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Million-scale near-duplicate video retrieval system

In this paper, we present a novel near-duplicate video retrieval system serving one million web videos. To achieve both the effectiveness and efficiency, a visual word based approach is proposed, which quantizes each video frame into a word and represents the whole video as a bag of words. The system can respond to a query in 41ms with 78.4% MAP on average.