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Hierarchical, non-uniform locality sensitive hashing and its application to video identification

机译:分层,非均匀局部敏感哈希及其在视频识别中的应用

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Searching for similar video clips in large video database, or video identification, requires finding the nearest neighbor in high-dimensional feature space. Locality sensitive hashing, or LSH, is a well-known indexing method that allows us to efficiently find approximate nearest neighbor in such space. We address two weaknesses of LSH when applied to the video identification problem. We propose two enhancements to LSH, and show that our enhancements improve the performance of LSH significantly in terms of efficiency and accuracy.
机译:在大型视频数据库中搜索相似的视频剪辑或视频标识,需要在高维特征空间中找到最近的邻居。局部敏感哈希(LSH)是一种众所周知的索引方法,它使我们能够有效地找到此类空间中的近似最近邻居。当应用于视频识别问题时,我们解决了LSH的两个缺点。我们提出了LSH的两项增强功能,并表明我们的增强功能在效率和准确性方面显着提高了LSH的性能。

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