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An efficient algorithm for video sequence matching using themodified Hausdorff distance and the directed divergence

机译:使用修正的Hausdorff距离和有向散度的视频序列匹配有效算法

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To manipulate a large video database, effective video indexing and retrieval are required. A large number of video retrieval algorithms have been presented for framewise user query or video content query, whereas few video-sequence matching algorithms have been investigated. In this paper, we propose an efficient algorithm for video sequence matching using the modified Hausdorff distance and the directed divergence of histograms between successive frames. To effectively match the video sequences with a low computational load, we use the key frames extracted by the cumulative directed divergence and compare the set of key frames using the modified Hausdorff distance. Experimental results with color video sequences show that the proposed algorithms for video sequence matching yield better performance than conventional algorithms such as histogram difference, histogram intersection, and chi-square test methods
机译:为了操纵大型视频数据库,需要有效的视频索引和检索。已经提出了大量用于逐帧用户查询或视频内容查询的视频检索算法,而很少研究视频序列匹配算法。在本文中,我们提出了一种有效的视频序列匹配算法,该算法使用修改后的Hausdorff距离和连续帧之间的直方图定向发散。为了有效地以低计算量匹配视频序列,我们使用通过累积有向散度提取的关键帧,并使用修改后的Hausdorff距离比较关键帧集。彩色视频序列的实验结果表明,所提出的视频序列匹配算法比直方图差异,直方图相交和卡方检验方法等常规算法具有更好的性能。

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