Image based tracking of news stories

Seventh IEEE International Symposium on Multimedia (ISM'05) Pub Date : 2005-12-12 DOI:10.1109/ISM.2005.67

Jedrzej Z. Miadowicz, J. Gauch, Abhishek Shivadas

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引用次数: 1

Abstract

Broadcasters often reuse video clips while reporting news stories. New clips are added to the story as it develops replacing old clips. A subset of these video clips may be replayed as follow up stories are investigated. This pattern of video repetition can be used to impose a story level organization on video clips that are broadcast by one or more news channels. In this paper, we describe an automated system for detecting and tracking repeated video clips in news broadcasts. We begin by performing temporal video segmentation to divide the video into shots and scenes. As each frame of the video source is processed, we extract low-level video features that are used to perform repeated sequence detection in realtime. Our matching algorithms have been adapted to recognize partial clip reuse while remaining robust to minor variations in the video source. Our system then builds a set of shots relevant to the news story being tracked, called a story core, and identifies new story episodes by detecting occurrences of shots belonging to this set. The story core is allowed to evolve dynamically over time to account for additional video footage as it becomes available. This technique was evaluated on a 24-hour broadcast of CNN News channel where we were very successful locating and tracking video clips associated with selected news stories.

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基于图像的新闻故事跟踪

广播公司在报道新闻时经常重复使用视频片段。随着故事的发展，新的片段被添加到故事中，取代旧的片段。这些视频片段的一个子集可能会在调查后续故事时重播。这种视频重复的模式可以用来对由一个或多个新闻频道播放的视频片段施加故事级别的组织。在本文中，我们描述了一个自动检测和跟踪新闻广播中重复视频片段的系统。我们首先执行时间视频分割，将视频划分为镜头和场景。在处理视频源的每一帧时，我们提取低级视频特征，用于实时执行重复序列检测。我们的匹配算法已经适应了识别部分剪辑重用，同时对视频源中的微小变化保持鲁棒性。然后，我们的系统建立一组与正在跟踪的新闻故事相关的镜头，称为故事核心，并通过检测属于该集的镜头的出现来识别新的故事情节。故事核心可以随着时间的推移而动态发展，以解释额外的视频片段，因为它变得可用。这项技术在CNN新闻频道的24小时广播中进行了评估，我们非常成功地定位和跟踪了与选定新闻故事相关的视频剪辑。

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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来源期刊

Seventh IEEE International Symposium on Multimedia (ISM'05)

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