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Efficient indexing, browsing and retrieval of image/video content.

机译:高效索引,浏览和检索图像/视频内容。

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摘要

With advances in the computer technologies and the advent of the World Wide Web, there has been an explosion in the amount and complexity of digital data being generated, stored, transmitted, analyzed, and accessed. Much of this information is multimedia in nature, including digital images, video, audio, graphics, and text data. In order to make use of this vast amount of data, efficient and effective techniques to analyze and retrieve multimedia information based on its content need to be developed.; This thesis is dedicated to the two of the most important media types: images and videos. Novel approaches to feature analysis, content representation, indexing and retrieval are presented.; The main contributions of this thesis axe: (i) reliable and robust feature extraction and representation techniques for images and videos; (ii) introduction of relevance feedback techniques to image retrieval, which greatly improves the retrieval performance and alleviates the user's query formulation burden; and (iii) introduction of a video hierarchical structure and construction of video Table of Contents to facilitate the video analysis and retrieval. Extensive experimental results over large test data sets have validated the proposed approaches.
机译:随着计算机技术的进步和万维网的出现,正在生成,存储,传输,分析和访问的数字数据的数量和复杂性激增。本质上,许多信息都是多媒体,包括数字图像,视频,音频,图形和文本数据。为了利用海量数据,需要开发有效和有效的技术来根据其内容分析和检索多媒体信息。本文致力于两种最重要的媒体类型:图像和视频。提出了用于特征分析,内容表示,索引编制和检索的新颖方法。本论文的主要贡献是:(i)可靠且健壮的图像和视频特征提取和表示技术; (ii)在图像检索中引入相关反馈技术,从而大大提高了检索性能并减轻了用户的查询制定负担; (iii)引入视频分级结构和视频目录结构,以促进视频分析和检索。在大型测试数据集上的大量实验结果验证了所提出的方法。

著录项

  • 作者

    Rui, Yong.;

  • 作者单位

    University of Illinois at Urbana-Champaign.;

  • 授予单位 University of Illinois at Urbana-Champaign.;
  • 学科 Engineering Electronics and Electrical.; Computer Science.
  • 学位 Ph.D.
  • 年度 1999
  • 页码 145 p.
  • 总页数 145
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 无线电电子学、电信技术;自动化技术、计算机技术;
  • 关键词

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