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EMD-Based Video Clip Retrieval by Many-to-Many Matching

机译:通过多对多匹配基于EMD的视频剪辑检索

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摘要

This paper presents a new approach for video clip retrieval based on Earth Mover's Distance (EMD). Instead of imposing one-to-one matching constraint as in [11, 14], our approach allows many-to-many matching methodology and is capable of tolerating errors due to video partitioning and various video editing effects. We formulate clip-based retrieval as a graph matching problem in two stages. In the first stage, to allow the matching between a query and a long video, an online clip segmentation algorithm is employed to rapidly locate candidate clips for similarity measure. In the second stage, a weighted graph is constructed to model the similarity between two clips. EMD is proposed to compute the minimum cost of the weighted graph as the similarity between two clips. Experimental results show that the proposed approach is better than some existing methods in term of ranking capability.
机译:本文提出了一种基于地球移动者距离(EMD)的视频剪辑检索新方法。我们的方法没有像[11,14]中那样施加一对一的匹配约束,而是允许多对多的匹配方法,并且能够容忍由于视频分区和各种视频编辑效果而引起的错误。我们将基于剪辑的检索分为两个阶段作为图匹配问题。在第一阶段,为了允许查询和长视频之间的匹配,采用在线片段分割算法来快速定位候选片段以进行相似性度量。在第二阶段,构建加权图以对两个片段之间的相似性进行建模。提出了EMD来计算加权图的最小代价,作为两个片段之间的相似度。实验结果表明,该方法在排序能力方面优于现有方法。

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