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Consistent Re-identification in a Camera Network*
Abir Das, Anirban Chakraborty, and Amit K. Roy-Chowdhury
Dept. of Electrical Engineering, University of California, Riverside, CA 92521, USAAbstract. Most existing person re-identification methods focus on finding similarities between persons between pairs of cameras (camera pairwise re-identification) without explicitly maintaining consistency of the results across the network. This may lead to infeasible associations when results from different camera pairs are combined. In this paper, we propose a network consistent re-identification (NCR) framework, which is formulated as an optimization problem that not only maintains consistency in re-identification results across the network, but also improves the camera pairwise re-identification performance between all the individual camera pairs. This can be solved as a binary integer programing problem, leading to a globally optimal solution. We also extend the proposed approach to the more general case where all persons may not be present in every camera. Using two benchmark datasets, we validate our approach and compare against state-of-the-art methods.
Keywords: Person re-identification, Network consistency
Electronic Supplementary Material:
LNCS 8690, p. 330 ff.
lncs@springer.com
© Springer International Publishing Switzerland 2014