 系統實作 36
4.1 建立運動影片本體論 37
4.2 運動影片本體論資料庫 38
4.3 特徵擷取 39
4.3.1 直接轉換、漸進式的轉換 39
4.3.2 Logo偵測 40
4.4 分析影片與新增個體 41
4.5 資料庫數據轉換XML 43
4.6 影片播放搜尋及摘要 44
第五章 結論與未來探討 46
5.1 結論 46
5.2 未來發展 47
參考文獻 48
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