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Video Annotation System Based on Categorizing and Keyword Labelling

机译:基于分类和关键词标注的视频注释系统

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摘要

In this work, we demonstrate an automatic video annotation system which can provide users with the representative keywords for new videos. The system explores the hierarchical concept model and multiple feature model to improve the effectiveness of annotation, which consists of two components: a SVM classifier to ascertain the category; and a multiple feature model to label the keywords. We implement the demo system using the videos downloaded from YouTube. The results show the superiority of our approach.
机译:在这项工作中,我们演示了一个自动视频注释系统,该系统可以为用户提供新视频的代表性关键字。该系统探索了分层概念模型和多特征模型以提高注释的有效性,该模型包括两个组件:SVM分类器,用于确定类别; SVM分类器,用于确定类别。以及用于标记关键字的多功能模型。我们使用从YouTube下载的视频实施演示系统。结果表明了我们方法的优越性。

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  • 来源
  • 会议地点 Brisbane(AU);Brisbane(AU)
  • 作者单位

    Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA School of EECS, Peking University;

    Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA School of EECS, Peking University;

    School of ITEE, University of Queensland, Australia;

    Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA School of EECS, Peking University;

    Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, CHINA School of EECS, Peking University;

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  • 原文格式 PDF
  • 正文语种 eng
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