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An Efficient Method for Near-Duplicate Video Detection

机译：一种有效的近重复视频检测方法

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摘要

In order to monitor video streams in real-time or search large collections of video documents, several solutions based on near-duplicate video detection have been proposed in the literature. We present in this paper an architecture based on signature-based index structures coupling visual and temporal features and on an N-gram matching and scoring framework. The techniques we cover are robust and insensitive to general video editing and/or degradation, making it ideal for re-broadcasted video search. Through the use of signature-based indexing and N-gram matching and scoring, we identify corresponding query and index contents accurately in order to detect near-duplicate videos, even when these contents constitute only a small section of the videos being compared. Experiments are carried out on large quantities of video data collected from the TRECVID 02, 03 and 04 collections and real-world video broadcasts recorded from two German TV stations. An empirical comparison over two state-of-the-art dynamic programming techniques is encouraging and demonstrates the advantage and feasibility of our method.
机译：为了实时监视视频流或搜索大量视频文档，文献中提出了几种基于近重复视频检测的解决方案。我们在本文中提出了一种基于结构的基于签名的索引结构，该结构结合了视觉和时间特征以及一个N-gram匹配和评分框架。我们介绍的技术既健壮又对一般视频编辑和/或降级不敏感，因此非常适合重新广播的视频搜索。通过使用基于签名的索引以及N-gram匹配和评分，我们可以准确地识别相应的查询和索引内容，以便检测几乎重复的视频，即使这些内容仅构成要比较的视频的一小部分。对从TRECVID 02、03和04集合中收集的大量视频数据以及从两个德国电视台录制的真实世界视频广播进行了实验。对两种最先进的动态编程技术进行的经验比较令人鼓舞，并证明了我们方法的优势和可行性。

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