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A Video Grammar-Based Approach for TV News Localization and Intra-structure Identification in TV Streams

机译:基于视频语法的电视新闻本地化和电视流中的结构内识别方法

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The growing number of TV channels led to an expansion of the mass of video documents produced and broadcast on TV channels according to precise rules (e.g. consideration of the graphic charter, recurring of studios...). Thus, the use of a priori knowledge deduced from these rules contributes to the amelioration of the quality of segmentation and indexing of video documents. However, the effectiveness of automatic video segmentation works depends on video type. So, for a better quality of the segmentation, it is necessary to consider a priori knowledge concerning video types. In this context, this paper suggests an approach based on video grammar to identify programs in TV streams and deduce their internal structure. This approach attempts to automatically extract a priori knowledge to conceive the grammar descriptors. The study case of TV news programs is selected to validate the adopted approach since it is one of the most important types of multimedia content.
机译:越来越多的电视频道导致了根据精确的规则在电视频道上生产和广播的视频文档的扩展(例如,考虑图形租赁,工作室的重复......)。因此,使用从这些规则推断的先验知识有助于改善视频文档的分割质量和索引。然而,自动视频分段工作的有效性取决于视频类型。因此,为了更好的分割质量,有必要考虑有关视频类型的先验知识。在这种情况下,本文建议了一种基于视频语法的方法,以识别电视流中的程序并推断出其内部结构。这种方法试图自动提取先验知识以构思语法描述符。选择电视新闻节目的研究案例以验证采用的方法,因为它是最重要的多媒体内容类型之一。

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