Efficient and Language Independent News Story Segmentation for Telecast News Videos

Anubha Jindal, Aditya Tiwari, Hiranmay Ghosh
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引用次数: 9

Abstract

A TV news program comprises a continuous video stream containing a number of news stories, interspersed with commercials and headlines. This paper presents a method to detect the story boundaries and to separate out the stories from the other components and from each other. The method is based on movement of ticker text bands and repetition of ticker texts during different parts of a news program. The method does not use any language processing tool and is independent of language of telecast. It uses some simple features to distinguish news from the advertisements and can be used for large scale news indexing. We produce some test results on channels telecasting in English and few other Indian languages.
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面向电视新闻视频的高效、独立语言的新闻故事分割
电视新闻节目包括连续的视频流,其中包含一些新闻故事,穿插着商业广告和标题。本文提出了一种检测故事边界并将故事从其他组件中分离出来的方法。该方法是基于在新闻节目的不同部分的股票文本带的运动和股票文本的重复。该方法不使用任何语言处理工具,不依赖于电视广播的语言。它使用一些简单的特征来区分新闻和广告,可以用于大规模的新闻索引。我们在英语和少数其他印度语言的电视频道上发布了一些测试结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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