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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.