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Switchable TV-series Browsing Scheme Using Alignment of Video and Episode Plot Description

机译：使用视频和情节图说明对齐的可切换电视系列浏览方案

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Watching TV-series is very time-consuming and it is tired to see out dozens of episodes at one time, but we always can not help doing that because of the interesting plot. In this paper, we investigate to automatically align the video with the widely existing Episode Plot Description (EPD) and design a scheme to flexibly switch TV-serial browsing between videos and EPDs with two principles: (1) optimizing the interesting content reservation of teleplay for audiences; and (2) flexibly offering convenience for quickly acquiring the main content and skimming long and boring video clips. The scheme mainly contains three components: video entities extracting and EPD parsing, video scenes and EPD sentences associating, and alignment. Video entities extracting and EPD parsing utilizes face recognition, location recognition and action learning as well as the Chinese Natural Language Processing techniques to get several video entities and EPD words named association elements. Video scenes and EPD sentences associating then use the association elements distance calculation based on ConceptNet-Zn to associate video scenes with EPD sentences. Finally, minimum cost estimate mechanism is used to align the scenes sequence to the EPD sentences and also a commendable browsing scheme is accomplished via the alignment results. Experiments conducted on a set of TV serials have demonstrated the usefulness and effectiveness of the scheme.
机译：观看电视连续剧非常耗时，一次只看数十集很累，但是由于有趣的情节，我们总是不禁这样做。在本文中，我们研究将视频与广泛存在的情节剧情描述（EPD）自动对齐，并设计一种方案，以两种原则灵活地在视频和EPD之间切换电视串行浏览：（1）优化电视剧的有趣内容保留给观众（2）灵活地提供便利，以便快速获取主要内容并浏览冗长而乏味的视频剪辑。该方案主要包括三个部分：视频实体提取和EPD解析，视频场景和EPD语句关联以及对齐。视频实体提取和EPD解析利用面部识别，位置识别和动作学习以及中国自然语言处理技术来获得多个视频实体和称为关联元素的EPD单词。然后将视频场景和EPD句子关联起来，然后使用基于ConceptNet-Zn的关联元素距离计算将视频场景与EPD句子关联起来。最后，使用最小成本估算机制将场景序列与EPD句子对齐，并通过对齐结果实现了值得称赞的浏览方案。在一组电视连续剧上进行的实验证明了该方案的有用性和有效性。

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