中大機構典藏-NCU Institutional Repository-提供博碩士論文、考古題、期刊論文、研究計畫等下載:Item 987654321/51594
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 78852/78852 (100%)
造訪人次 : 38473778      線上人數 : 152
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋


    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/51594


    題名: VIDEO CONTENT SUMMARIZATION AND AUGMENTATION BASED ON STRUCTURAL SEMANTIC PROCESSING AND SOCIAL NETWORK ANALYSIS
    作者: Chen,BW;Wang,JF;Wang,JC
    貢獻者: 資訊工程學系
    關鍵詞: PROTEIN-INTERACTION NETWORKS;VISUAL ANALYSIS;SIMILARITY;RETRIEVAL;FRAMEWORK;MODEL
    日期: 2010
    上傳時間: 2012-03-27 18:56:59 (UTC+8)
    出版者: 國立中央大學
    摘要: Video summarization techniques have been proposed for years to offer people comprehensive understanding of a whole story on video. However, although these traditional methods give brief summaries for users, they still do not provide concept-organized or structural views. Besides, the knowledge they offer to users is often limited to existing videos. In this study, we present a structural video content summarization that utilizes the four kinds of entities, "who," "what," "where," and "when," to establish the framework of the video contents. Relevant media associated with each entity in the online resource are also analyzed to enrich existing contents. With the above-mentioned information, the structure of the story and its complementary knowledge can be built up according to the entities. Therefore, users can not only browse the video efficiently but also focus on what they are interested in. In order to construct the fundamental system, we employ the maximum entropy criterion to integrate visual and text features extracted from video frames and speech transcripts, generating high-level concept entities. Shots are linked together based on their contents. After constructing the relational graph, we exploit the graph entropy model to detect meaningful shots and relations. The social network analysis based on the Markov clustering algorithm is performed to explore relevant information online. The results demonstrate that our system can achieve excellent performance and information coverage.
    關聯: JOURNAL OF THE CHINESE INSTITUTE OF ENGINEERS
    顯示於類別:[資訊工程學系] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML499檢視/開啟


    在NCUIR中所有的資料項目都受到原著作權保護.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 隱私權政策聲明