基于图论聚类的新闻视频主播镜头检测

Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003 Pub Date : 2003-09-27 DOI:10.1109/ICCIMA.2003.1238109

G. Xinbo, Li Jie, Yang Bing

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引用次数: 16

摘要

在基于内容的新闻视频索引检索系统中，主播镜头检测对于视频镜头的语义解析、索引信息和线索提取具有重要意义。本文提出了一种基于新闻节目中主播关键帧相似性的无模型主播镜头检测方案。首先，用任何有效的视频句法解析算法将新闻视频分割成多个视频片段。对于每个镜头，从帧序列中提取一帧作为代表性关键帧。然后对关键帧进行图论聚类算法来识别主播帧。主播镜头进一步区别于其他新闻视频镜头。在217篇新闻报道的主播镜头检测实验中，该方案的准确率达到100%，召回率超过97.69%。

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A graph-theoretical clustering based anchorperson shot detection for news video indexing

Anchorperson shot detection is of significance for video shot semantic parsing and indexing information and clues extraction in content-based news video indexing and retrieval system. This paper presents a model-free anchorperson shot detection scheme based on the similarity among the anchorperson key frames throughout each news program. First, a news video is segmented into video shots with any effective video syntactic parsing algorithm. For each shot, a frame is extracted from the frame sequence as a representative key frame. Then the graph-theoretical clustering algorithm is performed on the key frames to identify the anchorperson frames. The anchorperson shots are further distinguished from other news video shots. The proposed scheme achieves a precision of 100% and a recall of over 97.69% in the anchorperson shot detection experiment of 217 news stories.

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来源期刊

Proceedings Fifth International Conference on Computational Intelligence and Multimedia Applications. ICCIMA 2003

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