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In this paper, we present a large database of over 50,000 user-labeled videos collected from YouTube. We develop a compact representation called “tiny videos” that achieves high video compression rates while retaining the overall visual appearance of the video as it varies over time. We show that frame sampling using affinity propagation - an exemplar-based clustering algorithm - achieves the best...
This work extends the tiny images techniques developed by Torralba et al. to videos. A dataset of 6,612 videos was collected from YouTube in the Sports and News sections. We present a method for compressing the temporal dimension nonuniformly using affinity propagation. We show that nonuniform sampling using affinity propagation outperforms temporal sampling at uniform intervals, because it covers...
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