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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内部结构识别方法

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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:电视频道的数量不断增加,导致根据严格的规则(例如,考虑图形宪章,制片厂的反复出现等),在电视频道上制作和播放的视频文件的数量有所增加。因此,从这些规则推导出的先验知识的使用有助于改善视频文档的分割和索引的质量。但是,自动视频分割工作的有效性取决于视频类型。因此,为了获得更好的分割质量,有必要考虑有关视频类型的先验知识。在这种情况下,本文提出了一种基于视频语法的方法来识别电视流中的节目并推断其内部结构。这种方法试图自动提取先验知识以构想语法描述符。选择电视新闻节目的研究案例来验证所采用的方法,因为它是多媒体内容中最重要的类型之一。

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