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

机译:基于EMD的视频剪辑通过多对多匹配来检索

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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器距离(EMD)的视频剪辑检索的新方法。我们的方法允许多对多匹配方法,而不是将一对一匹配约束施加一对一匹配约束,而是能够容忍由于视频分区和各种视频编辑效果而抵御错误。我们将基于剪辑的检索标志为两个阶段的图形匹配问题。在第一阶段中,为了允许查询和长视频之间的匹配,采用在线剪辑分段算法来快速定位候选剪辑以进行相似度测量。在第二阶段,构建加权图以模拟两个剪辑之间的相似性。建议EMD将加权图的最小成本计算为两个剪辑之间的相似性。实验结果表明,在排名能力方面,该方法比某些现有方法更好。

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