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In this paper, we present a multiple human tracking approach that takes the single frame human detection results as input, and associates them hierarchically to form trajectories while improving the original detection results by making use of reliable temporal information. It works by first forming tracklets, from which reliable temporal information can be extracted, and then refining the detection...
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