Abstract
People re-identification process provides relevant information in order to understand the scene. In this paper, we present a multiple-view oriented model for performing people re-identification in a camera network. An appearance model for different perspectives is generated from people trajectories. Global and local features besides path orientation are extracted from each person's image, given a short-term tracking. Experimental results based on different sets of features demonstrate the effectiveness of our system.
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