Person Re-Identification Based on SAD and Histogram in a Non-Overlapping Camera Network

In this paper, we present the conception and implementation of a system for person re-identification in a camera network, based on the appearance. This system aims to build an online database that contains the history of every person that enters the field of view of the cameras. This system is able to associate an identifier to each detected person, which keeps this identifier in the same camera and in other cameras even if he or she disappears and then appears again. Our system comprises a moving objects detection step that is implemented using the Mixture of Gaussians method and a proposed difference method, to improve the detection results. It also comprises a tracking step that is implemented using the sum of absolute differences algorithm. The re-identification stage is realized using three steps: the tracking for the temporal association, the histogram and the new smart exploitation of the interpolation technique for comparison. The global system was tested on a real data set collected by three cameras. The experimental results show that our approach gives very satisfactory results.