基于语义特征的新闻故事分割

Wenping Liu, Gang Yang, Xin-yuan Huang
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引用次数: 2

摘要

为了高效地找到想要的视频片段,基于内容的视频检索技术的研究已成为当前研究的热点之一。提出了一种基于多语义特征的新闻故事分割方法。开发了一个具有新闻故事分割、浏览和检索功能的原型系统,对该方法进行了测试。该方法通过检测新闻视频中的视频特征(即主播人脸)和音频特征(即沉默间隙和说话人的变化),将新闻故事与文本信息(即从新闻视频中提取的字幕)一起进行分割。实验结果表明,该方法比基于标题的方法具有更高的分割精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semantic features based news stories segmentation for news retrieval
In order to find desired video clips efficiently, the research on content-based video retrieval techniques has become one of the most prominent research areas. A multiple semantic features based news stories segmentation approach is proposed in this paper. A prototype system with the capability of the news stories segmentation, and browsing & retrieval is developed for testing the proposed approach. In this approach, the video features, (i.e. anchor-person face) and the audio features (i.e. the silence gap and change of speaker) in the news video are detected and used to segment the news stories along with text information (i.e. extracted caption from the news video). The experimental results demonstrate that the proposed approach has higher segmentation precision than that of the caption-based method.
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