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Shot-based similarity measure for content-based video summarization

机译:基于镜头的相似性度量,用于基于内容的视频摘要

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The rapid development of multimedia applications over the past decade requires efficient methods for video browsing. In this paper, we present an algorithm for video summarization with shot comparison. We analyze video content in the shot level, and we calculate the shot distance using the advanced Hausdorff distance. The advanced Hausdorff distance combines the Hausdorff distance and Boolean model, and it could compare two shots from the global view. When the shot similarity matrix is obtained, we group these video shots into several clusters using the affinity propagation cluster method to remove redundant video content. Performance evaluation on ten video sequences are given to illustrate the proposed algorithm.
机译:在过去的十年中,多媒体应用的快速发展需要有效的视频浏览方法。在本文中,我们提出了一种具有镜头比较的视频摘要算法。我们在镜头级别分析视频内容,并使用高级Hausdorff距离计算镜头距离。先进的Hausdorff距离结合了Hausdorff距离和布尔模型,并且可以比较全局视图中的两个镜头。当获得镜头相似度矩阵时,我们使用亲和力传播聚类方法将这些视频镜头分组为几个聚类,以删除多余的视频内容。给出了对十个视频序列的性能评估,以说明所提出的算法。

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