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Special issue on Multimedia Event Detection

机译：多媒体事件检测特刊

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摘要

Recently, the generation, storage and sharing of multimedia video data has increased at an astronomical rate. In 2012, over 100h of videos was uploaded on YouTube every minute. The multimedia data being shared covers a wide variety, ranging from homemade birthday videos to professionally produced comedy skits, and from woodworking tutorials to breaking news reports and analysis, etc. Although the storage and dissemination capacity of the network has grown exponentially, the development of automatic tools to search and retrieve this data has not kept pace, and by large, manual annotation and categorization is used for video search. Manual annotation, along with being expensive and slow, cannot express the rich content of video data. A layperson or an analyst might want to search the video not only based on the main topic (e.g., news report of a protest) but also based on the events taking place, the activities of the people and entities being viewed, the conversations taking place and the sounds recorded.
机译：近来，多媒体视频数据的产生，存储和共享以天文数字的速度增长。 2012年，每分钟有超过100小时的视频上传到YouTube。共享的多媒体数据涵盖了各种各样的范围，从自制的生日视频到专业制作的喜剧短剧，从木工教程到最新新闻报道和分析，等等。尽管网络的存储和传播能力呈指数增长，自动搜索和检索此数据的工具并没有跟上步伐，并且大体上，视频搜索使用了手动注释和分类。手动注释以及昂贵且缓慢的方法无法表达视频数据的丰富内容。外行或分析师可能不仅要根据主要主题（例如，抗议活动的新闻报道）来搜索视频，还希望根据发生的事件，所查看的人员和实体的活动，所进行的对话来搜索视频并记录声音。

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  • 来源
    《Machine Vision and Applications》 |2014年第1期|1-4|共4页
  • 作者

    Thomas B. Moeslund; Omar Javed; Yu-Gang Jiang; R. Manmatha;

  • 作者单位

    Aalborg University, Aalborg, Denmark;

    SRI International, Princeton, NJ, USA;

    School of Computer Science, Fudan University, Shanghai, China;

    School of Computer Science, University of Massachusetts, Amherst, MA 01007, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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