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High-Speed Topic Organizer of TV Shows Using Video Dialog Detection

机译:使用视频对话框检测的电视节目高速主题组织者

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摘要

Recently, due to the rapid spread of digital video recorders capable of storing a large number of TV programs, there is a great need for easy interfaces for viewing program content and for accessing scenes of interest. To provide such functions, it is necessary and effective to segment a recorded TV program into temporal sections according to the content structure. However, in conventional approaches such as cut-detection methods, content is chopped up into segments that are too short, and the computational costs of intelligent recognition methods for speech, face, and text are prohibitive in many cases. The author has developed a light and high-speed algorithm which estimates the structure of video content and completes temporal segmentation instantly after the recording. The proposed method introduces a measurement which denotes the likelihood of a given temporal part of a recorded TV program being a dialog scene, according to the appearances of similar shots. With this measurement, related consecutive shots are determined as being in a dialog scene, and consequently topics in a news program and sections in a variety show are effectively estimated. In this paper, the author discusses development, implementation, and effectiveness of the system which provides automatic segmentation of a variety of recorded TV programs, applying the proposed method.
机译:近来,由于能够存储大量电视节目的数字视频记录器的迅速普及,迫切需要用于观看节目内容和访问感兴趣场景的简单接口。为了提供这样的功能,有必要并且有效地根据内容结构将记录的TV节目分割成时间段。但是,在诸如剪切检测方法之类的常规方法中,将内容切成太短的段,并且在许多情况下,语音,面部和文本的智能识别方法的计算成本很高。作者开发了一种轻量级的高速算法,该算法可估算视频内容的结构并在记录后立即完成时间分段。所提出的方法引入了一种测量,该测量根据相似镜头的出现来表示所记录的电视节目的给定时间部分是对话场景的可能性。通过这种测量,相关的连续镜头被确定为处于对话场景中,因此可以有效地估计新闻节目中的主题和综艺节目中的部分。在本文中,作者讨论了使用提出的方法的系统的开发,实现和有效性,该系统可以自动分割各种录制的电视节目。

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