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The problem of automatically tracking a pedestrian within camera networks with non-overlapping field-of-view, known as person re-identification, is a challenging task with still suboptimal results. Different features have been proposed in the literature, specially colors which achieved the best results when fused in a unique feature representation. Despite being better than considering individually,...
The main challenges in person re-identification are related to different camera acquisition conditions and high inter-class similarities. These aspects motivated us to handle such problems by learning intra-camera discriminative models, based on training samples, to discover representative individuals for a given sample (probe or gallery samples), referred to as prototypes. These prototypes are used...
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