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Event Detection on Online Videos Using Crowdsourced Time-Sync Comment

机译：使用众包时间同步注释对在线视频进行事件检测

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摘要

In recent years, more and more people are like to watch videos online because of its convenience and social features. Due to the limit of entertainment time, there is a new requirement that people prefer to watch some hot video segments rather than an entire video. However, it is a quite time-consuming work to extract the highlight segments in videos manually because the number of videos uploaded to the internet is huge. In this paper, we propose a model of event detection on videos using Time-Sync comments provided by online users. In the model, three features of Time-Sync comments are extracted firstly. Then, user behavior relevance in time series are analyzed to find the video shots that people are interested in most. Metric and its optimization to score video shots for event detection are introduced lastly. Experiments on several movies shows that the events detected by our method coincide with the highlights in the movies. Experiments on movies show that the events detected by our method coincide with the highlights in the movies.
机译：近年来，由于其便利性和社交功能，越来越多的人喜欢在线观看视频。由于娱乐时间的限制，新的要求是人们更喜欢观看一些热门视频片段，而不是整个视频。但是，由于要上传到互联网的视频数量巨大，因此手动提取视频中的突出显示片段是一项非常耗时的工作。在本文中，我们提出了一种使用在线用户提供的时间同步注释对视频进行事件检测的模型。在该模型中，首先提取了时间同步注释的三个特征。然后，分析时间序列中与用户行为的相关性，以找到人们最感兴趣的视频镜头。最后介绍了度量标准及其对视频镜头进行评分以进行事件检测的优化。在几部电影上进行的实验表明，通过我们的方法检测到的事件与电影中的亮点一致。在电影上进行的实验表明，通过我们的方法检测到的事件与电影中的亮点相吻合。

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