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Semantic features based news stories segmentation for news retrieval

机译:基于语义的功能的新闻故事细分新闻检索

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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.
机译:为了有效地找到所需的视频剪辑,基于内容的视频检索技术的研究已成为最突出的研究领域之一。本文提出了一种基于多种语义特征的新闻故事分割方法。开发了具有新闻故事分割和浏览和检索的功能的原型系统,用于测试所提出的方法。在这种方法中,检测到新闻视频中的视频特征(即锚点)和音频特征(即扬声器的静音差距和变化),并用于分割新闻故事以及文本信息(即提取的标题来自新闻视频)。实验结果表明,所提出的方法具有比基于标题的方法更高的分割精度。

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